Lateralization of Cognitive Functions: The Visual Half-Field Task...
Transcript of Lateralization of Cognitive Functions: The Visual Half-Field Task...
Lateralization of Cognitive Functions: The Visual Half-Field
Task Revisited
Ark Verma
Promotor: Prof. Dr. Marc Brysbaert
Proefschrift ingediend tot het behalen van de academische graad
van Doctor in de Psychologie
2014
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
Something I owe to the soil that grew
More to the life that fed
But most to Allah who gave me two
Separate sides to my head.
I would go without shirts or shoes,
Friends, tobacco or bread
Sooner than for an instant lose
Either side of my head.
Kim (1901)
--By Rudyard Kipling
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
Table of Contents
Acknowledgment i
Chapter 1: Introduction 3
Mythology of Lateralization 3
From mythology to science: a brief history
Of Investigations into Hemispheric Asymmetry 6
Methods Investigating Hemispheric Asymmetry
WADA Test 11
Behavioral Methods Investigating Hemispheric Asymmetry 13
EEG & MEG Methods 21
Hemodynamic Neuroimaging Methods 25
Evidence of Hemispheric Specialization
from Clinical Studies 28
from Split-Brain Patients 30
from Neurologically Intact Individuals 33
Structural & Functional Indices of Hemispheric Asymmetry 35
Structural Asymmetry between the Hemispheres 37
Functional Asymmetry in Visuospatial Processing 42
Motivations for the Current Thesis 48
Outline of the Current Thesis 50
References 52
Chapter 2: A right visual field advantage for tool recognition
in the visual half-field paradigm 79
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
Introduction 82
Method 92
Results 96
Discussion 98
References 103
Chapter 3: Avalidated set of tool pictures with matched objects and
non-objects for laterality research 109
Introduction 111
Method 120
Results 125
Discussion 130
References 133
Appendix 139
Chapter 4: Symmetry detection in Typically and Atypically
Speech Lateralized Individuals: AVisual Half-field Study 153
Introduction 156
Experiment 1 163
Method 164
Results 168
Discussion 169
Experiment 2 171
Method 172
Results 172
Discussion 173
Experiment 3 174
Method 177
Results 177
Discussion 179
General Discussion 180
Conclusion 183
References 184
Chapter 5: Evidence for Right Hemisphere Superiority in Figure Matching
& Judging Negative Emotions from Facial Expressions 195
Introduction 197
Experiment 1 203
Method 203
Results 205
Discussion 207
Experiment 2 207
Method 207
Results 210
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
Discussion 212
Experiment 3 212
Method 213
Results 215
Discussion 217
General Discussion 219
References 222
Chapter 6: General Discussion 230
The Visual Half-Field Paradigm: Conclusions 244
References 246
Nederlandse Samenvatting 249
Referenties 255
Acknowledgments
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Acknowledgments
Now, that four years of an academic journey culminate into this doctoral thesis, which I hereby
present before you, it is most befitting that I gratefully thank and acknowledge all those without
whom this would never have been possible.
First of all, I would like to thank my supervisor Prof. Dr. Marc Brysbaert, for his
unwavering support and guidance throughout these years without which this thesis could not
have been completed. I can vividly remember every instance you encouraged me to push harder
and take one more step, to reach this day. As an immigrant doctoral candidate, coming from
India to Gent, Belgium, there were certainly moments when I ran into difficult times, but I must
thank you for the enormous patience and compassion with which you would always persuade me
back on track and spur me into action, to understand and conduct quality research. Besides the
immense knowledge and your vast experience, you have always been an example to aspire for,
with the amount of hard work and dedication that you put into research and also with the passion
that still drives your every endeavor. I will certainly always keep it as a goal to reach out for in
the future years of my academic career.
I would like to thank Lise Van der Haegen, for your help in conducting the experiments
listed in Chapter 3, and also later, in writing of the manuscript. I would always remember you as
a very hard working colleague who would always have answers to my queries and who would
always be ready to help me out while I was still learning the ways to function in the university
and conduct research.
I would also like to express my heartfelt appreciation and gratitude towards Emmanuel
Keuleers, my senior colleague and officemate. You have been one of the closest friends I have
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made during my stay here, in Belgium. You have been my host to this beautiful country and
made me aware of its intricacies, its systems and thought processes. Besides, I will always be
indebted for your efforts in helping me settle down here for these four years, in many ways. At
this moment, I can remember the various rides you took me along to, right from the supermarkets
to restaurants, to those lovely walks in the nature and an introduction to mushroom-picking. I can
also recall the many discussions we have had on a broad range of topics from academics to
politics to philosophy, also some in which I tried to rub off my passion for cricket unto you and
also where we shared our unique styles of cooking, wherein you introduced me to European
cuisine (and helped me appreciate it, sans the extra salt and spices!!!). I am sure these moments
will stay etched in my memory forever and will keep reminding me of the good times I shared
with you.
I would like to thank Prof. Dr. Guy Vingerhoets, Prof. Dr. Wim Fias and Prof. Dr.
Wouter Duyck, who constituted my doctoral guidance committee, for their valuable inputs that
went a long way in enhancing the research presented in this thesis. I would like to thank them for
always taking out time to be present in annual meetings and their enthusiastic comments that
would often help me improve upon my experiments and provide a direction to the thesis.
I would like to thank members of my research group Qing, Wim, Maaike, Michael and
Pawel who have always been kind and helpful towards me. Also, I would like to thank Evelyne
Lagrou for her help in finalizing the thesis for publication.
I would also like to thank the academic and technical staff in the Department of
Experimental Psychology, where I conducted my work. I would especially like to thank Lies,
Linde & Christophe for being very helpful throughout these four years.
Acknowledgments
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Also, I would like to thank a host of undergraduate students, who participated in my
experiments. I can recall having enjoyed answering your questions about my research and my
experiences as a researcher in UGent. This work owes a lot to your patience and co-operation.
Apart from those at the university, there are many people I need to thank, who shared this
dream of obtaining a PhD with me and contributed in their own unique ways to bring it to a
reality.
I would like to thank Ms. Priyanka Srivastava and Ms. Monika Lohani who convinced
me for applying for a PhD, in the first place and helped me take the very first steps in this
direction. My teachers, Dr. Bhoomika R. Kar and Prof. Narayanan Srinivasan, for their constant
support and encouragement, even though it has been years since I left the Centre of Behavioral
and Cognitive Sciences, University of Allahabad.
I would then like to thank my parents, Mr. Akhilesh Kumar and Mrs. Rajkumari
Srivastava for being the constant source of strength and belief which held me together and
inspired me to carry on. I would also like to mention my siblings, Sagar Verma and Tripti
Verma who always shared my responsibilities and encouraged me in every way. I would like to
thank my parents-in-law Dr. Santosh Khare and Mrs. Vandana Khare, who have always believed
in me and encouraged me in my endeavors, and also my sisters-in-law Shraddha Khare and
Gaurisha Khare who have been so supportive and encouraging.
I have been fortunate to have had some wonderful friends throughout my life and these
years of PhD were no exception. I would like to acknowledge the amazing friendships that
developed and blossomed during my stay in Gent and also those that remained in India; as they
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have always shared my feelings and helped me get through the different phases of this
memorable journey.
Finally, I would like to thank the most prominent of these friendships, that which I shared
with my wife, Vatsala Khare, who has always stood by me through thick and thin and
encouraged me by creating a protected home around me, which never let me feel too homesick
and always proved to be a nest which was always there to return to. I value your many sacrifices
and love with which you have supported me, to bring this journey to a successful closure in form
of this thesis.
Chapter 1| Introduction
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Chapter 1: Introduction
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Chapter 1| Introduction
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Chapter 1: Introduction
That the human brain consists of two hemispheres, i.e. the left and the right half, has evoked
pervasive fascination for over centuries now, both in the academic & popular discussions.
However, the mythology and symbolism associated with left & right dates back to ancient times,
long before organized scientific investigation took over the mantle to understand the
complementary and interdependent functioning of the two cerebral hemispheres.
In order to put contemporary laterality research in perspective, I will first revisit the
mythological avenues that first brought the notions of left and right into the domain of human
curiosity. Then, I will examine the historical evolution of research on cerebral lateralization from
split brain patients to neurologically intact individuals. I will then review the different methods
employed by scientists to investigate the functions of the two hemispheres. Finally, I will discuss
the evidence regarding structural and functional asymmetry in the human brain and evidence for
lateralized processing in the visual and auditory processing domains. At the end, I will
summarize the evidence, and point out the motivations for the work undertaken in the current
thesis.
Mythology of Lateralization
The dichotomized notion of hemispheric function possibly emanates from long standing
beliefs about duality: left & right or good & evil that have transcended human thought across
continents & cultures. In his review of myths associated with laterality, Corballis (1980) recounts
that such beliefs have been around for ages and have exerted enormous influence on religion,
philosophy, literature and scientific thought.
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Different cultures have held surprisingly similar beliefs about the left and right, from the
Maori civilization of New Zealand to the Isis cult of Egypt and also in ancient Israel (Bradshaw
& Nettleton, 1983, Corballis, 1980). Hertz (1909) documented the left-right symbolism in the
Maori culture, from New Zealand. For the Maori people, the right side of the body was
considered the sacred side, associated with the Gods, with the virtues of strength and life; the left
side, on the other hand was considered to be associated with demons, profanity, weakness &
death. The Maori expression tama tane or “the male side”, also refers to the right, and is
associated with strength, virility, the east, and creative force; the expression tama wahine or “the
female side” is associated with opposite of these virtues (Best, 1901, 1905). Similarly, In the
Pythagorean tradition of ancient Greece, the right side was associated with one, odd numbers, the
light, the straight, the good and the male; while the left corresponded to the many, the even
numbers, the dark, the crooked, the evil & the female. Such a bias towards the “right-male”
prototype may be characteristic of many patriarchal societies; and it sometimes gets reversed in
case of matriarchal societies. For example, the Isis cult of ancient Egypt preferred Isis (a female
Goddess) over Osiris (the male God), mother over son, night over day and also the Isis
procession was led by the image of a left hand.
Interestingly, the bias towards the right side in this dichotomy is also present in the Bible,
as pointed out by Corballis (1980), as in Matthew 25:33-41; 41:
And He will set the sheep upon His right hand and the goats upon His left. Then shall the King
say to those upon His right, “Come, ye blessed of my father, and inherit the Kingdom prepared
for you from the beginning of the world.”…Then shall He also say to those on the left, “Depart
from me, ye accursed, into everlasting fire prepared for the Devil and His angels.”
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Another example of the same can be derived from Hindu mythology, where the words for
right and left are dakshina & vama respectively , whereas dakshina is considered to be
straightforward, honest, amiable, compliant and submissive, vama is symbolized as contrary,
reverse, crooked & opposite. Also, vama is considered to be the side of females, often regarded
as the source of maya (illusion) and root of all evils.
Such polarized beliefs about the left and right were mostly pinned to the phenomenon of
handedness and might have stemmed from the fact that one of the two patterns of handedness
outnumbers the other by a large margin. As the left handed people were so few, they were often
regarded as anomalous and thown away as a stigma. Indeed, it has been pointed out that the
incidence of left handedness has been only about 10% for around 50 centuries (Coren & Porac,
1977), while right handedness appears to be a dominant pattern for even the Australopithecus,
which are said to use their right-hand to attack their victim with stones (Dart, 1949).
Initially, the cause of handedness was also attributed to other bodily asymmetries, for
instance, the rightward displacement of liver by Sir Francis Bacon (Corballis, 1980) or early
warfare (for a review see Wile, 1934). It is now accepted that the asymmetry of handedness has
its roots in the asymmetry of the brain, and that the left hemisphere of the brain is the dominant
hemisphere for the majority of people, which accounts for the high numbers of right-handed
people.
The current state of knowledge about the cerebral hemispheres has developed over a
period of time, gradually taking into account developments from phrenology to
neuropsychology, and evidence from split brain patients, epileptic patients, patients who suffered
from various manifestations of cortical atrophy and also a large number of studies done on
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neurologically intact individuals. In the next section we will briefly review the course of this
development.
From Mythology to Science: A Brief History of Investigations into
Hemispheric Asymmetry
Investigations into the functional asymmetry of the two hemispheres have closely
evolved together with the more general investigations of the localization of mental functions in
the brain. Accordingly, Anne Harrington (1995) in her review on the history of laterality research
remarks, “many of the fundamental assumptions – the unquestioned truths – that provide the tacit
grounding for modern laterality research have their source in an early nineteenth-century
approach to visualizing mind-brain relations called localization theory” (p.3). This new approach
that sought to break down the various attributes of mind into smaller building blocks based in the
brain still forms the basic principle in neuroscience.
When, in 1865, Paul Broca, the French physician, declared that speech was controlled by
the left hemisphere of the brain; he broke major ground in the field of neuroscience in general &
laterality research in particular. However, steps in the said direction had been taken long before
this moment (for a detailed review, see Harris (1999)).
Franz Joseph Gall, the Austrian anatomist and physician had developed his theory of
phrenology or organology by examining the skulls of people with “very one-sided talents” i.e. a
severe lack or abundance of certain abilities or “faculties”. Gall theorized about 27 faculties or
talents of the human mind divided into two groups as intellectual and moral, which were situated
in the brain; the intellectual in the anterior portions and the moral/passions in the posterior part
of the brain. In many ways, hence, Gall was one of the pioneers of cerebral localization along
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with few others like Thomas Willis (1681/1965), Georgius (Jirf) Prochaska (1784), and Emanuel
Swedenborg (1740-1741). Gall’s attempts at establishing phrenology as a credible theory
postulating cerebral localization of mental abilities, was met with mixed response from his
contemporaries; while he was opposed by critics as Thomas Sewall (1837) & Marie Jean Pierre
Flourens (1824, 1846) there was also supporting evidence produced by Jean Baptiste Bouillaud
(1825, 1839-1840), Jacques Etienne Belhomme (1848) in France and Samuel Jackson (1828),
Henry Dickson (1830), and Daniel Drake (1834) in America.
However, hemispheric specialization was not the main concern of Gall; he and his
contemporary Marie Francois Xavier Bichat (1805/1809) in their observations of the human
brain concluded that “all parts of the brain resemble each other on every side”, and Bichat
declared the law of symmetry which goes as “two parts essentially alike in their structure,
cannot be different in their mode of acting” (Harris (1999), translation by T. Watkins, pp. 8, 14).
As Gall, being a prominent physician of the era, also endorsed this view, structural & functional
symmetry became the dominant perspectives and contrary evidence presented by Felix Vicq
d’Azyr (1786), Joseph Francois Magendie (1827) & Bouillaud (1825) was never accredited.
It was not until Paul Broca, a French physician, encountered his first aphasic patient, M.
Leborgne, popularly known as “Tan”, as all he could articulate was “tan, tan, tan” that concrete
evidence for cerebral localization of speech began to surface. On posthumous examination of
Leborgne’s brain, Broca (1861a, 1861b, and 1861c) found extensive softening throughout the
left frontal lobe, more specifically in F3, the third convolution, corresponding to the triangular
and opercular parts of the inferior frontal gyrus. Similar areas of the brain were implicated in his
next aphasic patient named M. Lelong (Broca, 1861b). Even though cautious at first, with more
and more evidence indicating that the pattern of cerebral atrophy was focused on the left side of
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the brain, Broca finally declared in 1865 that speech could be lateralized in the left hemisphere;
though he was certain that “this does not allow us to say that the left hemisphere is the exclusive
seat of the general faculty of language” (Broca 1865, as quoted in Harris (1999)). Broca’s work
with aphasic patients, who were later known as patients of “Broca’s aphasia” or “motor
aphasia”, established the role of the left hemisphere in language production. Later, evidence
indicated the involvement of the left hemisphere in language comprehension as well.
Evidence regarding the role of the left hemisphere in language comprehension came from
cases of sensory aphasia. Early reports came from the German physician Johann Gesner (1769-
1776) and in an interesting self-report by the Montpellier physician Jacques Lordat (1843).
While Gesner described a patient with fluent but meaningless speech; Lordat reported that since
the age of 52, he had become “incapable of understanding sounds that I heard quickly enough to
grasp their meaning” (translated by J. Hubert, quoted in Riese 1954, p. 237). However, the cause
of such symptoms could not be clearly identified, as even though there were hints of the
involvement of posterior left hemisphere lesions, there was not enough data or theory to support
such claims.
Carl Wernicke (1874), a student of Theodore Meynert, provided useful data and theory to
explain these symptoms, in his doctoral dissertation, Der Aphasische Symtomencomlex [ On the
Aphasia Symptom Complex]. He described the case of a 59-year old, Suzanne Adam, who could
“comprehend absolutely nothing which was said to her”. Wernicke applied Meynert’s
neuroanatomical approach (Meynert 1866, 1872) to the study of aphasia and brought fresh
insights & revelations to the role of left hemisphere in language functions. Meynert’s approach
had three important highlights; firstly, it proposed that the anterior parts of the brain were
involved in motor functions, while the posterior parts of the brain were responsible for sensory
Chapter 1| Introduction
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functions; secondly, it simplified the tangle of white matter tracts and distinguished them as: the
ascending & descending pathways (cortical-subcortical connections), association pathways
(intrahemispheric connections), and the commissural pathways (interhemispheric pathways);
finally Meynert (1866) described the case of a 23-year old man, with paraphasic speech and
inability to understand. Autopsy of the patient revealed an infarct in the parietal operculum and
posterior insula, which led Meynert to conclude that, “its (Sylvian fissure) posterior part
contains the auditory cortex” where “’sound-images’ are formed”.
On the basis of these, Wernicke proposed that movements for articulation of speech were
stored in the Broca’s area while the traces of the sounds of words were stored in the posterior
regions, later known as “Wernicke’s Area”. Consequently, lesions in these posterior parts were
supposed to lead to loss of language comprehension ability, which came to be known as
Wernicke’s aphasia. Hence, the contribution of the left hemisphere in language comprehension
was confirmed.
Another major step, which set the ball rolling for decades of research on hemispheric
specialization, was the work by a British neurologist, John Hughlings- Jackson. In 1874, citing
clinical evidence, Hughlings-Jackson attributed the “recognition of objects, places, persons, &
c.” to the right hemisphere; thereby proposing that the right cerebral hemisphere might be
specialized for processing visuo-spatial information. Hughlings-Jackson, presented more
evidence for the special role of right hemisphere in spatial processing while treating a 59-year
old patient, Eliza T in 1876, who suffered from symptoms of visual disorientation, spatial
localization, in dressing herself etc.; later her autopsy revealed a “large gliomatus tumor” in the
temporo-occipital region of the right hemisphere. Importantly, Hughlings Jackson also provided
evidence for the contribution of the right hemisphere in production of emotional utterances; he
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noted that under strong emotion, speechless patients (i.e. suffering from left hemisphere
damage/aphasia) could utter oaths or “automatic phrases”. Similar evidence had earlier been
observed by Broca (1861a) also, as “Tan” could utter a curse when angry; hence indicating the
ability of emotional expression was not damaged. Another important contribution in this regard
was made by Jules Luys (1879, 1881), who described the differences between patients suffering
from left-hemisphere lesions &right hemisphere lesions respectively; and pointed out that while
“… right hemiplegics are more or less apathetic …silent, passive and stricken with hebetudes
(dullness/lethargy); left emotional hemiplegics are … afflicted with an abnormal
impressionability. They respond, (…) in a limping voice, broken up by a kind of sobbing… (at
other times) they are boisterous and loquacious, their face is congested…eyes sparkle”.
Such case descriptions coupled with other evidence established the right hemisphere
specialization for emotion; and promoted the right hemisphere as the irrational, emotional
hemisphere. Luys’ (1879, 1881) work was instrumental in developing related research in this
domain.
In light of these groundbreaking studies by the end of the 19th
century, it became evident
that not only the functions of the mind could be localized to the tangible brain; there were also
differences in the way these functions would be organized in the left and right halves of the
brain. This knowledge spurred decades of research into the asymmetries of the structure &
function of the brain. In the next section, I will survey the various methods that have been used
by researchers to investigate hemispheric asymmetries for various cognitive functions, such as
word recognition, face processing etc. The methods too, have evolved during the course of time,
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from the earliest, the WADA test till the recent hemodynamic methods as fMRI. Likewise, they
have changed the field’s approach and perception of the asymmetries in human behavior.
Methods Investigating Hemispheric Asymmetry of Cognitive Function
Intracarotid Amobarbital Test (WADA Test)
The intracarotid amobarbital testing procedure was first developed by Japanese-Canadian
epileptologist Juhn Atsushi Wada (1949), as a method to determine cerebral dominance for
language functions, prior to surgical sectioning of the brains of epileptic patients. Over the
decades, it has been modified to diagnose memory functions and predict the vulnerability to
amnesia (Milner, 1962). More recently, the WADA test has been used to evaluate lateralized
distribution of language and memory functions. Also, a variety of modern neuro-imaging
findings have been validated and correlated with WADA test measurements.
Basically, the WADA procedure involves injection of an anesthetic agent like sodium
amobarbital into the internal carotid artery via a catheter. The anesthesia effectively blocks or
shuts down the functions of the hemisphere where the drug is injected; and hence makes testing
of the functions partaken by the said hemisphere by virtue of deficiency or absence. The
anesthetic injection is usually presented for baseline testing for language and memory functions,
for comparisons with post-injection performance.
Usually after the injection of the anesthetic to the dominant hemisphere global aphasia
sets in, lasting for a few minutes; on resumption the speech is typically characterized by
paraphasic errors and perseverations; while in case of the non-dominant hemisphere, the patients
can still have relatively unaffected speech though other functions may be affected. Along with
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the determination of speech related functions and language dominance, the WADA test has also
been used to test for the lateralization of memory functions (Dodrill & Ojemann, 1997).
Off late, findings from various new methods have been correlated with those of the
WADA test. Lehericy et al. (2000) compared the indices of frontal and temporal language
language dominance obtained from the fMRI and the WADA tests and concluded that while
there was congruence between the two methods where the frontal lobes were concerned there
was less coincidence of measures for the temporal lobes. Other studies also compared language
lateralization measures obtained from fMRI and the WADA tests and found high correlation
between the two (Binder et al., 1996; Desmond et al., 1995).
Despite its usefulness in diagnostic information about cognitive functions (particularly
language and memory) seated in the brain, the WADA test has certain limitations. For instance,
it has been suggested that the documented predictive value of the WADA test is suboptimal
(Ojemann and Kelley, 2002). For instance, the cerebral amytal test is found to be only partially
predictive of post operative verbal memory deficits when measured via neuropsychological tests
(Dodrill and Ojemann, 1997). Further, the WADA test involves up to 0.7% risk of carotid artery
dissection (Lodenkemper et al., 2002). Other related risks include those of cerebral infarction,
arterial spasms and transient femoral neuropathy. As the WADA test is an invasive method, it is
less suitable for testing with normal participants. Apart from these methodological considerations
also affect the WADA test studies. For instance, the procedure for the WADA test is non-
standardized across testing centers (Rausch et al., 1993) and evidence regarding failure of
anesthetization with amobarbital in patients taking antiepileptic drugs has been reported
(Bookheimer et al., 2005).
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Finally, the WADA test does not allow further localization of language functions in each
hemisphere, as it is strictly a test of language lateralization; thus limiting its overall scope. As a
result recently, researchers have looked for noninvasive alternatives to the WADA test, such as
the near infrared spectroscopy method (Watanabe et al. 1998).
Behavioral Methods Investigating Hemispheric Asymmetries
The Dichotic Listening Method
The Dichotic Listening method, i.e. simultaneous presentation of same/different sounds
to the left and right ear respectively, was first introduced by Broadbent (1956), when he
presented digits from 0-9 to test different aspects of attention. As an experimental paradigm it
developed throughout the 1960s with a view to study functional cerebral lateralization (Kimura,
1967, Hugdahl, 2011).
Behavioral studies testing of lateralization for speech related functions employ the
dichotic listening technique (for detailed reviews see Hugdahl, 1995, 2003). Here, two different
auditory stimuli are presented at the same time, one in each ear (Kimura, 1967), and the subject
is asked to report the item heard first, or to discriminate between the two heard items, depending
on the requirements of the experimenter. Typically better recall from the right ear is termed as
right ear advantage and is attributed to the fact the contralateral projections are stronger and may
block those from ipsilateral connections (Kimura, 1967; Bryden, 1988). Importantly,
hemispheric advantages in processing have been manifested through ear advantages for the kind
of stimuli being processed; for e.g. right ear advantages for verbal stimuli and left ear advantages
for some nonverbal/emotional stimuli have been observed. Accordingly, different verbal and
non-verbal variants of the paradigm have been used over the years (Bryden, 1988; Hugdahl,
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1995, 2003). One of the most widely used paradigms has been the presentation of consonant-
vowel pairs, made up of six stop-consonants: /b/, /d/, /g/, /p/, /t/, & /k/, known as the C-V
syllables paradigm (Hugdahl, 2011). The major findings coming from the DL paradigm have
been that, participants with left-hemispheric dominance for language are found to be faster and
more accurate in reporting verbal items presented in the right ear, dubbed as the right ear
advantage (REA; Kimura, 1961; Studdert-Kennedy & Shankweiler, 1970) and conversely they
exhibit a left ear advantage for tasks involving the recognition of musical or environmental
sounds (Boucher & Bryden, 1997; Brancucci & San Martini, 1999, 2003; Brancucci et al. 2005;
Brancucci et al., 2008). Anatomically, the paradigm is based on the fact that monaural input to
each ear is represented in both cerebral hemispheres with an advantage for contralateral over
ipsilateral pathways (Fujiki et al., 2002). However when different stimuli are presented
simultaneously (i.e. dichotically) to the two ears, interactions between auditory pathways make
the situation more complex. Two major theories have been offered in this regard, the “structural
theory” (Kimura, 1967) postulates that the during the DL setup the contralateral auditory
pathway suppresses the ipsilateral pathway; hence auditory stimuli presented to the left ear are
processed first by the right cerebral hemisphere and vice-a-versa. Alternatively, the “the
attentional theory” has proposed that ear advantages are a result of priming, i.e. attending to a
particular type of stimuli and not due to the anatomical properties of the auditory system. Recent
evidence however, indicates support for the interplay of both structural and attentional factors
(Hugdahl et al., 2000; Jäncke et al., 2003; Thomsen et al., 2004).
Hugdahl (2011) presents evidence for a reasonably high reliability and validity of the DL
paradigm. For instance, while an early study reported a high reliability for the DL paradigm of
0.90 (Speaks, Niccum & Carney, 1982); more recent accounts as Voyers & Rodgers (2002) have
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also reported a high level of test-retest reliability. Several efforts regarding validating the
findings of the DL method as the right ear advantage (REA), have been successful using modern
neuroimaging methods, such as PET (Hugdahl et al., 1999) and fMRI (e.g. Van den Noort,
Specht, Rimol, Ersland, & Hugdahl, 2008; Van der Haegen, Westerhausen, Hugdahl, &
Brysbaert, 2013), and electrophysiology measures, such as EEG (Brancucci et al., 2005), and
MEG (Brancucci et al., 2004).
The DL paradigm has an appeal beyond the basic function of determining language
lateralization. DL as a paradigm has been used to investigate emotional processing in
individuals. Some of the earliest works presented emotionally intoned sentences (sentences in
angry, happy or sad voices) compared with monotone sentences and found a left ear advantage
(LEA) for the processing the emotional content of the sentences and a right ear advantage (REA)
for the verbal content (Ley & Bryden, 1982; Shipley-Brown et al., 1988). LEA for emotional
prosody has also been reported for nonsense words spoken in happy, sad, angry or fearful
prosody (McNeely & Netley, 1998). More recent experiments (Techentin & Voyer, 2007;
Techentin, Voyer & Klein, 2009) presented emotional valent stimuli in congruent or incongruent
intonation (for e.g. happy message with sad intonation) and found a stronger LEA for
incongruent target detection; indicating that an incongruent emotional tone can enhance the
emotional information of the content.
Further, the DL task has been instrumental in uncovering patterns of unusual
lateralization associated with psychopathology. In his review, Bruder (1983) presented evidence
that schizophrenic and depressed patients, showed smaller ear asymmetries on a dichotic
listening task and thus reduced lateralization when they were more ill as compared to when they
were faring better with the disease. More recently, Ocklenburg, Westerahausen, Hirnstein &
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Hugdahl (2013) conducted a meta-analysis and compared schizophrenic and normal participants
and found that schizophrenic patients showed weaker cerebral lateralization for language as
compared to the normal individuals. Finally, the DL paradigm has also helped to establish that
auditory verbal hallucinations in patients with schizophrenia are a result of aberrant speech
lateralization coupled with failure to focus attention (Hugdahl et al., 2012).
All in all, we can say that the DL paradigm has been a useful method to investigate not
only cerebral lateralization of language, but also other cognitive functions that are related with
auditory processing.
In the next section I will talk about the visual half-field method (VHF method) for
investigating the functional asymmetry between the two cerebral hemispheres.
The Visual Half-Field Method
One of the most popular methods of investigat ing the lateralization of cognitive
functions at the behavioral level has been the visual half-field method (Hunter & Brysbaert,
2008) along with the dichotic listening method.
The VHF task involves tachistoscopic presentation of stimuli in the left or the right
parafovea, and measurement of the participants’ speed and accuracy as a function of the
presentation location. The task is based on the logic that information displayed in the right visual
half-field (RVF) is initially projected to and processed by the left hemisphere while the
information presented to the left visual half-field is initially handled by the right hemisphere.
Exploiting this basic anatomical principle of the human visual system, researchers predicted that
people with left hemispheric language dominance should show a RVF advantage in a VHF task
Chapter 1| Introduction
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using verbal stimuli while the reverse should be true for participants with right hemispheric
language dominance.
The Visual Half-field method has been extensively used for research on the lateralization
of various cognitive functions over the last few decades. As a method the visual half-field
method places minimal demands on the experimenter, as it can be set up easily with the help of a
computer, a microphone and a button box (or keyboard) (Hunter & Brysbaert, 2008).
In one of the earliest studies, Mishkin & Forgays (1952) presented words unilaterally to
the left or the right of fixation to investigate visual hemifield asymmetries in visual word
recognition and found a right hemifield advantage. In a later study, Hines, Satz & Clementino
(1973) found better recall for digit sequences presented in the right visual half-field for right
handers. Apart from measuring effects for processing of verbal tasks, Ornstein, Johnstone,
Herron & Swencionis (1980) reported higher right hemisphere engagement in visuo-spatial tasks
with the exception of mental rotation.
Using the visual half-field paradigm in combination with ERPs, Kayser et al. (1997)
demonstrated right hemispheric specialization for processing pictures with negative valence.
Michimata (1997) showed a significant right hemisphere/left visual field advantage in judging
for coordinate spatial relations. Earlier, Laeng & Peeters (1995) had shown left and right
hemisphere advantages for categorical and coordinate judgment tasks respectively. Nagae &
Moscovitch (2002) showed that the recall of emotional words was more dependent on the right
cerebral hemisphere as compared to the left cerebral hemisphere. Wilkinson & Halligan (2002)
showed that the right hemisphere is faster and more accurate than the left hemisphere in judging
pre-bisected lines, in a perceptual landmark task. Koivisto & Revonsuo (2003) showed that the
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right hemisphere is more adept at gauging the overall shape of objects from memory while the
left hemisphere is adept at matching whether the parts of objects match with memory
representations. In a different area, Coulson & Williams (2005) used the visual half-field method
in combination with ERPs and found evidence for right hemisphere involvement in joke
comprehension.
Despite churning up numerous findings regarding the lateralization of a wide array of
cognitive functions at the behavioral level over the last three decades, there have been doubts
about the reliability and validity of the findings that came from visual half-field research.
Hunter & Brysbaert (2008) reviewed the problems associated with the method and
recommended a series of steps to strengthen the paradigm. For instance, Voyer (1998) pointed
out that the reliability of VHF tasks was only 0.56 for verbal tasks and 0.28 for non-verbal tasks.
Moreover, the VHF advantages correlated only at 0.26 with the ear advantages (indexed in a
dichotic listening task) for the same participants. Attempts at revalidating findings from the VHF
experiments with more recent methods like functional transcranial doppler sonography (fTCD)
have also not always yielded encouraging findings. Krach, Chen & Hartje (2006) measured
hemispheric differences in blood flow in a word generation task, also they sought to compare the
laterality indices (LIs) obtained from a VHF experiment to those obtained from fTCD. They
found that the individual VHF differences did not correlate with the LIs based on fTCD in the
word generation task measured during the VHF task (r=0.18, n=58).
Overall there has been criticism about the validity of behavioral tasks for the
measurement of the laterality of language and other functions, for instance Heron (1957) argued
that VHF differences were caused by attentional biases towards either visual field and not due to
Chapter 1| Introduction
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hemispheric specialization. Hunter & Brysbaert (2008) observed that these criticisms were
probably due to many of the earlier tasks being suboptimal. Further, they predicted that some of
the low correlations reported were possibly due to bad testing rather than to the fact that VHF
differences are not fit for assessment of cerebral lateralization. Hunter & Brysbaert (2008)
recommended several steps to design a good VHF task:
Having a considerable number of trials.
Using matched stimulus sets to be presented across visual half-fields.
Using bilateral stimulus presentation (also recommended by Boles (1990)).
Using clearly visible stimuli.
Using adequate fixation control at the beginning of a trial.
Also testing left-handed participants to increase the range of LIs.
Possibly validating against an fMRI study.
They used the recommendations to design VHF picture naming and word naming tasks
respectively; and compared LIs obtained from RT (reaction time) patterns in these tasks to the
LIs obtained in the same individuals during a mental word generation task in the fMRI scanner.
A direct link was established between the findings of the two behavioral tasks and the fMRI task;
as participants with a clear RVF advantage in the picture and word naming tasks were shown to
be left hemisphere dominant in the scanner, while the ones with a clear LVF advanatge turned
out to be right hemisphere dominant. The authors concluded that a well designed visual half field
task can be used to assess language lateralization reliably. A further validation was provided by
Van der Haegen, Cai, Seurinck & Brysbaert (2011) who used the same tasks and tested a large
sample of 250 left handers and again compared the obtained LIs with those obtained in the fMRI
scanner; and found that none of the left handed participants who showed clear right visual field
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(RVF) advantages in the VHF word and picture naming was found to have bilateral or right
hemisphere dominance in the scanner, while 80% of those participants with a consistent LVF
advantage for both picture naming and word naming showed right hemisphere language
dominance in the scanner. Such a finding can be taken to make a strong case for using VHF tasks
for assessing cerebral lateralization of not only language related functions but also for other
cognitive functions as well, if the tasks are well designed or designed in accordance with the
recommendations of Hunter & Brysbaert (2008).
Using the VHF method has advantages over choosing neuroimaging techniques like,
fMRI, PET, fTCD etc. right at the onset of a new hypothesis. As mentioned earlier, setting up a
VHF task is cheap and easy, both in terms of resources and also the knowhow to handle the data
afterwards; while on the other hand each fMRI scan can cost up to a few hundred Euros, and
sophisticated technical knowledge about data gathering and analysis is required. This makes it
practically difficult to test new hypotheses directly using these techniques, or for that matter
testing hypothesis on a large sample of participants. Further, it might be beneficial first to test
new hypothesis on a behavioral level and later take the same for testing with a scanner.
Recent developments in visual half-field research, particularly, the new and improved
version of the paradigm offered by Hunter & Brysbaert (2008) has created exciting opportunities.
The paradigm needs to be tested for its performance with a variety of cognitive functions; there
are possibly two ways in which this can be done, firstly we need to design experiments that test
the pre-established notions of lateralization about various cognitive functions; and secondly to
test whether the paradigm can demonstrate complementary patterns of lateralization for the
participants that are typically and atypically lateralized for speech.
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Electro-encephalographic (EEG) and Magneto-encephalographic (MEG)
Methods
Electroencephalography and Magneto-encephalography are two closely related methods
that gauge brain functions and cerebral activity by reading variations in the electric fields and
magnetic fields over the cortex respectively.
The EEG instrumentation consists of a set of scalp electrodes coupled to a high
impedance amplifier and a digital data acquisition system. The system is capable of recording
data from 2 to 512 EEG electrodes placed over the scalp. First developed by Hans Berger in the
1920s (Berger, 1929) this method can record brain activity with high temporal resolution.
MEG (magnetoencephalography) is a comparatively younger method developed by
physicist David Cohen (Cohen, 1972). The MEG is a more sophisticate technique, requiring the
set up of expensive superconducting quantum interference devices (SQUIDs)- based
magnetometers housed in a magnetically shielded room; recording from upto 512 MEG sensors
with high temporal resolution.
Both techniques have a high temporal resolution and are capable of recording very fast
brain events of a duration of 1 ms or even less. Such a capacity allows the investigation of
transient neural activity indexed in event related potentials (ERPs) or magnetic fields (ERFs)
which are brain responses related to the presentation of a stimulus, detectable with the averaging
technique employed in data analysis (Celesia & Brigell, 1992).
While the EEG and MEG methods are both based on neuro-physiological and
electromagnetic processes, there are differences between them too. MEG as a method is much
costlier to use than EEG; though MEG signals are free from possible artifacts that might affect
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EEG signals. Also MEG signals are less distorted by the resistance of the skull and the scalp
tissue. Further, as the decay of magnetic fields over distance over the scalp is more pronounced
than electric fields, MEG signals are more sensitive to superficial brain activity. These set of
differences together make it easier to interpret data form MEG signals. However, there are some
advantages of using EEG over MEG too, as for instance with the EEG electrodes being placed
directly over the subjects scalp head movements are easily taken into account than in MEG.
The use of EEG and MEG also has the advantage of high temporal resolution over
hemodynamic neuroimaging methods like fMRI (functional magnetic reasonance imaging) and
PET (positron imaging tomography), both of which have a low temporal resolution.
With these special characteristics, the EEG and MEG methods can be ideal to gauge the
temporal asymmetry between the two hemispheres. For example: given its adeptness at handling
verbal material, the left hemisphere may respond with shorter latencies than the right hemisphere
in a task that uses verbal stimuli. Employing techniques as the visual half-field method (Hunter
& Brysbaert, 2008) or the dichotic listening paradigm (DL, Tervaniemi & Hugdahl, 2003) it is
possible to present stimuli in a lateralized fashion and observe differences in speed/accuracy of
the two hemispheres in terms of responses; the differences assumed to reflect the relative skill of
a particular hemisphere with respect to the stimuli being processed. While there are many ways
in which hemispheric asymmetries in function can manifest, in terms of differences in activations
or response latencies, laterality indices may serve well to illustrate the brain’s hemispheric
specialization for a given task pertaining to specific stimuli. In EEG/MEG studies, laterality
indices can be computed on ERP/ERF amplitudes and from frequency data (Brancucci, 2010).
EEG/MEG measures of hemispheric asymmetries have been found to be considerably stable over
time, within one subject (Brancucci, 2010).
Chapter 1| Introduction
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The EEG/MEG methods have been successful at uncovering various behavioral
asymmetries in humans, especially in the auditory domain. EEG/MEG has been used to
investigate lateralization of language related functions, mainly due to their high temporal
resolutions which affords a distinct advantage over the hemodynamic methods. Several findings
can be cited to illustrate the usefulness of these methods. The magnetic mismatch negativity
(mMMN; a cortical response to infrequent stimuli in a series) to language stimuli has been
shown lateralized to the left hemisphere in right-handed subjects for vowels (Naatanen et al.,
1997), fricative sounds (Lipski & Mathiak, 2007), syllables (Shtyrov et al., 2000), and words
(Pulvermuller, 2001). Similarly, a MEG study showed that while in the right hemisphere, the
mMMN elicited by an infrequent chord change was stronger than an mMMN elicited by a
phoneme change; the mMMN strength for a chord versus phoneme change did not differ
significantly; indicating at the specialization and sensitivity of the right hemisphere for musical
sounds (Tervaniemi, et al., 1999). Several specifically language related EEG/MEG components
have also been identified and reported over the last decade or so, having different temporal and
spatial characteristics. The N400 component has been found to index sematic processes, and is
elicited in terms of bilateral centroparietal negativity after the onset of a semantically anomalous
word in a particular context (Kutas & Hillyard, 1980). It is thought to be generated at the anterior
part of left inferior frontal lobe (Nobre & McCarthy, 1995). Syntactic processes on the other
hand, have been found to be indexed in either a left anterior negativity between 150-200ms for
phase structure violations (Friedrici et al., 1993) or between 300-500ms for morphosyntactic
violations between lexical elements (Coulson et al., 1998) or finally in a late bilateral
centroparietal positivity around 600ms, the P-600 (Osterhout & Holcomb, 1992). EEG/MEG as
methods, have also been compared with the traditional WADA test (Wada & Rasmussen, 1960)
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and fMRI (Kamada et al., 2007; Steinbeis & Koelsch, 2008) to demonstrate that they can be
reliably used as tools for the determination of language dominance. In the same vein, Ressel et
al. (2006) developed a tool to investigate hemispheric dominance and temporal aspects of
cortical linguistic processing based on a verb generation task and a vowel identification task
respectively. While the verb generation task elicited left lateralization in frontal brain regions;
the vowel identification task yielded significant left lateralization in posterior language regions.
Apart from their obvious utility in studies dealing with language and related functions,
EEG/MEG have been useful in various frontal lobe asymmetries which index affective and
cognitive well being of individuals. For instance, Fox & Davidson (1986) found that babies
exhibited greater left frontal EEG when confronted with sucrose (pleasant taste) compared to
water (neutral taste) or citric acid (unpleasant taste). Similarly, Kline et al., (2000) reported that
elderly women showed greater relative left frontal activity in response to a pleasant odor as
compared to a neutral or unpleasant odor. On a different note, frontal activity asymmetries
indexed via electromagnetic activity have also been linked to depression and related affective
disorders. For instance, individuals with a history of depression have been found to demonstrate
a pattern of asymmetrical resting EEG activity over the frontal cortex that is different from never
depressed persons (Allen et al., 2004).
Finally, EEG/MEG methods are being used in combination with other techniques like the
TMS (transcranial magnetic simulation; Thut & Minussi, 2009), fMRI (Kircher et al., 2004) and
the ultra low field (ULF) MRI signal methods to devise more advanced methods of investigating
brain functioning with increasing precision as far as both temporal and spatial resolutions are
concerned.
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While the EEG/MEG methodologies have been hailed for their good temporal resolution,
hemodynamic imaging methods have been useful in determining the areas in the brain involved
in specific cognitive functions. Emergence of hemodynamic brain imaging techniques like
positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) have
given a whole new impetus to uncovering different functional networks in the brain and
hemispheric specialization (Frackowiak, Friston, Frith, Dolan, & Mazziotta, 1997). In the next
section, I will review important evidence for hemispheric specialization discovered using
hemodynamic imaging methods.
Hemodynamic Neuroimaging Methods
Functional brain imaging techniques as PET & fMRI have been extensively used in the
study of functional brain asymmetries for over a few decades (Toga & Thompson, 2003). With
different tracer compounds PET technique can map the rates of regional blood flow, and even
oxygen and water to different brain areas. Similarly, the fMRI technique can monitor blood flow
in real time during cognitive tasks. The blood flow varies as a function of brain activity and is
useful for identifying cortical areas involved in tasks for e.g. reading, speaking or visual search
etc. Later, statistical mapping techniques are used to compare activation in different brain areas
(Friston, 2003) within and between the two hemispheres.
Functional brain imaging studies have not only been useful in uncovering functional
brain asymmetries, they have also been useful in establishing structural asymmetries of the brain
(Hugdahl, 2011). For instance, in a voxel based morphometric analysis of the interaction for
handedness, sex and structural asymmetry, Good et al. (2001) found significant asymmetry of
cerebral grey and white matter in the temporal, occipital and frontal lobes including Heschl’s
gyrus and planum temporale regions; males demonstrated significantly more leftward asymmetry
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in Heschl’s gyrus and planum temporale compared to females. Similarly, Pujol et al. (2012)
found significant white matter asymmetry in language-related regions of the brain, in their
volumetric magnetic resonance imaging study of 100 healthy right-handed participants. At the
same time they found a rightward asymmetry for a temporo-parieto-occipital region. Also,
Greve, Van der Haegen, Cai, Stufflebeam, Sabuncu, Fischl, & Brysbaert (2013) used the surface
based analyses technique of fMRI data and demonstrated differences in cortical surface areas in
the superior temporal gyrus (STG) and fusiform gyrus between 34 left hemisphere language
dominant and 21 right hemisphere language dominant individuals.
Further, according to Hugdahl (2000) the introduction of hemodynamic brain imaging
methods, such as PET and fMRI have brought a new impetus to the research on the
specialization of the two cerebral hemispheres. For instance, Pujol, Deues, Losilla & Capdevila
(1999) demonstrated in a sample of 50 right and 50 left handed participants, that while 96% of
the right handed participants showed left hemispheric lateralization of language only 76% of the
left handed participants showed left hemispheric lateralization for language. Similar findings
were reported by Knecht et al. (2000) for healthy subjects, by Holland et al. (2001) and
Szaflarski et al. (2012) for children, with indications that this left hemispheric specialization
increases with age. fMRI has been useful in studying asymmetry for other cognitive functions as
well. With respect to emotion, for instance, Canli, Desmond, Zhao, Glover & Gabrieli (1998)
demonstrated left hemispheric lateralization for positively valenced pictures, and right
hemispheric lateralization for negative pictures. Wildgruber et al. (2004) demonstrated
predominantly right hemisphere activation for comprehending affective prosody. Further,
Virginia et al. (2000) used fMRI in combination with data from lesion studies and compared
Chapter 1| Introduction
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hemispheric preference for visuospatial tasks; they found a major role for the parietal areas of the
right hemisphere in visuo-spatial tasks.
Hence, there is plenty of evidence for the multifaceted use of direct neuroimaging in
investigating brain function in general and hemispheric specialization in particular. However,
running a neuroimaging study is not all that easy and hassle free. Right from setting up a
specialized lab with sophisticated instrumentation to the task of handling the complex data; the
technology of neuroimaging requires huge investment, and therefore, is still limited in its
availability to the wider research community. It is indeed expensive to collect data for several
kinds of studies, which is perhaps reflected in the small numbers of participants in most
neuroimaging studies. For a fast growing field of research like that of hemispheric specialization,
with more and more new hypotheses being generated this might present a handicap. Precisely for
this reason it is important to keep the traditional behavioral methods alive and running. It might
indeed be economical to design robust experiments with the behavioral counterparts like the
visual half-field method and the dichotic listening paradigm, before proceeding to test the
participants with methods such as PET, fMRI etc. Nevertheless, the neuroimaging methods
provide us with direct spatial localization of the cortical areas involved in different cognitive
functions and therefore are very important and indispensable for laterality research.
In the last section, I briefly reviewed some of the methods that have been used by
researchers to investigate into the functional asymmetries of the brain. Using these different
methods over the past many decades, researchers have documented evidences for hemispheric
specialization for various cognitive functions. In the next sections, I will review some of the
evidence that has been drawn from clinical studies of brain damaged patients, i.e. patients with
lesions in parts of their brain, split brain patients i.e. patients whose corpus callosum (bunch of
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neural fibers connecting the two hemispheres) has been severed, and also from neurologically
intact and healthy individuals.
Evidence of hemispheric specialization: from Clinical Studies
Clinical studies of patients suffering from brain lesions are quite informative for
researchers studying questions about the relationship between mental functions & neural
substrates. Not only the fact that lesions in the brain cause disturbance of normal cognitive
functioning, illustrating the relationship between brain & behavior, lesions in the brain have also
been the most dramatic demonstrations of cerebral asymmetry, in that lesions in the left
hemisphere regions of the brain lead to a loss of verbal functions while lesions to the right
hemisphere lead to the loss of non-verbal functions like visuo-spatial processing, emotion
processing etc. For instance: Bryden, Hecaen & DeAgostini (1983) reviewed 130 right-handed
patients with cerebral lesions and found that while 51% (36/70) of the patients with left
hemisphere lesions had aphasia in comparison to only 8% (5/60) with right hemisphere lesions;
52% (31/60) patients with right hemisphere lesions had problems with spatial cognition (e.g.
spatial agnosia, spatial dysgraphia, loss of topographical memory) in comparison to only 23%
(16/70) with left hemisphere lesions.
Different disorders resulting from brain lesions have indicated the importance of the
lesioned brain areas with regards to the affected mental function. Some of the examples are:
Broca’s Aphasia: Patients suffering from lesions to the posterior portion of the third, or
inferior, frontal gyrus anterior to the primary motor area in the left hemisphere of the brain;
typically produce telegraphic or agrammatic speech, omitting articles function words, such as
articles or prepositions.
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Wernicke’s Aphasia: Lesions to the posterior portion of the superior temporal gyrus, i.e.
the first temporal gyrus on the parietal-temporal junction of the left hemisphere lead to a disorder
commonly referred to as Wernicke’s aphasia. Patients typically produce fluent, effortless
utterances though consisting of meaningless jargon, “syntactically and prosodically well formed,
but irrelevant and empty of content”.
Prosopagnosia: This is a disorder of face recognition wherein a person fails to recognize
faces. According to Benton (1980) this deficiency can exist for recognizing familiar faces,
caused by mostly right hemisphere lesions; and for discriminating between unfamiliar faces,
which could be due to partly bilateral but majorly right hemisphere lesions. Lesions leading to
prosopagnosia may involve the parieto-occipital regions bilaterally, though unilateral damage to
the posterior portions of the right hemisphere is also sufficient to disrupt facial recognition
capacities.
Apart from clinical studies of manifested disorders, studies making use of methods like
WADA & ECT (electro-convulsive therapy) also provided researchers with valuable insights.
The Wada test developed by Wada (1949) involved inducing hemispheric inactivity by injecting
barbiturate sodium amytal in the ipsi-lateral carotid arteries. While the target cerebral
hemisphere is rendered inactive, the researchers can test for the more or less severely affected
cognitive functions and evaluate the relative involvement of the two hemispheres. ECT
originally used for treating patients with severe depression also provided means for the
determination of language dominance, as unilateral ECT treatments caused temporary dysphasia
in the patients.
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However, Bradshaw & Nettleton (1983) have pointed out that although clinical studies
have provided high volumes of information about brain functioning, the findings are beset by
several problems of interpretation. While on one hand the clinicians have little control over the
extent & influence of the lesions in their patients; it is a harder task to locate the specific cause of
specific cognitive symptoms. Moreover, individual differences between patient’s prior
experiences, such as age, education, motivation etc. make it difficult to build theories which can
be easily generalized to the rest of the population.
In the next section, I will present converging evidence obtained from the study of split-brain
patients.
Evidence of Hemispheric Specialization: from Split-brain patients
There have been various speculations about how the two cerebral hemispheres function.
Interestingly, the brain has even been visualized as a “double organ” (Holland, 1852). Certain
theories proposed that each cerebral hemisphere could be assumed to be a perfect organic whole
capable of functioning alone as an organ of thought, or that the two cerebral hemispheres, if left
alone might develop differently & independently (Zangwill, 1976).
While it was initially thought impossible to examine the functioning of each cerebral
hemisphere in isolation, commissurotomy operations performed with patients having epileptic
seizures, opened the isolated hemispheric functioning to empirical investigation. The corpus
callosum and anterior commissures connect the two cerebral hemispheres and co-ordinate the
functioning of the two hemispheres. In some patients with epilepsy these connecting fibres were
surgically severed to control the spread of epileptic seizures. Such an arrangement makes it
possible to examine the functioning of the two hemispheres in isolation. As the left & right
Chapter 1| Introduction
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hemispheres are disconnected and cannot communicate with each other, researchers used a
variety of ingenious methods to test their functioning, with regards to specific cognitive
functions, termed as positive competence of each hemisphere (Zaidel, 1983).
R.W. Sperry received a Nobel Prize in 1981, for his pioneering work with the
hemispherectomy patients of P.J. Vogel & J.E. Bogen. In his early work during the 1960s,
Sperry demonstrated the basic effect of splitting the two hemispheres; where the left hemisphere
was shown to dominate verbal functions. Later, from around 1968 to 1972 Sperry demonstrated
the complementary abilities of the right hemisphere in terms of nonverbal, visuospatial tasks.
Finally, Sperry also contributed to the development of new testing procedures, for instance,
chimeric stimulation and Zaidel’s scleral contact lens techniques (Bradshaw & Nettleton, 1983).
In order to test patients with commissurotomy operations for cognitive functions, it is
necessary to present information to only the targeted hemisphere, and elicit the relevant response
from only that hemisphere (see Efron, 1990) for a detailed discussion.
The human nervous system is arranged in such a way that sensory information from each
half of the body, projects directly only to the contralateral hemisphere and then via the corpus
callosum to the ipsilateral hemisphere. More specifically, tactile information presented to the
right limbs is first projected to and processed by the left hemisphere. Similarly, visual
information from the left or the right hemifields is also processed by the contralateral cerebral
hemisphere. Using this anatomical arrangement of the nervous system, testing techniques present
information to only one of the hemispheres and evaluate its adeptness at processing different
stimuli. The resulting findings have elucidated patterns of hemispheric superiority in different
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functions, establishing the roles of the left & right hemispheres in verbal & nonverbal (visuo-
spatial) information processing.
Patients who have undergone commissurutomy can verbally report words or pictures
flashed to the RVF or objects touched by the right hand; while they can’t verbally report these
stimuli if they are flashed to the LVF or touched by the left hand. The right hemisphere takes to
reporting or identifying stimuli by pointing or producing a selection response involving the left
hand. Further, while the right hand stays better in writing, the left hand may demonstrate better
capabilities in drawing, copying, block construction and other tasks involving processing spatial
relations.
While it may be useful to study the positive competences of each hemisphere in isolation,
there are some limitations to the data provided by these patients (e.g. Whitaker & Ojemann,
1977). Most of these patients have had long periods of abnormal neural functioning & epileptic
seizures; and this may have influenced the functioning of the hemispheres in unverifiable ways,
even though Hellige (1993) remarks that this might be a strong point of hemispherectomy studies
as uniform findings in spite of individual differences among patients make it more impressive.
For reasons pointed out at the end of each of the two earlier sections, research into
hemispherical asymmetries of the normal, neurologically intact human brain becomes
indispensable. Indeed, research with normal and healthy individuals’ forms a large chunk of the
studies that have looked into the lateralization of cognitive functions. In the next section, I
review evidences from normal individuals.
Chapter 1| Introduction
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Evidence of Hemispheric Specialization: from Neurologically intact
individuals
While several methodological considerations come in the way of interpreting &
integrating data from the clinical & hemispherectomy studies into the mainstream theories, the
neurologically intact brain has its own set of problems for researchers. In normal subjects,
although one can be sure of morbidity and surgical trauma being absent, the interaction between
the hemispheres is not entirely controlled. The commissures between the two hemispheres are
functioning normally and may be operating in both facilitatory & inhibitory ways to mediate the
transfer of sensory, perceptual, or mnemonic information between the two hemispheres
(Bradshaw and Nettleton, 1983).
Therefore, even though researchers may adopt similar ways for stimuli presentation and
testing participants, e.g. lateralized (unilateral/bilateral) presentation of visual or auditory
information through tachistoscopic or dichotic procedures, dependent measures like reaction
time differences or ear advantages may vary because of a wide variety of possible confounds.
I will now briefly mention a few examples of such differences observed in visual and
auditory modalities; where differences between visual fields or ears have indexed superiority of
either hemisphere in information processing.
RVF superiority has been reported for laterally presented single-letter stimuli, with
accuracy of recall being the dependent variable (Bryden, 1965, 1966; Bryden & Rainey, 1963);
and also for reaction time measure in letters of various languages e.g. for English letters (Geffen,
Bradhsaw & Wallace, 1971) or for Hebrew letters (Carmon, Nachshon, Isseroff, & Kleiner,
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 34
1972). A RVF advantage has also been found in terms of reaction time and recall accuracy for
unilaterally and even bilaterally presented words (Bradshaw, Nettleton & Taylor, 1981).
Conversely, LVF superiority has been documented for a variety of nonverbal tests such
as: lightness discrimination (Davidoff, 1975), color discrimination (Davidoff, 1976; Hannay,
1979; Pennal, 1977), dot detection (Davidoff, 1977; Umilta, Salmaso, Bagnara, & Simion, 1979),
and dot localization (Bryden, 1976). Further, LVF advantage for accuracy has also been
documented with photographed faces (Hillard, 1973) and even cartoon line drawing (Ley &
Bryden, 1979); along with reaction time advantages for photographs (Rhodes & Woodling,
1989) and schematic drawings (Patterson & Bradshaw, 1975).
Auditory studies testing for lateralization have been carried out using the dichotic
listening procedure; where right or left ear advantages indicate the dominance for left or right
hemisphere respectively. Typically, a standard dichotic listening procedure involves presenting
participants with two different auditory stimuli (often speech syllables), to the different ears
using headphones. Efficiency of processing these stimuli is measured and the difference between
the two ears is termed as an ‘ear advantage’. A right – ear advantage (REA) with dichotically
presented digits was reported by Kimura (1961). Further, a REA was also reported with words
(Dirks, 1964), nonsense sounds (Curry, 1967), and speech played backwards (Kimura & Folb,
1968), and with consonant-vowel syllables (Shankweiler & Studdert-Kennedy, 1967).
Left-ear advantages (LEAs) were reported for sound stimuli preferentially processed by
the right hemisphere, e.g. melodies (Kimura, 1964; Spree, Spellacy, and Reid, 1970; Goodglass
& Calderon, 1977), musical chords (Gordon, 1970), synthetic musical tones (Cutting & Rosner,
Chapter 1| Introduction
P.| 35
1974), piano tones (Sidtis & Bryden, 1978), and environmental sounds e.g. dish-washing,
phones ringing, dogs barking, clocks ticking etc. (Knox & Kimura, 1970).
Up till now, I have reviewed the growth of the discipline of lateralization research from
being a mythology to a scientific endeavor. I have demonstrated that through the use of a variety
of methods of investigation, researchers have documented many evidences for hemispheric
specialization for cognitive functions. However, this review was largely limited to the research in
20th century.
In the next section, I will review some recent findings related to structural and functional
symmetries between the two cerebral hemispheres.
Structural and Functional Indices of Hemispheric Asymmetry: Recent
Findings
Years of laterality research using many different methods, have furnished evidence of
functional specialization between the two hemispheres of the brain. However, finding a common
underlying principle to explain the vast variety of behavioral asymmetries observed in humans
has been a significant challenge to theorists and researchers alike (Hugdahl, 2000).
Consequently, numerous efforts have been put in to identify a basic principle which may
govern the lateralized organization of cognitive functions in the brain. A number of dichotomies
have been offered as possible factors; for instance, the processing of global vs. local visual
patterns, whereas the left hemisphere is deemed specialized for processing local elements, the
right hemisphere is proposed to be adept at processing global elements (Robertson, 1986).
Another principle proposed is the ability to make categorical vs. coordinate judgments, where
the left hemisphere is specialized for categorical judgments and right hemisphere for coordinate
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 36
judgments (Kosslyn, 1987). A third principle that has been offered is the processing of low
spatial frequency vs. high spatial frequency, where the right hemisphere has been found adept at
processing low spatial processing and the left hemisphere being involved in better processing of
higher spatial processing (Sergent, 1983; Ivry & Robertson, 1998).
Unfortunately, none of these principles have been able to account for the majority of
findings and produce consistent empirical evidence over the years. Accordingly, Hellige (1993)
states that, “the quest for a fundamental dimension of hemispheric asymmetry has been
unsuccessful” (p.58).
However, Hugdahl (2000) puts forward the language-visuospatial judgment as a basic
dichotomy that governs the lateralization of cognitive functions in the brain. Hugdahl (2000)
proposes that while the left-right distinction is an important anatomical principle of the brain’s
organization, it must be related to a fundamental principle of functional organization i.e.
language and visuospatial judgment, two capacities which have played an important role during
the course of human evolution. Further, he proposes that the lateralized functional organization
of the brain may be a consequence of the evolutionary pressure on the hemispheres towards
specialization for these functions. More specifically, it has been proposed that language and
related functions maybe lateralized to left hemisphere, while functions involving visuospatial
processing and others maybe lateralized to the right hemisphere; due to crowding (Lansdell,
1969, Teuber, 1974). Recent research with atypically lateralized individuals seems to support
these preliminary hypotheses, where it is reported that when language faculty is lateralized to the
right hemisphere, other functions get reversed to the left hemisphere (see Cai et al., 2013, Verma,
van der Haegen & Brysbaert, 2013).
Chapter 1| Introduction
P.| 37
Indeed, no processes other than verbal & visuospatial functions have produced consistent
empirical differences between the two hemispheres since Sperry’s first findings (Sperry, 1974).
With this foreground to the contemporary opinion about lateralization, I will now review
some recent research into structural and functional asymmetries of the brain that lays the
foundation for the current thesis.
Structural Asymmetry between the two Hemispheres
Marie-Francois Xavier Bichat, in his “law of physiological symmetry” proposed that two
structures i.e. the left and the right hemispheres, that look exactly alike should function alike as
well. However, it turns out that neither the two hemispheres look exactly alike, nor that they
function in identical ways (Amunts, 2010).
A detailed review of morphological asymmetries in the brain has been given by Amunts
(2010). She points out that the structural indices of the human brain include: a) macroscopic
features as the volume, shape and size of sulci, gyri and cerebral lobes; b) microstructural
features as the number and density of nerve cells in a brain region, size, volume, surface and
cortical thickness of cytoarchitectonic areas including cellular indices (cell characteristics as:
number of spines, degree of arborization of dendrites and axons) and c) molecular aspects of
brain organization and gene expression.
Further, it is also pointed out that while the macroscopic features and molecular features
can be studied by both in vivo (imaging techniques as MRI, CT, and PET) and in vitro methods
(autopsy, immunohistochemistry etc.), the microstructural features may only be studied via in
vitro methods. While in vitro methods have proved useful in posthumous examination of brain
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 38
atrophies, in vivo methods have worked well together with behavioral tests, along with
functional imaging experiments thus being able to observe the brain in action (Amunts, 2010).
Using these methods, researchers have identified numerous instances of structural
asymmetries in the brain at these three levels. Now, I will discuss some of these observed
asymmetries in the structure of the brain and their implications for cognitive function.
The Perisylvian Region: Language and the Auditory Functions
Three main regions of the brain have been put forward as key to the linguistic and
auditory functions of the brain. They are: the primary auditory cortex, the Heschl gyrus, and the
superior temporal gyrus; all three of which lie around the sylvian fissure.
The Sylvian Fissure
The left part of the sylvian fissure has been reported to be longer and more horizontal
than the right part (Eberstaller, 1890; Cunningham, 1892; Jancke & Steinmetz, 2004); with
indication that such a difference already exists at early stages of ontogeny (Le May & Culebras,
1972).
Further, it has been reported that men with consistent right hand preference had longer
left/horizontal segments in the sylvian fissure as compared to men without this preference
(Witelson & Kigar, 1992). Moreover, Hellige et al. (1998) have associated the length of the right
hemispheric sylvian fissure with error rates for detecting briefly presented consonant-vowel-
consonant trigrams.
Hechl Gyrus and Primary Auditory Cortex
Chapter 1| Introduction
P.| 39
The Heschl gyrus with the primary auditory cortex has been reported to be larger in the
left hemisphere than in the right hemisphere, as a result of larger amounts of white matter
underlying the gyrus (Rademacher et al., 1993; Penhune et al., 1996).
The Planum Temporale and Superior Temporal Gyrus
The planum temporale region is located posterior to the Heschl gyrus within the auditory
cortex and continues to the lateral surface of the superior temporal gyrus; it is typically
associated with the Wernicke’s area. The planum temporale region has been reported to be larger
in the left hemisphere in a range of studies (Pfeifer, 1911; von Economo and Horn, 1930;
Geschwind and Lewistky, 1968; Steinmetz, 1996 and Shapleske et al., 1999).
Further, the leftward asymmetry of the planum temporale region has been linked to
measures of functional asymmetry such as handedness and auditory lateralization (Steinmetz et
al., 1995; Steinmetz, 1996). Also, increased asymmetry in the planum temporale has been
associated with better abilities to process musical information; higher asymmetry was reported in
musicians than non musicians and controls (Schlaug et al., 1999) and in people with perfect pitch
than those without perfect pitch (Keenan et al., 2001). Reduced asymmetry on the other hand has
been reported for schizophrenics (Chance et al., 2008).
Broca’s Region
Brodmann’s areas 44 and 45 comprise the key regions of the Broca’s area, and occupy the pars
opercularis and pars triangularis, respectively (Amunts, 2010). The volume of the left area 44
was reported to be larger than the area in the right hemisphere in a two post-mortem studies
(Galaburda, 1980; Amunts, 1999). Also, both areas, 44 and 45, were found asymmetrical with
respect to the laminar distribution of cell bodies (Amunts and Zilles, 2001). Further, the total
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 40
number of neurons in area 44 were found to be more in the left side, no statistically significant
difference in the number of neurons could be ascertained for area 45 (Uylings et al., 2006).
Finally, studies have reported that such interhemispheric differences in the cytoarchitecture of
these areas could be found as early as 1 year old infants, it also increased with age (Amunts et
al., 2003).
These differences in the left and right sides of area 44 and 45 have also been linked to
functional features of the brain, for instance, interhemispheric differences in the structure of area
44 is associated with the development of adult like syntactic process, whereas those in area 45
are associated with the development of semantic processing abilities.
Somatosensory and Motor Areas
Hemispheric differences in structure has also been found in several components of the
motor and sensory systems of the human brain, for e.g. caudate nucleus (Watkins et al., 2001),
the cerebellum (Snyder et al., 1995) and the sensory and motor cortices. Also, interhemispheric
asymmetry in structure has been reported for the central sulcus (Davatzikos and Bryan, 2002;
Cykowski et al., 2008) and even though the results are not unequivocal (Amunts, 2010) a
correlation between the depth of the central sulcus and age has been claimed (Cykowski et al.,
2008).
Finally, in vivo morphometry studies of right handed male professional keyboard players
have revealed less asymmetry in the central sulcus than matched controls (Amunts et al., 1997).
Chapter 1| Introduction
P.| 41
The Limbic System
Components of the limbic system mainly implicated with affective and memory functions
have also been reported to demonstrate structural asymmetry. The limbic system includes the
hippocampus, the cingulated gyrus, the amygdale and the habenula.
A number of studies have reported asymmetry in terms of volume and surface of the
hippocampus; for e.g. rightward asymmetry was found in MRI data of 61 healthy volunteers (Li
et al., 2007). Also, rightward asymmetry in hippocampal and amygdalar volume has been
reported (Niemann et al., 2000; Szabo et al., 2001). Further, hippocampal asymmetry has been
shown to decrease with age (Shi et al., 2007).
Significant leftward asymmetry in the thickness of the anterior segment and significant
leftward asymmetry in the surface area of the posterior segment of the cingulated cortex was
reported in a MRI study of 68 healthy subjects and a group of patients with schizophrenia (Wang
et al., 2007).
Brain Areas Involved in Visuospatial Processing
Hasnain et al. (2006) analyzed spatial covariance between human occipital sulci and
other visual areas through retinotopic mapping and found stronger sulcus-function covariance in
the left occipital lobe than the right occipital lobe and suggested that the degree of hemispheric
lateralization is reflected in the strength of correspondence between cortical surface anatomy and
function. Volumetric analyses in a sample of postmortem fetal brains in the Yakovlev Collection
showed that male striate-extrastriate cortices were more asymmetrical than female brains (de
Lacoste et al., 1991).
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 42
Brodmann areas 39 and 40 form the parietal cortex and also play a role in the visual
processing in te brain; however claims of rightward asymmetry in terms of volume (Caspers et
al., 2008) have not be backed by other studies (Jancke et al., 1994; Eidelberg & Galaburda,
1984).
Over all, we can say that there is enough evidence for structural asymmetry in the brain.
The degree of asymmetries in structure, has been found to be differ with respect to brain region,
handedness, gender and disease (Amunts, 2010). Also, some of these asymmetries develop
during early stages of ontogeny and interact with age. Finally, it can be concluded that
anatomical symmetry of the brain interacts with the lateralization of cognitive function (Amunts,
2010).
Functional asymmetry in Visuospatial Processing between the Hemispheres
Functional asymmetry refers to the difference in the ability of the two hemispheres at
performing different cognitive functions. As most of the cognitive functions are mediated by
sensory modalities of vision and audition, asymmetries in visual and auditory processing can
serve as windows for better understanding asymmetries in cognition.
Given that my thesis explores lateralization of cognitive functions, mainly through the
visual modality; I will limit the discussion to asymmetries in visual processing.
Hemispheric asymmetries in visual processing exist not only in humans but in other
vertebrate species and primates as well (Hellige, 1996; Rogers and Andrew, 2002; Hopkins,
2007). Given such a pattern, speculations have been made that humans inherited such an
asymmetry during the course of evolution from their ancestors (Hellige, Laeng, & Michimata,
2010).
Chapter 1| Introduction
P.| 43
The nature of hemispheric asymmetry in processing visual information, however, has
been deemed “subtle” and “complementary” across species (Rogers & Andrew, 2002; Hopkins,
2007). More specifically, while both the hemispheres can process all aspects of visual
information to a reasonable extent, they exhibit complementary specializations for e.g. right
hemisphere is deemed dominant for “diffuse or global attention, spatial analysis and no
involvement in control of response” and the left hemisphere is supposed to be dominant for
“focused attention, processing of local cues and control of response” (Rogers and Andrew, 2002;
Hopkins, 2007).
Now, I will briefly examine the various asymmetries in visual processing observed in
humans.
Categorical and Coordinate Spatial Relations
Two most important functions of the visual system is to provide us the information about
“where” and “what” i.e. location and identification of things in the surroundings (Schneider,
1967; Ingle, 2002). Mishkin, Ungerleider & Macko (1983) identify two “cortical visual systems”
i.e. a ventral visual steam that mediates identification and a dorsal stream that mediates location
of objects in the space around us. It is known that both of these streams are duplicated in each of
the two cerebral hemispheres, though it is proposed that the hemispheres are concerned with
qualitatively different aspects of the “where” and “what”.
I will begin with reviewing findings of hemispheric asymmetry in processing the “where”
or the location processing visual systems.
Kosslyn (1987, 2006) distinguishes between “coordinate” and “categorical”
spatial relations between objects that are used by the visual system to compute the location of
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 44
objects. Coordinate relations between objects occur within a”metric space” and allow the
perception and expression of distances between objects quantitavely (for e.g. two objects are x
meters apart). Categorical relations, on the other hand express qualitative spatial relations
between objects, and “categorize” space to describe objects as “above”, “below”, “alongside”,
“behind”, “between” or “inside” each other (Pinker, 2007).
Several studies have documented evidence that for the majority of population,
typically right handed, the left hemisphere is adept at processing categorical relations while the
right hemisphere is better at processing coordinate spatial relations (Hellige, 1995; Laeng,
Chabris, & Kosslyn, 2003).
Early evidence in this direction was provided by visual half field studies wher
participants were found to be faster and more accurate in judging coordinate relations when
presented in the left visual half-field and judging categorical relations when presented with such
stimuli in the right visual half-field (Hellige & Michimata, 1989). A range of simple geometrical
figures to more naturalistic figures have been used as stimuli to ask participants to produce such
judgments (Lange, Peters, & McCabe,1998; Roth & Hellige, 1998; and van der Ham, van Wezel,
Oleksiak, & Postma, 2007; Laeng & Peters,1995). However, the visual half field differences in
RTs (reaction times) have been found to be rather volatile (Hellige,& Cumberland,2001) and
small. A meta analysis by Laeng, Chabris & Kosslyn (2003) showed that the left hemisphere is
about 8 ms faster for making categorical judgments and the right hemispheres is just about 14ms
faster for making coordinate judgments, respectively; though these differences were highly
significant (combined Z value = 6.93, p < 0.0001).
Chapter 1| Introduction
P.| 45
Another source of evidence comes from clinical studies. For instance, Laeng (1994)
demonstrated that left hemisphere damaged patients were worse at noticing changes in
categorical relations while they did much better at noticing coordinate relations between stimulus
objects; and right hemisphere damaged patients were much better at noticing categorical
relations but fared badly when asked to judge coordinate relations between stimulus objects.
Similar evidence was also provided in a recent clinical study (Palermo, Bureca, Matano and
Guariglia, 2008).
While there it has been a little difficult to find consistent neuroimaging evidence for these
findings (see Amunts, 2010 for a detailed discussion); some recent studies (Slotnick, Moo,
Tesoro, & Hart, 2001; Trojano, Conson, Maffei, & Grossi, 2006) have used the repetitive
transcranial magnetic stimulation (rTMS) method to support the earlies proposition of left
hemisphere role in categorical relations processing and right hemisphere role in coordinate
relations processing.
Spatial Frequency Processing
Sergent (1983) proposed that the left and the right hemispheres of the brain are more
efficient at processing information carried by channels tuned to the high and low spatial
frequencies respectively. A number of studies have demonstrated evidence that supported this
hypothesis by using spatial frequency filtered stimuli (Jonsson, & Hellige 1986; Michimata &
Hellige, 1987) and sinusoidal gratings (Kitterle, Hellige, & Christman, 1990, 1992).
Further, it has been proposed that the hemispheric differences regarding the processing of
categorical and coordinate spatial relations may be linked to the asymmetry in processing spatial
frequencies (Kosslyn et al. ,1992); and the testing of this hypothesis by Okubo & Michimata
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 46
(2002, 2004) has supported the hypothesis. It can therefore be concluded that spatial frequency
processing mediates computation of spatial relations, and hemispheric asymmetry in the former
is reflected in the latter.
We have discussed the hemispheric asymmetries in processing the “where” aspect of
visual processing; now we turn to the “what” question.
Global-Local Processing
Answering questions about “what” an object is, involves processing information about its
composition. Often, an object can be described as having global (larger, holistic) structure that
may be composed in turn by many local (smaller) structures (Navon, 1977). It has been proposed
that while the left hemisphere is better at processing information about these local constituents
the right hemisphere is better at processing information about the larger structure (Sergent, 1983;
Fink, Halligan, Marshall, Frith, Frackowiak, & Dolan. 1996, 1997; and Yamaguchi, Yamagata,
& Kobayashi, 2000).
Evidence supporting this hypothesis has been provided by clinical studies which show
that damage to the left versus the right superior temporal gyrus disrupts local versus global
processing (Ivry, & Robertson, 1998). Also, visual half-field studies have shown a typical RVF-
LH advantage for identifying local patterns and a LVF-RH advantage for identifying global
patterns (Hubner, 1998; Hubner & Studer, 2009; Hopkins, 1997). Neuroimaging studies have
also supported the hypothesis, though the evidence from these studies has been variable (Sasaki,
Hadjikhani, Fischl, Liu, Marrett, Dale & Tootell, 2000; Han, Weaver, Murray, Kang, Yund, &
Woods, 2002 and Amunts, 2010).
Chapter 1| Introduction
P.| 47
Finally, visual processing asymmetries for global-local processing have been linked to
asymmetries in processing spatial processing, i.e. global processing has been proposed to be
mediated by relatively low spatial frequencies while local processing has been proposed to be
mediated by relatively high spatial frequencies (Hellige, 1993, 1995; Amunts, 2010). In line with
these proposals, spatial filtering has been shown to influence the pattern of hemispheric
asymmetry in global-local processing accordingly (Hughes, Fendrich, & Reuter-Lorenz, 1990;
Han et al., 2002; Yoshida, Yoshino, Takahashi, & Nomura, 2007).
Object Discrimination
The hemispheric asymmetry in processing spatial relationships has also been linked to
object discrimination; wherein, a left hemisphere advantage has been proposed for between
category discrimination and a right hemisphere advantage has been proposed for within catgory
discrimination (Amunts, 2010). Several studies have provided supporting evidence for this
hypothesis (Laeng, Zarrinpar, & Kosslyn, 2003; Laeng, Carlesimo, Calta-girone, & Miceli,
2002).
Saneyoshi et al. (2006) conducted a fMRI study and demonstrated relatively greater left
hemisphere contributions to between category object discrimination and relatively greater right
hemisphere contribution to within category object recognition, respectively. Further, Saneyoshi
& Michimata (2009) have also conducted a behavioral visual half-field study, showing a RVF-
LH advantage in RTs (reaction times) for a categorical discrimination task and a LVF-RH
advantage for a coordinate task, using novel objects called ‘geons’ as stimuli.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 48
Face Recognition
As with object discrimination, another basic visual asymmetry in processing global
versus local features mediates a processing asymmetry that has been documented for face
recognition. Cooper & Wojan (2000) pointed out that face identification involves processing
configural, metric or coordinate relations between face-parts (eyes, nose, lips etc.) whereas just
differentiating faces from other classes of stimuli involves categorical processing. Consequently,
it has been proposed that the left and right hemispheres play qualitatively different roles in face
processing (Amunts, 2010). Rossion, Dricot, Devolder, Bodart, Crommelinck, de Gelder and
Zoontjes (2000) used positron emission tomography (PET) in a whole and part based face-
matching tasks and showed greater right fusiform face area during the whole condition and
greater activation in the left FFA during the part condition.
All in all, we have seen that several asymmetries in the processing of visual information
have been reported. It can also be said that asymmetries in processing some fundamental
channels of information (for e.g. spatial frequency) may mediate hemispheric asymmetries in
processing categorical-coordinate spatial relations, global-local processing etc.
I have, now reviewed the methods of investigation, the evidences & also the markers that
have established the functional asymmetries between the two hemispheres of the brain. I will
now introduce my own studies in the next section.
Motivations for the current thesis
Research into the lateralization of cognitive functions has travelled a long way from
being a source of mythical stigmatization of the left handed individuals to being a major topic of
investigation in the empirical fields of neuroscience, neuropsychology, cognitive psychology and
Chapter 1| Introduction
P.| 49
many other related areas. I have surveyed the many methods that have been used to investigate
the laterality of cognitive functions and the functioning of the two cerebral hemispheres. I have
also summarized the evidence for the lateralization of a variety of cognitive functions from
multiple sources.
While there has been plenty of research into the functional specialization of both the
hemispheres, the major body of work leans heavily towards the language-related and other left
hemispheric functions. There are several reasons for this, one of them probably being, as
Hugdahl (2000) remarked, that the language-related functions have consistently given stable
findings over the years. Research with nonverbal stimuli and paradigms has not always produced
consistent results (Whitehouse, Badcock, Goen & Bishop, 2009). Another observation is that for
the development of laterality research, more and more new research needs to be done with the
behavioral methods as an initial point and later supplemented with the sophisticated
neuroimaging techniques available today. Indeed, a lot of work with the Dichotic Listening task
is being done in the lab of Kenneth Hugdahl, who has used the DL paradigm in a variety of areas
in cognitive psychology, clinical psychology, neuroscience etc. In our lab major work has been
done with the visual half-field task as far as lateralization of language is concerned, in both
typically and atypically lateralized populations (Van der Haegen et al., 2011, 2012).
I undertook the task of further validating and testing the version of the visual half-field
task proposed by Hunter & Brysbaert (2008), with respect to cognitive functions other than
language. The idea was to test the task with at least one other left hemispheric and one or more
right hemispheric cognitive function. If possible I would also validate the same task with left-
handed atypically lateralized individuals. Eventually, I was successful in testing the task with
tool recognition (chapters 2 & 3) as a left hemisphere function. I was also able to test the VHF
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 50
task with 3 different right hemisphere functions; symmetry detection (chapter 4), figure
comparison & facial emotion perception (chapter 5). I was able to test the symmetry detection
task with a group of atypically lateralized left handed individuals, provided by my colleague Lise
Van der Haegen (Van der Haegen et al., 2011).
Outline of the present thesis
In Chapter 2, I present work with the tool-recognition task, which was pre-established as a left
hemisphere lateralized function. The VHF task used could successfully replicate the RVF/left
hemisphere advantage for tool recognition.
In Chapter 3, I further standardized the stimuli used in the tool recognition and object
recognition tasks and replicated & even enhanced the RVF/left hemisphere advantage for tool-
recognition through our VHF paradigm.
In Chapter 4, I took a right hemisphere lateralized cognitive function of symmetry detection. I
additionally checked whether symmetry detection is lateralized in a complementary fashion in a
sample of atypically lateralized individuals. I found the expected LVF/right hemisphere
advantage for symmetry detection in the typically lateralized right handed and left handed
individuals. I also found an indication for the reversed RVF/left hemisphere lateralization for
symmetry detection in the group of left handed atypically lateralized individuals.
In Chapter 5, I present experiments with figure comparison and facial emotion perception.
While a left visual half-field/right hemisphere lateralization for figure comparison could be
ascertained, the experiments with facial emotion perception served to illuminate a more complex
picture than a straightforward right hemisphere lateralization for all emotions. Additionally, in
Chapter 1| Introduction
P.| 51
the data of the three experiments I investigated for the possible validation of the polarity coding
hypotheses. I found that participants were overall faster for index finger-yes responses.
Finally, in Chapter 6, I will look back at all the studies put together and try to arrive at a
conclusion about the efficacy of the particular VHF paradigm as a viable task to study
lateralization of cognitive functions in general, and right hemisphere functions in particular.
Further, I will also speculate at future research using the VHF task.
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References
Allen , J. J. B. , McKnight , K. M. , Moreno , F. A. , Demaree , H. A. , & Delgado , P. L. (2009 ).
Alteration of frontal EEG asymmetry during tryptophan depletion predicts future
depression. Journal of Affective Disorder, 115, 189 – 195.
Amunts , K. , & Zilles , K. (2001). Advances in cytoarchitectonic mapping of the human cerebral
cortex. In T. P. Naidich, T. A. Yousry, & V. P. Mathews (Eds.), Neuroimaging Clinics of
North America: Anatomic basis of functional MR imaging (pp. 151 – 169 ). Philadelphia:
Harcourt.
Amunts , K. , Schlaug , G. , J a ncke , L. , Steinmetz , H. , Schleicher , A. , & Zilles , K. (1997).
Motor cortex and hand motor skills: Structural compliance in the human brain. Human
Brain Mapping, 5, 206 – 215.
Amunts , K. , Schleicher , A. , B u rgel , U. , Mohlberg , H. , Uylings , H. B. M. , & Zilles , K.
(1999). Broca’s region revisited: Cytoarchitecture and intersubject variability. Journal of
Comparative Neurology, 412, 319 – 341.
Amunts , K. , Schleicher , A. , Ditterich , A. , & Zilles , K. (2003). Broca’s region:
Cytoarchitectonic asymmetry and developmental changes. Journal of Comparative
Neurology, 465, 72 – 89.
Amunts, K. (2010). Structural Indices of Asymmetry. The Two Halves of the Brain, 145.
Belhomme, J.-E. (1848). De la localisation de la parole ou plutdt de la me"moire des mots les
lobes ant6rieurs du cerveau. Summarized by J. Cloquet and J. Ferrus. Bulletin de
UAcadfmie Royale de Midecine, 13, 527-536.
Benton, A. L. (1980). The neuropsychology of facial recognition. American Psychologist, 35 (2),
176.
Berger H. (1929). Uber das elektrenkephalogramm des menschen. Archiv fuÈr Psychiatrie und
Nervenkrankheiten, 87, 527-570.
Chapter 1| Introduction
P.| 53
Best, E. (1901). Maori magic. Transactions and Proceedings of the New Zealand Institute, 34,
69-98.
Best, E. (1905) Maori eschatology. Transactions and Proceedingsof the New Zealand Institute,
38, 148-239.
Bichat, X. (1805/1809). Physiological Researches Upon Life and Death. First English translation
1809, by Tobias Watkins, of the 2nd Paris edition (1805) of Recherches Physiologique
sur la Vie et la Mort. Philadelphia, PA: Smith & Maxwell.
Binder, J. R., Swanson, S. J., Hammeke, T. A., Morris, G. L., Mueller, W. M., Fischer, M., ... &
Haughton, V. M. (1996). Determination of language dominance using functional MRI A
comparison with the Wada test. Neurology, 46 (4), 978-984.
Bookheimer, S., Schrader, L. M., Rausch, R., Sankar, R., & Engel, J. (2005). Reduced
anesthetization during the intracarotid amobarbital (Wada) test in patients taking carbonic
anhydrase–inhibiting medications. Epilepsia, 46(2), 236-243.
Boucher, R., & Bryden, M. P. (1997). Laterality effects in the processing of melody and
timbre. Neuropsychologia, 35(11), 1467-1473.
Bouillaud, J. B. (1825). Recherches cliniques propres a demonstrer que la perte de la parole
correspond a la lesion de lobules anterieurs du cerveau, et confirmer l’opinion de M Gall
sur le siege de l'organe du langage articuie. Archives Ginirales de Midecine, 8, 25-45.
Bouillaud, J.B. (1839-1840). Exposition du nouveaux faits a l'appui de l'opinion qui localise dans
les lobules antdrieurs du cerveau le principe legislateur de la parole; examen preliminaire
des objections dont cette opinion a ete sujet. Bulletin de I'Acadimie Royale de Midecine,
4, 282-328, 333-349, 353-369.
Bradshaw, J. L., & Nettleton, N. C. (1983). Human cerebral asymmetry (pp. 219-222).
Englewood Cliffs, NJ: Prentice-Hall.
Bradshaw, J. L., Nettleton, N. C., & Taylor, M. J. (1981). The use of laterally presented words in
research into cerebral asymmetry: Is directional scanning likely to be a source of
artifact?. Brain and Language, 14(1), 1-14.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 54
Brancucci, A. (2010). Electroencephalographic and magnetoencephalographic Indices of
hemispheric asymmetry. The two Halves of the Brain: information processing in the
cerebral hemispheres. The MIT Press, Cambridge, 211-251.
Brancucci, A., & San Martini, P. (1999). Laterality in the perception of temporal cues of musical
timbre. Neuropsychologia, 37(13), 1445-1451.
Brancucci, A., & San Martini, P. (2003). Hemispheric asymmetries in the perception of rapid
(timbral) and slow (nontimbral) amplitude fluctuations of complex
tones. Neuropsychology, 17(3), 451.
Brancucci, A., Babiloni, C., Babiloni, F., Galderisi, S., Mucci, A., Tecchio, F., ... & Rossini, P.
M. (2004). Inhibition of auditory cortical responses to ipsilateral stimuli during dichotic
listening: evidence from magnetoencephalography.European Journal of
Neuroscience, 19(8), 2329-2336.
Brancucci, A., Babiloni, C., Rossini, P. M., & Romani, G. L. (2005). Right hemisphere
specialization for intensity discrimination of musical and speech
sounds. Neuropsychologia, 43(13), 1916-1923.
Brancucci, A., Babiloni, C., Vecchio, F., Galderisi, S., Mucci, A., Tecchio, F., ... & Rossini, P.
M. (2005). Decrease of functional coupling between left and right auditory cortices
during dichotic listening: An electroencephalography study. Neuroscience, 136(1), 323-
332.
Brancucci, A., D’Anselmo, A., Martello, F., & Tommasi, L. (2008). Left hemisphere
specialization for duration discrimination of musical and speech
sounds. Neuropsychologia, 46(7), 2013-2019.
Broadbent, D. E. (1956). Successive responses to simultaneous stimuli. The Quarterly Journal of
Experimental Psychology, 8, 145–162.
Broca, P. (1861a). Remarques sur le siege de la faculte du langage articuie, suivies d'une
observation d'aphemie (perte de la parole). Bulletins de la Sociiti Anatomique de Paris 6,
330-357.
Chapter 1| Introduction
P.| 55
Broca, P. (1861b). Nouvelle observation d'aphemie produite par une lesion de la moitie
posterieure des deuxieme et troisieme circonvolutions frontales gauches. Bulletins de la
Sociiti Anatomique de Paris, 6, 398-407.
Broca, P. (1861c). Perte de la parole, ramollissement chronique et destruction partielle du lobe
anterieur gauche du cerveau. Bulletins de la Sociiti d'Anthropologie de Paris, 2, 235—
238.
Broca, P. (1865). Sur le siege de la faculte du langage articuie. Bulletins de la Sociiti
d'Anthropologie de Paris, 6, 377-393.
Bruder, G. E. (1983). Cerebral laterality and psychopathology: a review of dichotic listening
studies. Schizophrenia bulletin, 9 (1), 134.
Bryden, M. P. (1965). Tachistoscopic recognition, handedness, and cerebral
dominance. Neuropsychologia, 3 (1), 1-8.
Bryden, M. P. (1966). Left-right differences in tachistoscopic recognition: Directional scanning
or cerebral dominance? Perceptual and Motor Skills,23 (3f), 1127-1134.
Bryden, M. P. (1976). Response bias and hemispheric differences in dot localization. Perception
& Psychophysics, 19 (1), 23-28.
Bryden, M. P. (1988). An overview of the dichotic listening procedure and its relation to cerebral
organization. In K. Hugdahl (Ed.), Handbook of dichotic listening: Theory, methods, and
reseaarch (pp. 1–44). Chichester, UK: Wiley & Sons.
Bryden, M. P., & Rainey, C. A. (1963). Left-right differences in tachistoscopic
recognition. Journal of Experimental Psychology, 66 (6), 568.
Bryden, M. P., Hecaen, H., & DeAgostini, M. (1983). Patterns of cerebral organization. Brain
and language, 20 (2), 249-262.
Cai, Q., Van der Haegen, L., & Brysbaert, M. (2013). Complementary hemispheric
specialization for language production and visuospatial attention. Proceedings of the
National Academy of Sciences, 110 (4), E322-E330.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 56
Canli, T., Desmond, J. E., Zhao, Z., Glover, G., & Gabrieli, J. D. (1998). Hemispheric
asymmetry for emotional stimuli detected with fMRI. Neuroreport, 9, 3233–3239.
Carmon, A., Nachshon, I., Isseroff, A., & Kleiner, M. (1972). Visual field differences in reaction
times to Hebrew letters. Psychonomic Science, 28(4), 222-224.
Caspers , S. , Eickhoff , S. B. , Geyer , S. , Scheperjans , F. , Mohlberg , H. , Zilles , K. , et al.
(2008). The human inferior parietal lobule in stereotaxic space . Brain Structure &
Function, 212, 481 – 495.
Celesia, G. G., & Brigell, M. (1992). Event-related potentials. Current Opinion in
Neurology, 5(5), 733-739.
Chance , S. A. , Casanova , M. F. , Switala , A. E. , & Crow , T. J. (2008). Auditory cortex
asymmetry altered mini column spacing and absence of ageing effects in schizophrenia.
Brain, 131, 3178 – 3192.
Cohen D. (1972) Magnetoencephalography: Detection of the brain's electrical activity with a
superconducting magnetometer. Science, 175, 664-6.
Cooper , E. E. , & Wojan , T. J. (2000). Differences in the coding of spatial relations in face
identification and basic-level object recognition . Journal of Experimental Psychology.
Learning, Memory, and Cognition , 26 , 470 – 488 .
Corballis, M. C. (1980). Laterality and Myth. American Psychologist, 35 (3), 284-295.
Coren, S., & Porac, C. (1977). Fifty centuries of right-handedness: The historical
record. Science.
Coulson, S. , King , J. W. , & Kutas , M. (1998). Expect the unexpected: Event-related brain
responses to morphosyntactic violations. Language and Cognitive Processes, 13, 21 – 58.
Coulson, S., & Williams, R. F. (2005). Hemispheric asymmetries and joke
comprehension. Neuropsychologia, 43 (1), 128-141.
Chapter 1| Introduction
P.| 57
Cunningham , D. J. (1892). Contribution to the surface anatomy of the cerebral hemispheres:
Cunningham memoirs. Dublin, Ireland: Royal Irish Academy.
Curry, F. K. (1967). A comparison of left-handed and right-handed subjects on verbal and non-
verbal dichotic listening tasks. Cortex, 3 (3), 343-352.
Cutting, J. E., & Rosner, B. S. (1974). Categories and boundaries in speech and
music*. Perception & Psychophysics, 16 (3), 564-570.
Cykowski , M. D. , Coulon , O. , Kochunov , P. V. , Amunts , K. , Lancaster , J. L. , Laird , A. R.
, et al. (2008). The central sulcus: An observer-independent characterization of sulcal
landmarks and depth asymmetry. Cerebral Cortex (New York, N.Y.), 18, 1999 – 2009.
Dart, R. A. (1949). The predatory implemental technique of Australopithecus. American Journal
oj Physical Anthropology, 7, 1-38.
Davatzikos , C. , & Bryan , R. N. (2002). Morphometric analysis of cortical sulci using
parametric ribbons: A study of the central sulcus. Journal of Computer Assisted
Tomography, 26, 298 – 307.
Davidoff, J. (1976). Hemispheric sensitivity differences in the perception of colour. The
Quarterly journal of experimental psychology, 28 (3), 387-394.
Davidoff, J. B. (1977). Hemispheric differences in dot detection. Cortex, 13(4), 434-444.
Davidoff, J. B.(1975).Hemispheric differences in the perception of lightness. Neuropsychologia,
13, 121–124.
de Lacoste , M.-C. , Horvath, D. S., & Woodward, D. J. (1991). Possible sex differences in the
developing human fetal brain. Journal of Clinical and Experimental Neuropsychology,
13, 831 – 846.
Desmond, J. E., Sum, J. M., Wagner, A. D., Demb, J. B., Shear, P. K., Glover, G. H., ... &
Morrell, M. J. (1995). Functional MRI measurement of language lateralization in Wada-
tested patients. Brain, 118(6), 1411-1419.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 58
Dickson, H. (1830). Case of amnesia. American Journal of the Medical Sciences, 7, 359-360.
Dirks, D. (1964). Perception of dichotic and monaural verbal material and cerebral dominance
for speech. Acta oto-laryngologica, 58 (1-6), 73-80.
Dodrill, C. B., & Ojemann, G. A. (1997). An exploratory comparison of three methods of
memory assessment with the intracarotid amobarbital procedure.Brain and
cognition, 33(2), 210-223.
Drake, D. (1834). Case of partial amnesia, in which the memory for proper names was lost.
American Journal of the Medical Sciences, 15, 551-553.
Eberstaller , O. (1890). Das Stirnhirn . Vienna : Ein Beitrag zur Anatomie der Oberflache des
Gehirns. Urban & Schwarzenberg.
Efron, R. (1990). The decline and Fall of Hemispheric Specialization. Hillsdale, NJ: Erlbaum.
Eidelberg, D., & Galaburda , A. M. (1984). Inferior parietal lobule: Divergent architectonic
asymmetries in the human brain. Archives of Neurology, 41, 843 – 852.
Fink , G. R. , Halligan , P. W. , Marshall , J. C. , Frith , C. D. , Frackowiak , S. J. , & Dolan , R.
J. (1996). Where in the brain does visual attention select the forest and the trees? Nature ,
382 , 626 – 628 .
Fink , G. R. , Halligan , P. W. , Marshall , J. C. , Frith , C. D. , Frackowiak , S. J. , & Dolan , R.
J. (1997). Neural mechanisms involved in the processing of global and local aspects of
hierarchically organized visual stimuli . Brain , 120 , 1779 – 1791 .
Flourens, M.J.P. (1824). Recherches Expirimentales sur les Propriites et les Fonctions du
Systeme Nerveux dans les Animaux Vertibris. Paris, France: Crevot.
Flourens, P. (1846). Phrenology Examined. Translated from the 2nd ed. (1845) by Charles de
Lucena Meigs. Philadelphia, PA: Hogan & Thompson.
Chapter 1| Introduction
P.| 59
Fox, N. A., & Davidson, R. J. (1986). Taste-elicited changes in facial signs of emotion and the
asymmetry of brain electrical activity in human newborns . Neuropsychologia , 24 , 417 –
422 .
Frackowiak, R. S., Friston, K. J., Frith, C. D., Dolan, R. J., & Mazziotta, J. C. (1997). Human
brain function. New York, 528.
Friederici, A. D., Pfeifer, E., & Hahne, A. (1993). Event-related brain potentials during natural
speech processing: Effects of semantic, morphological and syntactic violations. Brain
Research. Cognitive Brain Research, 1, 183 – 192.
Friston, K. J. (2003). Statistical parametric mapping. In Neuroscience Databases (pp. 237-250).
Springer US.
Fujiki, N., Jousmaki, V., Hari, R. (2002). Neuromagnetic responses to frequency-tagged sounds:
a new method to follow inputs from each ear to the human auditory cortex during
binaural hearing. J. Neurosci, 22, 1–4.
Galaburda , A. M. (1980). La region de Broca: Observations anatomiques faites un si e cle apr e
s la mort de son d e coveur . Revue Neurologique, 136, 609 – 616.
Geffen, G., Bradshaw, J. L., & Wallace, G. (1971). Interhemispheric effects on reaction time to
verbal and nonverbal visual stimuli. Journal of Experimental Psychology, 87, 415-22.
Geschwind , N. , & Levitsky , W. (1968). Human brain: Left – right asymmetries in temporal
speech region. Science, 161, 186 – 187.
Gesner, J.A.P. (1769-1776). Samlung von Beobachtungen aus der Arzneigelehrheit und
Naturkunde. Nordlingen, Bavana, Swabia.
Good, C. D. et al. (2001). A voxel based morphometric study of ageing in 465 normal adult
human brains. Neuroimeage, 14, 21-36.
Goodglass, H., & Calderón, M. (1977). Parallel processing of verbal and musical stimuli in right
and left hemispheres. Neuropsychologia, 15(3), 397-407.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 60
Gordon, H. W. (1970). Hemispheric asymmetries in the perception of musical
chords. Cortex, 6(4), 387-398.
Greve, D. N., Van der Haegen, L., Cai, Q., Stufflebeam, S., Sabuncu, M. R., Fischl, B., &
Brysbaert, M. (2013). A surface-based analysis of language lateralization and cortical
asymmetry. Journal of cognitive neuroscience, 25(9), 1477-1492.
Han , S. , Weaver , J. A. , Murray , S. O. , Kang , X. , Yund , E. W. , & Woods , D. L. (2002).
Hemispheric asymmetry in global/local processing: Effects of stimulus position and
spatial frequency. NeuroImage, 17, 1290 – 1299.
Hannay, H. J. (1979). Asymmetry in reception and retention of colors. Brain and
Language, 8(2), 191-201.
Harrington, A. (1995). Unfinished business: models of laterality in the nineteenth century. Brain
asymmetry, 3-27.
Harris, L. J. (1999). Early theory and research on hemispheric specialization. Schizophrenia
Bulletin, 25(1), 11-39.
Hasnain , M. K. , Fox , P. T. , & Woldorff , M. G. (2006). Hemispheric asymmetry of sulcus –
function correspondence: Quantization and developmental implications. Human Brain
Mapping, 27, 277 – 287.
Heillige, J. B., Taylor, K. B., Lesmes , L. , & Peterson , S. (1998). Relationship between brain
morphology and behavioural measures of hemispheric asymmetry and interhemispheric
interaction. Brain and Cognition, 36, 158 -192.
Hellige , J. B. (1993). (2001 paperback). Hemispheric asymmetry: What ’ s right and what ’ s left
. Cambridge, MA : Harvard University Press .
Hellige , J. B. (1995). Hemispheric asymmetry for components of visual information processing.
In R. J. Davidson & K. Hugdahl (Eds.), Brain asymmetry (pp. 99 – 121 ). Cambridge,
MA: MIT Press.
Chapter 1| Introduction
P.| 61
Hellige , J. B. , & Cumberland , N. (2001). Categorical and coordinate spatial processing: More
on contributions of the transient/magnocellular visual system . Brain and Cognition , 45 ,
155 – 163 .
Hellige , J. B. , & Michimata , C. (1989). Categorization versus distance: Hemispheric
differences for processing of spatial information. Memory & Cognition, 17, 770 – 776.
Hellige, J. B., Laeng, B., & Michimata, C. (2010). 13 Processing Asymmetries in the Visual
System. The Two Halves of the Brain, 379.
Heron,W. (1957). Perception as a function of retinal locus and attention. American Journal of
Psychology, 70(1), 38–48.
Hertz, R. (1909). La preeminence de la main droite: Etude sur la polarite religieuse. Revue
Philosophique, 68, 553-580. (Translated in Hertz, 1960.)
Hilliard, R. D. (1973). Hemispheric laterality effects on a facial recognition task in normal
subjects. Cortex, 9(3), 246-258.
Hines, D., Satz, P., & Clementino, T. (1973). Perceptual and memory components of the superior
recall of letters from the right visual half-fields.Neuropsychologia, 11(2), 175-180.
Holland, H. (1852). On the brain as a double organ. In: H. Holland, ed. Chapters on Mental
Physiology. London, England: Longman, Brown, Green & Longmans, 1852. pp. 170-191.
(Original work published in Holland, H., Medical Notes and Reflections. London,
England: Haswell, Barrington, and Haswell, 1839.).
Holland, S. K., Plante, E., Weber Byars, A., Strawsburg, R. H., Schmithorst, V. J., & Ball Jr, W.
S. (2001). Normal fMRI brain activation patterns in children performing a verb
generation task. Neuroimage, 14(4), 837-843.
Hopkins , W. D. (1997). Hemispheric specialization for local and global processing of
hierarchical visual stimuli in chimpanzees ( Pan troglodytes ) . Neuropsychologia , 34 ,
343 – 348.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 62
Hopkins, W. D. (Ed.). (2007). The evolution of hemispheric specialization in primates . London:
Elsevier.
Hubner , R. (1998). Hemispheric differences in global/local processing revealed by same –
different judgments . Visual Cognition , 5 , 457 – 478 .
Hubner , R. , & Studer , T. (2009). Functional hemispheric differences for the categorization of
global and local information in naturalistic stimuli . Brain and Cognition , 69, 11 - 18 .
Hugdahl, K. (1995). Dichotic listening: Probing temporal lobe functional integrity. Brain
asymmetry, 1, 123-56.
Hugdahl, K. (2000). Lateralization of cognitive processes in the brain. Acta
psychologica, 105(2), 211-235.
Hugdahl, K. (2003). Dichotic listening in the study of auditory laterality. The asymmetrical
brain, 1, 441-75.
Hugdahl, K. (2011). Fifty years of dichotic listening research–Still going and going and…. Brain
and cognition, 76(2), 211-213.
Hugdahl, K., Law, I., Kyllingsbæk, S., Brønnick, K., Gade, A., & Paulson, O. B. (2000). Effects
of attention on dichotic listening: an 15O‐PET study. Human Brain Mapping, 10(2), 87-
97.
Hugdahl, K., Løberg, E. M., Falkenberg, L. E., Johnsen, E., Kompus, K., Kroken, R. A., ... &
Özgören, M. (2012). Auditory verbal hallucinations in schizophrenia as aberrant
lateralized speech perception: evidence from dichotic listening. Schizophrenia
research, 140(1), 59-64.
Hughes , H. C. , Fendrich , R. , & Reuter-Lorenz , P. A. (1990). Global versus local processing in
the absence of low spatial frequencies . Journal of Cognitive Neuroscience , 2 , 272 –
282.
Chapter 1| Introduction
P.| 63
Hunter, Z. R., & Brysbaert, M. (2008). Visual half-field experiments are a good measure of
cerebral language dominance if used properly: Evidence from
fMRI.Neuropsychologia, 46(1), 316-325.
Ingle , D. (2002). A wider view of the spatial mode of vision . Behavioral and Brain Sciences ,
25 , 108 – 110 .
Ivry , R. B. , & Robertson , L. C. (1998). The two sides of perception . Cambridge, MA : MIT
Press .
Jackson, S. (1828). Case of amnesia. American Journal of the Medical Sciences, 3, 272-274.
Jancke , L. , & Steinmetz , H. (2004). Anatomical brain asymmetries and their relevance for
functional asymmetries. In K. Hughdahl & R. J. Davidson (Eds.), The asymmetrical brain
(pp. 187 – 229). Cambridge, MA: MIT Press.
Jäncke, L., Specht, K., Shah, J. N., & Hugdahl, K. (2003). Focused attention in a simple dichotic
listening task: an fMRI experiment. Cognitive Brain Research,16(2), 257-266.
Jonsson , J. E. , & Hellige , J. B. (1986). Lateralized effects of blurring: A test of the visual
spatial frequency model of cerebral hemisphere asymmetry . Neuropsychologia , 24 , 351
– 362 .
Joseph B. Hellige. (1993). Hemispheric asymmetry: What's right and what's left(Vol. 6). Harvard
University Press.
Kamada , K. , Sawamura , Y. , Takeuchi , F. , Kuriki , S. , Kawai , K. , Morita , A. , et al. (2007).
Expressive and receptive language areas determined by a non-invasive reliable method
using functional magnetic resonance imaging and magnetoencephalography.
Neurosurgery, 60, 296 – 305.
Kayser, J., Tenke, C., Nordby, H., Hammerborg, D., Hugdahl, K., Erdmann, G. (1997). Event
related potential (ERP) asymmetries to emotional stimuli in a visual half-field paradigm.
Psychophysiology, 34(4), 414-426.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 64
Keenan , J. P. , Thangaraju , V. , Halpern , A. R. , & Schlaug , G. (2001). Absolute pitch and
planum temporale . NeuroImage, 14, 1402 – 1408.
Kimura, D. (1961). Cerebral dominance and the perception of verbal stimuli. Canadian Journal
of Psychology, 15, 166–170.
Kimura, D. (1964). Left ear differences in perception of melodies. Quarterly Journal of
Experimental Psychology, 16, 355-358.
Kimura, D. (1967). Functional asymmetry of the brain in dichotic listening. Cortex, 3, 163–168.
Kimura, D., & Folb, S. (1968). Neural processing of backwards-speech sounds. Science.
Kircher , T. T. , Rapp , A. , Grodd , W. , Buchkremer , G. , Weiskopf , N. , Lutzenberger , W. , et
al. (2004). Mismatch negativity responses in schizophrenia: A combined fMRI and
whole-head MEG study. American Journal of Psychiatry, 161, 294 – 304.
Kitterle, F. L., Christman, S., & Hellige, J. B. (1990). Hemispheric differences are found in the
identifi cation, but not the detection, of low versus high spatial frequencies. Perception &
Psychophysics, 48, 297 – 306.
Kitterle, F. L., Hellige, J. B., & Christman, S. (1992). Visual hemispheric asymmetries depend
on which spatial frequencies are task relevant. Brain and Cognition, 20, 308 – 314.
Kline , J. P. , Blackhart , G. C. , Woodward , K. M. , Williams , S. R. , & Schwartz , G. E. R.
(2000). Anterior electroencephalographic asymmetry changes in elderly women in
response to a pleasant and unpleasant odor. Biological Psychology, 52, 241 – 250.
Knecht, S., Drager, B., Deppe, M., Bobe, L., Lohmann, H., Floel, A., et al. (2000). Handedness
and hemispheric language dominance in healthy humans. Brain, 123, 2512–2518.
Knox, C., & Kimura, D. (1970). Cerebral processing of nonverbal sounds in boys and
girls. Neuropsychologia, 8(2), 227-237.
Chapter 1| Introduction
P.| 65
Koivisto, M., & Revonsuo, A. (2003). Object recognition in the cerebral hemispheres as revealed
by visual field experiments. Laterality: Asymmetries of Body, Brain and Cognition, 8(2),
135-153.
Kosslyn, S. M. (1987). Seeing and imagining in the cerebral hemispheres: A computational
approach. Psychological Review, 94, 148 – 175.
Kosslyn, S. M. (2006). You can play 20 questions with nature and win: Categorical versus
coordinate spatial relations as a case study. Neuropsychologia, 44, 1519 – 1523.
Kosslyn, S. M., Chabris, C. E., Marsolek, C. J., & Koenig, O. (1992). Categorical versus
coordinate spatial relations: Computational analyses and computer simulation . Journal of
Experimental Psychology. Human Perception and Performance, 18, 562 – 577.
Krach, S., Chen, L. M., & Hartje, W. (2006). Comparison between visual half-field performance
and cerebral blood flow changes as indicators of language dominance. Laterality:
Asymmetries of Body, Brain, and Cognition, 11(2), 122-140.
Kutas, M., & Hillyard, S. A. (1980). Reading senseless sentences: Brain potentials refl ect
semantic incongruity. Science, 207, 203 – 205.
Laeng, B. (1994). Lateralization of categorical and coordinate spatial functions: A study of
unilateral stroke patients . Journal of Cognitive Neuroscience, 6, 189 – 203.
Laeng, B., & Peters, M. (1995). Cerebral lateralization for the processing of spatial coordinates
and categories in left- and right-handers. Neuropsychologia, 33, 421 – 439.
Laeng, B., Carlesimo, G. A., Caltagirone, C., Capasso, R., & Miceli, G. (2002). Rigid and
nonrigid objects in canonical and noncanonical views: Hemispheric effects on object
identification. Cognitive Neuropsychology, 19, 697 – 720.
Laeng, B. , Chabris , C. F. , & Kosslyn , S. M. (2003). Asymmetries in encoding spatial relations.
In K. Hugdahl & R. Davidson (Eds.), The asymmetrical brain (pp. 303 – 339).
Cambridge, MA: MIT Press.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 66
Laeng, B., Zarrinpar, A., & Kosslyn, S. M. (2003). Do separate processes identify objects as
exemplars versus members of basic-level categories? Evidence from hemispheric
specialization. Brain and Cognition, 53, 15 – 27 .
Laeng, B., Peters, M., & McCabe, B. (1998). Memory for locations within regions: Spatial biases
and visual hemifield differences. Memory & Cognition, 26, 97 – 107.
Lansdell, H. (1969).Verbal and non-verbal factors in right-hemisphere speech: Relation to early
neurological history. Journal of Physiological and Comparative Psychology, 69, 734–
738.
Le May, M., & Culebras, A. (1972). A human brain: Morphological differences in the
hemispheres demonstrable by carotid angiography. New England Journal of Medicine,
287, 168 – 170.
Lehericy, S., Cohen, L., Bazin, B., Samson, S., Giacomini, E., Rougetet, R., ... & Baulac, M.
(2000). Functional MR evaluation of temporal and frontal language dominance compared
with the Wada test. Neurology, 54(8), 1625-1633.
Ley, R. G., & Bryden, M. P. (1979). Hemispheric differences in processing emotions and
faces. Brain and Language, 7(1), 127-138.
Ley, R. G., & Bryden, M. P. (1982). A dissociation of right and left hemispheric effects for
recognizing emotional tone and verbal content. Brain and Cognition, 1, 3-9.
Li , Y. J. , Ga , S. N. , Li , S. Y. , & Gao , X. G. (2007). Characteristics of hippocampal volumes
in healthy Chinese from MRI . Neurological Research, 29, 803 – 806.
Lipski, S. C., & Mathiak, K. (2007). A magnetoencephalographic study on auditory processing
of native and nonnative fricative contrasts in Polish and German listeners. Neuroscience
letters, 415(1), 90-95.
Loddenkemper, T, Morris, H. H, Lieneweaver, T, Kellinghaus, C. (2002). Repeated intracarotid
amobarbital test. Epilepsia 43, Suppl 7, 118-9. (abstract)
Chapter 1| Introduction
P.| 67
Lordat, J. (1843). Analyse de la parole pour servir a la th£orie de divers cas d'alalie et de
paralalie (de mutisme et d'imperfection du parler) que les Nosologistes ont mal connus.
Journal de la Sociiti de Medicine Pratique de Montpellier, 7, 333-353; 4, 17-33; 8, 1-17.
Luys, J. (1879). Etudes sur le de"doublement des operations ce"re*brales et sur le r61e isole" de
chaque hemisphere dans les ph£nemenes de la pathologie mentale. Bulletin de
I'Academie de Midecine, 8(2nd Series), 516-534, 547- 565.
Luys, J. (1881). Recherches nouvelles sur les he'miple'gies dmotives. Enciphale, 1, 378-398.
Magendie, F. (1822). Notes (translated by G. Hayward) on X. Bichat's Physiological Researches
Upon Life and Death (translated by F. Gold of 4th edition of Recherches Physiologique
sur la Vie et la Mort). Boston: Richardson and Lord, 1827. (Original French publication:
Paris, France: Gabou, Bechet Jeuve.)
McNeely, H. E., & Netley, C. E. (1998). Right hemisphere lateralization of emotional prosody
recognition predicts introverted personality in left-handers. Brain and Cognition, 37, 51–
54.
Meynert, T. (1866). Ein Fall von SprachstSrung, anatomisch begriindet. Medizinische Jahrbilch
der Zeitschrift des Artze, 12, 152-189.
Meynert, T. (1872). Von Gehirne der SSugethiere In: Strieker, S., ed. Handbuch der Lehre von
dem Geweben des Menschen und der Thiere, 1869-1872, Leipzig, Germany: W.
Engelmann. Translated excerpts in Clarke, E., and O'Malley, CD. The Human Brain and
Spinal Cord: A Historical Study Illustrated by Writings From Antiquity to the Twentieth
Century. Berkeley, CA: The University of California Press, 1968. pp. 602-605.
Michimata, C. (1997). Hemispheric processing of categorical and coordinate spatial relations in
vision and visual imagery. Brain and Cognition, 33(3), 370-387.
Milner, B. (1962). Study of short-term memory after intracarotid injection of sodium
amytal. Trans Am Neurol Assoc, 87, 224-226.
Mishkin , M. , Ungerleider , L. G. , & Macko , K. A. (1983). Object vision and spatial vision:
Two cortical pathways. Trends in Neurosciences, 6, 414 – 417.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 68
Mishkin, M., & Forgays, D. G. (1952). Word recognition as a function of retinal locus. Journal
of Experimental Psychology, 43, 43-48.
Näätänen R, Lehtokoski A, Lennes M, Cheour M, Huotilainen M, Iivonen A, Vainio M, Alku P,
Ilmoniemi RJ, Luuk A, Allik J, Sinkkonen J, Alho K. (1997). Language-specific
phoneme representations revealed by electric and magnetic brain responses. Nature, 385,
432–434.
Nagae, S., & Moscovitch, M. (2002). Cerebral hemispheric differences in memory of emotional
and non-emotional words in normal individuals. Neuropsychologia, 40 (9), 1601-1607.
Navon , D. (1977). Forest before trees: The precedence of global features in visual perception .
Cognitive Psychology , 9 , 353 – 383 .
Ng, Virginia. W., Eslinger, P. J., Williams, S. C., Brammer, M. J., Bullmore, E. T., Andrew, C.
M., ... & Benton, A. L. (2000). Hemispheric preference in visuospatial processing: a
complementary approach with fMRI and lesion studies. Human brain mapping, 10(2),
80-86.
Niemann , K. , Hammers , A. , Coenen , V. A. , Thron , A. , & Klosterk o tter , J. (2000).
Evidence of a smaller left hippocampus and left temporal horn in both patients with first
episode schizophrenia and normal control subjects. Psychiatry Research: Neuroimaging,
99, 93 – 110.
Nobre, A. C., & Mccarthy, G. (1995). Language-related field potentials in the anterior-medial
temporal lobe: II. Effects of word type and semantic priming. The Journal of
Neuroscience, 15(2), 1090-1098.
Ocklenburg, S., Westerhausen, R., Hirnstein, M., & Hugdahl, K. (2013). Auditory hallucinations
and reduced language lateralization in schizophrenia: a meta-analysis of dichotic listening
studies. Journal of the International Neuropsychological Society, 19(04), 410-418.
Ojemann, J. G., & Kelley, W. M. (2002). The frontal lobe role in memory: a review of
convergent evidence and implications for the Wada memory test.Epilepsy &
behavior, 3(4), 309-315.
Chapter 1| Introduction
P.| 69
Okubo , M. , & Michimata , C. (2002). Categorical and coordinate spatial processing in the
absence of low spatial frequencies . Journal of Cognitive Neuroscience , 14 , 291 – 297 .
Okubo , M. , & Michimata , C. (2004). The role of high spatial frequencies on hemispheric
processing of categorical and coordinate spatial relations . Journal of Cognitive
Neuroscience , 16 , 1576 – 1582 .
Ornstein, R., Johnstone, J., Herron, J., & Swencionis, C. (1980). Differential right hemisphere
engagement in visuospatial tasks. Neuropsychologia, 18(1), 49-64.
Osterhout , L. , & Holcomb , P. J. (1992). Event-related brain potentials elicited by syntactic
anomaly. Journal of Memory and Language, 31, 785 – 806.
Palermo , L. , Bureca , I. , Matano , A. , & Guariglia , C. (2008). Hemispheric contribution to
categorical and coordinate representational processes: A study on brain-damaged
patients. Neuropsychologia, 46, 2802 – 2807.
Patterson, K., Bradshaw, J. L. (1975). Differential Hemispheric Mediation of Nonverbal Visual
Stimuli. Journal of Experimental Psychology: Human Perception and Performance, 1
(3), 246-252.
Penhune , V. B. , Zatorre , R. J. , MacDonald , J. D. , & Evans , A. C. (1996). Interhemispheric
anatomical differences in human primary auditory cortex: Probabilistic mapping and
volume measurement from magnetic resonance scans. Cerebral Cortex (New York, N.Y.),
6, 661 – 672.
Pennal, B. E. (1977). Human cerebral asymmetry in color discrimination.
Neuropsychologia, 15(4), 563-568.
Pfeifer, B. (1911). Zur Lokalisation der corticalen motorischen und sensorischen Aphasie und
der ideokinetischen Apraxie . Journal f ü r Psychologie und Neurologie, 18, 23 – 35.
Pinker, S. (2007). The stuff of thought: Language as a window into human nature. New York :
Penguin Books .
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 70
Procha'ska, J. (1784). Adnotationum academicarum. Fasciculus tertius. Prague, Bohemia: W.
Gerle. (Translated and edited by Thomas Laycock as A Dissertation on the Functions of
the Nervous System.) In: The Principles of Physiology, by John Augustus Unzer; and a
Dissertation on the Function of the Nervous System, by George Prochiska. London,
England: Sydenham Society, 1851.
Pujol, J., Deus, J., Losilla, J. M., & Capdevila, A. (1999). Cerebral lateralization of language in
normal left-handed people studied by functional MRI. Neurology, 52, 1038–1043.
Pulvermuller, F. (2001). Brain reflections of words and their meaning. Trends in Cognitive
Sciences, 5, 517 – 524.
Rademacher, J., Caviness, J., Steinmetz, H., & Galaburda, A. M. (1993). Topographical variation
of the human primary cortices: Implications for neuroimaging, brain mapping, and
neurobiology . Cerebral Cortex (New York, N.Y.), 3, 313 – 329.
Rausch R, Silfvenius H, Weiser HG, Dodrill CB, Meador KJ, Jones Gotman MJ. (1993)
Intraarterial amobarbital procedures. In Engel J, Jr. (Ed) Surgical Treatment of the
Epilepsies. 2nd ed. Raven Press, New York, pp. 341–357.
Ressel , V. , Wilke , M. , Lidzba , K. , Preissl , H. , Krageloh-Mann , I. , & Lutzenberger , W.
(2006). Language lateralization in MEG: Two tasks to investigate hemispheric
dominance. NeuroReport, 17, 1209 – 1213.
Rhodes, G., & Wooding, R. (1989). Laterality effects in identification of caricatures and
photographs of famous faces. Brain and cognition, 9(2), 201-209.
Riese, W. (1954). Auto observation of aphasia reported by an eminent nineteenth-century
medical scientist. Bulletin of the History of Medicine, 28, 237-242.
Robertson, L. C. (1986). From gestalt to neo-gestalt. In T. J. Knapp, & L. C. Robertson (Eds.),
Approaches to cognition: Contrasts and controversies (pp. 169±188). Hillsdale, NJ:
Erlbaum.
Chapter 1| Introduction
P.| 71
Rogers, L. J., & Andrew, R. J. (Eds.). (2002). Comparative vertebrate lateralization. Cambridge,
England: Cambridge University Press .
Rossion, B., Dricot, L., Devolder, A. , Bodart , J.-M. , Crommelinck, M., de Gelder, B., et al.
(2000). Hemispheric asymmetries for whole-based and part-based face processing in the
human fusiform gyrus. Journal of Cognitive Neuroscience, 12, 793 – 802.
Roth, E. C., & Hellige, J. B. (1998). Spatial processing and hemispheric asymmetry:
Contributions of the transient/magnocellular visual system. Journal of Cognitive
Neuroscience, 10, 472 – 484.
Saneyoshi, A., & Michimata, C. (2009). Lateralized effects of categorical and coordinate spatial
processing of component parts on the recognition of 3-D non-namable objects . Brain and
Cognition, 71, 181 – 186.
Saneyoshi, A., Kaminaga, T., & Michimata, C. (2006). Hemispheric processing of categorical
metric properties in object recognition. NeuroReport, 17, 517 – 521.
Sasaki , Y. , Hadjikhani , N. , Fischl , B. , Liu , A. K. , Marrett , S. , Dale , A. M. , et al. (2000).
Local and global attention are mapped retinotopically in human occipital cortex .
Proceedings of the National Academy of Sciences of the United States of America, 98,
2077 – 2082.
Schlaug , G. , J a ncke , L. , Huang , Y. , & Steinmetz , H. (1995). In vivo evidence of structural
brain asymmetry in musicians. Science, 267, 699 – 701.
Schneider, G. E. (1967). Contrasting visuomotor functions of tectum and cortex in the golden
hamster. Psychologische Forschung, 31, 52 – 62.
Sergent, J. (1983). The role of the input in visual hemispheric asymmetries. Psychological
Bulletin, 93, 481-514.
Sewall, T. (1837). An Examination of Phrenology; In Two Lectures, Delivered to the Students of
the Columbian College, District of Columbia. Washington City [Washington, D.C.]: B.
Homans.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 72
Shankweiler, D., & Studdert-Kennedy, M. (1967). Identification of consonants and vowels
presented to left and right ears. The Quarterly journal of experimental psychology, 19(1),
59-63.
Shapleske , J. , Rossell , S. L. , Woodruff , P. W. R. , & David , A. S. (1999). The planum
temporale: A systematic, quantitative review of its structural, functional and clinical
signifi cance . Brain Research. Brain Research Reviews, 29, 26 – 49.
Shi , Y. , Thompson , P. M. , de Zubicaray , G. I. , Rose , S. E. , Tu , Z. , Dinov , I. D. , et al.
(2007). Direct mapping of hippocampal surfaces with intrinsic shape context.
NeuroImage, 37, 792 – 807.
Shipley-Brown, F., Dingwall, W. O., Berlin, C. I., Yeni-Komshian, G., & Gordon-Salant, S.
(1988). Hemispheric processing of affective and linguistic intonation contours in normal
subjects. Brain and Language, 33 (1), 16-26.
Shtyrov , Y. , Kujala , T. , Palva , S. , Ilmoniemi , R. J. , & N a a t a nen , R. (2000).
Discrimination of speech and of complex nonspeech sounds of different temporal
structure in the left and right cerebral hemispheres. NeuroImage, 12, 657 – 663.
Sidtis, J. J., & Bryden, M. P. (1978). Asymmetrical perception of language and music: Evidence
for independent processing strategies. Neuropsychologia, 16 (5), 627-632.
Slotnick , S. D. , & Moo , L. R. (2006). Prefrontal cortex hemispheric specialization for
categorical and coordinate visual spatial memory. Neuropsychologia, 44, 1560 – 1568 .
Snyder , P. J. , Bilder , R. M. , Wu , H. , Bogerts , B. , & Lieberman , J. A. (1995). Cerebellar
volume asymmetries are related to handedness: A quantitative study. Neuropsychologia,
33, 407 – 419.
Speaks, C., Niccum, N., & Carney, E. (1982). Statistical properties of responses to dichotic
listening with CV nonsense syllables. The Journal of the Acoustical Society of
America, 72(4), 1185-1194.
Chapter 1| Introduction
P.| 73
Sperry, R. W. (1974). Lateral specialization in the surgically separated hemispheres. In The
neuroscience: third study program (pp. 5±19). Cambridge: MIT Press.
Spreen, O., Spellacy, F. J., & Reid, J. R. (1970). The effect of interstimulus interval and intensity
on ear asymmetry for nonverbal stimuli in dichotic listening. , Neuropsychologia, 8, 245-
250.
Steinbeis, N., & Koelsch, S. (2008). Comparing the processing of music and language meaning
using EEG and FMRI provides evidence for similar and distinct neural representations .
PLoS ONE, 3 ( 5 ), 2226 .
Steinmetz , H. , Herzog , A. , Schlaug , G. , Huang , Y. , & J a ncke , L. (1995). Brain
(a)symmetry in monozygotic twins. Cerebral Cortex (New York, N.Y.), 5, 296 – 300.
Steinmetz, H. (1996). Structure, functional and cerebral asymmetry: In vivo morphometry of the
planum temporale . Neuroscience and Biobehavioral Reviews, 20, 587 – 591.
Studdert-Kennedy, M., & Shankweiler, D. (1970). Hemispheric specialization for speech
perception. Journal of the Acoustical Society of America, 48, 579–594.
Swedenborg, E. (1740-1741). Oeconomia regni animalis. Amsterdam, The Netherlands:
Changuion.
Szabo , C. A. , Xiong , J. , Lancaster , J. L. , Rainey , L. , & Fox , P. (2001). Amygdalar and
hippocampal volumetry in control participants: Differences regarding handedness. AJNR.
American Journal of Neuroradiology , 22 , 1342 – 1345 .
Szaflarski, J. P., Rajagopal, A., Altaye, M., Byars, A. W., Jacola, L., Schmithorst, V. J., ... &
Holland, S. K. (2012). Left-handedness and language lateralization in children. Brain
research, 1433, 85-97.
Techentin, C., & Voyer, D. (2007). Congruency, attentional set, and laterality effects with
emotional words. Neuropsychology, 21 (5), 646.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 74
Techentin, C., Voyer, D., & Klein, R. M. (2009). Between-and within-ear congruency and
laterality effects in an auditory semantic/emotional prosody conflict task. Brain and
cognition, 70 (2), 201-208.
Tervaniemi , M. , Kujala , A. , Alho , K. , Virtanen , J. , Ilmoniemi , R. J. , & Naatanen , R.
(1999). Functional specialization of the human auditory cortex in processing phonetic and
musical sounds: A magnetoencephalographic (MEG) study. NeuroImage, 9, 330 – 336.
Tervaniemi, M., & Hugdahl, K. (2003). Lateralization of auditory-cortex functions. Brain
Research Reviews, 43 (3), 231-246.
Teuber,H. L.(1974).Why two brains? In: F. O. Schmidts, & F. G. Worden (Eds.), The
Neurosciences: Third Study Program (pp. 71–74).Cambridge, MA: MIT Press.
Thomsen, T., Rimol, L. M., Ersland, L., & Hugdahl, K. (2004). Dichotic listening reveals
functional specificity in prefrontal cortex: an fMRI study. Neuroimage, 21 (1), 211-218.
Thut , G. , Hauert , C. A. , Blanke , O. , Morand , S. , Seeck , M. , Gonzalez , S. L. , et al. (2000).
Visually induced activity in human frontal motor areas during simple visuomotor
performance . NeuroReport, 11, 2843 – 2848.
Toga, A. W., & Thompson, P. M. (2003). Mapping brain asymmetry. Nature Reviews
Neuroscience, 4 (1), 37-48.
Trojano , L. , Conson , M. , Maffei , R. , & Grossi , D. (2006). Categorical and coordinate spatial
processingin the imagery domain investigated by rTMS . Neuropsychologia , 44, 1569 –
1574 .
Umiltà, C., Salmaso, D., Bagnara, S., & Simion, F. (1979). Evidence for a right hemisphere
superiority and for a serial search strategy in a dot detection task.Cortex, 15 (4), 597-608.
Uylings, H. B. M., Jacobsen, A. M., Zilles, K., & Amunts, K. (2006). Left – right asymmetry in
volume and number of neurons in adult Broca’s area. Cortex, 42, 652 – 658.
Chapter 1| Introduction
P.| 75
Van den Noort, M., Specht, K., Rimol, L. M., Ersland, L., & Hugdahl, K. (2008). A new verbal
reports fMRI dichotic listening paradigm for studies of hemispheric
asymmetry. Neuroimage, 40 (2), 902-911.
Van der Haegen, L., Cai, Q., & Brysbaert, M. (2012). Colateralization of Broca’s area and the
visual word form area in left-handers: fMRI evidence. Brain and language, 122 (3), 171-
178.
Van der Haegen, L., Cai, Q., Seurinck, R., & Brysbaert, M. (2011). Further fMRI validation of
the visual half field technique as an indicator of language laterality: A large-group
analysis. Neuropsychologia, 49 (10), 2879-2888.
Van der Haegen, L., Westerhausen, R., Hugdahl, K., & Brysbaert, M. (2013). Speech dominance
is a better predictor of functional brain asymmetry than handedness: A combined fMRI
word generation and behavioral dichotic listening study. Neuropsychologia, 51 (1), 91-
97.
van der Ham , I. J. M. , van Wezel , R. J. A. , Oleksiak , A. , & Postma , A. (2007). The time
course of hemispheric differences in categorical and coordinate spatial processing .
Neuropsychologia , 45 , 2492 – 2498.
Verma, A., Van der Haegen, L., & Brysbaert, M. (2013). Symmetry detection in typically and
atypically speech lateralized individuals: A visual half-field study.Neuropsychologia, 51
(13), 2611-2619.
Vicq d'Azyr, F. (1786). Traiti d'Anatomie et Physiologie avec des Planches Colonies
Reprtsentant au Natural Les Divers Organes de I'Homme et des Animaux. Vol. 1. Paris,
France: F.A. Didot l'aine.
von Economo , C. , & Horn , L. (1930). Uber Windungsrelief, Maseund Rindenarchitektonik der
Supratemporalfl a che, ihre individuellen und ihre Seitenunterschiede. Zeitschrift f ür
Neurologieund Psychiatrie , 130 , 678 – 757 .
Voyer, D. (1998). On the reliability and validity of noninvasive laterality measures. Brain and
Cognition, 36 (2), 209-236.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 76
Voyer, D., & Rodgers, M. A. (2002). Reliability of laterality effects in a dichotic listening task
with nonverbal material. Brain and Cognition, 48, 602–606.
Wada, J. (1949). A new method for the determination of the side of cerebral speech dominance.
A preliminary report on the intracarotid injection of sodium amytal in man. Medical
Biology, 14, 221-222.
Wada, J. A. , & Rasmussen , A. T. (1960). Intracarotid injection of sodium amytal for the
lateralization of cerebral speech dominance. Journal of Neurosurgery, 17, 266 – 282.
Wang , L. , Hosakere , M. , Trein , J. , Miller , A. , Ratnnanather , J. , Barch , D. , et al. (2007).
Abnormalities of cingulate gyrus neuroanatomy in schizophrenia. Schizophrenia
Research, 93, 66 – 78.
Watanabe, E., Maki, A., Kawaguchi, F., Takashiro, K., Yamashita, Y., Koizumi, H., &
Mayanagi, Y. (1998). Non-invasive assessment of language dominance with near-
infrared spectroscopic mapping. Neuroscience letters,256(1), 49-52.
Watkins , K. E. , Paus , T. , Lerch , J. P. , Zijdenbos , A. , Collins , D. L. , Neelin , P. , et al.
(2001). Structural asymmetries in the human brain: A voxel-based statistical analysis of
142 MRI scans. Cerebral Cortex (New York, N.Y.), 11, 868 – 877.
Wernicke, C. (1874). Der Aphasiche Symtomencomplex. Eine Psychologische Studie auf
Anatomischer Basis. Breslau, Germany: M. Conn and Weigart.
Whitaker, H. A., & Ojemann, G. A. (1977). LATERALIZATION OF HIGHER CORTICAL
FUNCTIONS: A CRITIQUE*. Annals of the New York Academy of Sciences, 299(1),
459-473.
Whitehouse, A. J., Badcock, N., Groen, M. A., & Bishop, D. V. (2009). Reliability of a novel
paradigm for determining hemispheric lateralization of visuospatial function. Journal of
the International Neuropsychological Society,15(06), 1028-1032.
Chapter 1| Introduction
P.| 77
Wildgruber, D., Hertrich, I., Riecker, A., Erb, M., Anders, S., Grodd, W., & Ackermann, H.
(2004). Distinct frontal regions subserve evaluation of linguistic and emotional aspects of
speech intonation. Cerebral cortex, 14(12), 1384-1389.
Wile, I. S. (1934). Handedness: Right and left. Boston: Lothrop, Lee & Shepard.
Wilkinson, D. T., & Halligan, P. W. (2002). The effects of stimulus symmetry on landmark
judgments in left and right visual fields. Neuropsychologia, 40 (7), 1045-1058.
Willis, T. (1965). The Anatomy of the Brain and Nerves. 2 vols. Feindel, W., ed. Montreal,
Canada: McGill University Press. (Facsimile of the English translation [1681] by S.
Pordage of Cerebri Anatome: cui accessit nervorum descriptio et usus. Original work
published in London by J. Martyn, and J. Allestry, 1664.)
Witelson, S. F., & Kigar, D. L. (1992). Sylvian fi ssure morphology and asymmetry in men and
women: Bilateral differences in relation to handedness in men. Journal of Comparative
Neurology, 323, 326 – 340.
Yamaguchi, S., Yamagata, S., & Kobayashi, S. (2000). Cerebral asymmetry of the “top-
down”allocation of attention to global and local features. Journal of Neuroscience, 20, 1
– 5.
Yoshida, T., Yoshino, A. , Takahashi , Y. , & Nomura , S. (2007). Comparison of hemispheric
asymmetry in global and local information processing and interference in divided and
selective attention using spatial frequency fi lters . Experimental Brain Research , 181 ,
519 – 529 .
Zaidel, E. (1983). A response to Gazzaniga: Language in the right hemisphere, convergent
perspectives.
Zangwill, O. L. (1976). Thought and the Brain. British Journal of Psychology, 67(3), 301-314.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
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Chapter 2|A right visual field advantage for tool recognition
P.| 79
Chapter 2: A right visual field advantage for tool
recognition in the visual half field paradigm
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Chapter 2|A right visual field advantage for tool recognition
P.| 81
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
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Chapter 2: A right visual field advantage for tool recognition in the
visual half-field paradigm
Neuropsychological and brain imaging studies have shown that the identification and use
of tools mainly involve areas of the left hemisphere. We investigate whether this dominance can
be observed in a behavioral visual half-field (VHF) task as well. To make sure that the VHF
effect was due to laterality and not due to attentional bias, we made use of two tasks: tool
recognition and object recognition. On the basis of the existing literature, we predicted a right
visual field (RVF) advantage for tool recognition, but not for object recognition. Twenty right-
handed participants made judgments about whether one of two bilaterally presented stimuli was
an object/non-object or a tool/non-tool. No VHF/hemisphere advantage was found for object
recognition, whereas a significant RVF/left hemisphere advantage was observed for tool
recognition. These findings show that VHF tasks can be used as a valid laterality measure of tool
recognition.
Introduction
The use and manufacturing of tools are typical human skills, going back to prehistoric times
(Ambrose, 2001); although primates can also be taught to manipulate existing objects in order to
achieve goals. Neuropsychological and brain imaging research have indicated that tool
knowledge in humans not only
This Chapter has been published as Verma, A., & Brysbaert, M. (2011). A right visual field advantage for tool
recognition in the visual half-field paradigm. Neuropsychologia, 49, 2342-2348.
Chapter 2|A right visual field advantage for tool recognition
P.| 83
involves dedicated brain regions but also that these areas are lateralized to the language dominant
(usually the left) hemisphere (Lewis, 2006).
Tool knowledge involves two types of information: (i) knowledge about tools and their
functions, and (ii) the motor skills needed to manipulate tools. Evidence from patients with brain
damage suggests that these two types of information are controlled by different brain areas, as
there is a double dissociation between both functions (Buxbaum, Schwartz, & Carew, 1997;
Buxbaum, Vermonti, & Schwartz, 2000). Patients suffering from ideational apraxia have
problems with the knowledge of tools and their use, whereas patients with ideomotor apraxia are
particularly deficient in the effective manipulation of tools.
Randerath, Goldenberg, Spijkers, Li, and Hermsdorfer (2010) examined 42 patients and
18 healthy controls on tool grasping and typical use of tools. They found that patients with
impaired tool use had a large area of overlap in the left supramarginal gyrus, whereas patients
with erroneous grasping had lesion overlap in the left inferior frontal gyrus and the left angular
gyrus. Goldenberg and Spatt (2009) examined 38 patients with brain damage and compared
appropriate tool use (both for common tools and new tools) and functional associations to tools
(i.e., knowing which recipients are appropriate for a tool and which other tool could be used for
the same purpose). These authors too observed that parietal lesions involving the left
supramarginal gyrus impaired tool use (both common and novel), whereas left frontal lesions
affected tool use and tool knowledge (as assessed by the test for functional associations). Osiurak
et al. (2009) compared 21 left brain damaged, 11 right brain damaged and 41 healthy controls on
experimental tests assessing the conventional use of objects, conceptual knowledge about object
function, pantomime of object use, recognition of object utilization gestures, and unusual use of
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
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objects. They found that left brain damage patients had more difficulties on the unusual use of
objects than controls or right brain damaged patients.
Brain imaging has also been used to investigate and localize the various components of
tool use. The most frequently used task involves asking participants to pantomime specific tool
operations and to compare these movements to repetitive limb movements (Choi et al., 2001), to
other meaningful hand gestures (Fridman et al., 2006), or to meaningless hand movements
(Fridman et al., 2006; Grezes & Decety, 2001a; Johnson Frey, Newman Norlund, & Grafton,
2005; Moll et al., 2000). Technological limitations often prevent the investigation of real tool
use. Therefore, researchers usually work with imagined operations, asking participants to engage
in mental simulations of tool use; the assumption being that the brain activity during simulation
corresponds to that of the actual operation.
Another frequently used paradigm in the functional neuroimaging literature involves
showing participants pictures of tools vs. pictures of humans, animals, houses, faces, or even
scrambled images, and measuring the differences in brain activity (Beauchamp, Lee, Haxby &
Martin, 2002; Chao, Haxby & Martin, 1999; Chao & Martin, 2000; Creem Regehr & Lee, 2005).
Kallenbach, Brett, and Patterson (2003) argued that the best comparison is tools vs. other
manmade objects, such as houses, because otherwise it is difficult to determine whether the
observed differences in brain activity are tool specific or caused by processing differences
between man-made things and naturally occurring organisms (humans, animals). Other
neuroimaging studies have involved naming tools vs. animals (Chao et al., 1999), or naming
tools vs. actions (Rumiati et al., 2004).
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In line with the neuropsychological evidence, two sets of left-hemisphere brain areas
have been identified in functional neuroimaging: Those related to the identification of tools, and
those related to the motor skills required for tool manipulation. As far as the identification of
tools is concerned, three cortical areas have been identified. They are: the left ventral pre-central
gyrus in the frontal lobe (ventral Premotor Cortex, VPMCx), the left Intraparietal Sulcus (IPS) in
the posterior parietal cortex, and the posterior middle temporal gyrus (PMTG) either on the left
or bilaterally (Beauchamp et al., 2002; Chao & Martin, 2000; Martin, Wiggs, Ungerleider &
Haxby, 1996; Perani et al., 1999). PMTG was particularly involved in a study by Chao et al.
(1999), who compared the perception of tools to that of houses, suggesting that the activity in
this area could be associated with the manipulability of the object (tools vs. houses). Chao and
Martin (2000) showed additional activation of the left VPMCx and the left IPS for the naming of
manipulable tools vs. houses. The left VPMCx has also been shown active during the
pantomiming of tool use, imagining motor actions, observation of movement; hence leading to
the proposal that it stores movement representations and relevant motor information for tool use
(Buccino et al., 2001; Decety et al., 1994; Grafton, Fagg, Woods & Arbib, 1996; Moll et al.,
2000). The left IPS activity has been linked to the retrieval of tool specific grasping movements
(Grezes & Decety, 2001a). Lesion data also suggest that this area is responsible for finger
movement coordination associated with grasping and manipulating objects (Binkofski et al.,
1998).
With respect to the motor skills required for tool manipulation, Frey (2008) combined the
results from apraxia studies and neuroimaging studies, and concluded that retrieval and planning
of these skills involves a network of cortical areas in the left hemisphere, situated in the parietal,
prefrontal, and posterior temporal cortices. Surprisingly, the left hemisphere dominance was also
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observed when the actions were performed with the left hand (Moll et al., 2000). The
involvement of parietal and frontal brain areas in tool related motor responses can be understood
in the light of a proposal made by Heilman, Rothi, and Valenstein (1982). According to this
proposal, parietal sites store representations of skills whereas the frontal sites take part in the
retrieval of the skills during performance. Activation of the left PPC (posterior parietal cortex)
during pantomiming and imagery corroborates the proposal.
In summary, it can be concluded that tool use, as a behavior that is specially advanced
and sophisticated in humans compared to other species (see Boesch and Boesch (1990) for
chimpanzees, and Hunt and Gray (2004) for crows), involves various components that are
lateralized to the left hemisphere.
Interestingly, to our knowledge no one has yet investigated whether the left lateralization
of tool knowledge can also be confirmed in a behavioral study. Neuroimaging techniques, such
as fMRI, are good methods to establish the lateralization of cognitive functions. However, they
also tend to be rather resource intensive, meaning that they are less suited for research on large
groups or for pilot testing. Before the introduction of functional neuroimaging, barely two
decades ago, the common practice was to test the laterality of cognitive functions with
behavioral methods, such as visual half field (VHF) experiments for visual stimuli and dichotic
listening tasks for auditory stimuli (Bradshaw & Nettleton, 1983; Bryden, 1982). So, for tool
identification researchers would have used a VHF experiment and gauged the laterality of the
function by comparing the performance of right handers to stimuli presented in the left visual
field (LVF) with stimuli presented in the right visual field (RVF).
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The VHF technique rests on assumption that a visual stimulus can be processed
more efficiently if it is projected directly to the specialized hemisphere than if it is initially sent
to the nonspecialized hemisphere. Due to the crossing of nasal fibers in the optic chiasm, stimuli
in RVF are projected directly to the left hemisphere, whereas stimuli in LVF are projected to the
right hemisphere. Therefore, the expectation is that tool identification would be better in RVF
than in LVF, given the left hemisphere dominance for this function.
The reason why researchers in tool use may not have thought of the VHF task is that it
has been criticized as a good measure of laterality in the past decades. For instance, Voyer
(1998) showed that the laterality index on the basis of a VHF task has a low reliability (r = 0.56
for verbal tasks and r = 0.28 for nonverbal tasks). Another problem is that VHF tasks usually
reveal some 30% LVF advantage for verbal stimuli in right handers, although it is well
established that right hemisphere dominance in these people is below 5% (Knecht et al., 2000).
Furthermore, there is a low correlation between the laterality estimates of the same participants
based on a VHF task and those based on a dichotic listening task (Kim, 1997). All these findings
have questioned the usefulness of the VHF task and suggested that task related variables may be
more important in the outcome than the fact that the two VHFs have direct access to different
hemispheres.
Hunter and Brysbaert (2008) recently reviewed the task variables that may play a role in
VHF asymmetries and made eight recommendations for the proper implementation of a VHF
experiment. First, because of the low reliability of the VHF asymmetries, experimenters must
present a reasonably large number of trials to the participants. How many depends on the
conclusions one wants to draw from the study. If the goal is to make an individual assessment of
the participants, then more trials will be required than when the goal is to draw conclusions on
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the basis of the grouped data. Second, the stimuli in LVF and RVF must be matched. Otherwise,
the VHF asymmetry may be influenced by the stimuli presented in both VHFs. Third; bilateral
presentation is to be preferred. In this technique, two stimuli are presented simultaneously in
LVF and RVF and a central arrow indicates to which stimulus the participant must respond. This
procedure creates competition between the left and the right hemisphere and also seems to be
better to counteract attentional biases to LVF or RVF (e.g., as a result of the reading direction).
Fourth, the stimuli must be clearly visible, despite the fact that stimulus presentation is limited in
the VHF paradigm (because the participants must not be able to make eye movements to the
stimulus). Fifth, some fixation control must be exerted, to make sure that the stimulus is
presented in the intended hemisphere. If fixation control entirely depends on instructions, there is
no way to exclude participants who fail to follow the instructions. Sixth, the task must be a valid
measure of the function one wants to assess (e.g., a naming task must be used if the experimenter
wants to measure the laterality of speech). Seventh, the stimuli must be optimized to exclude
confounds (i.e., the stimuli should be carefully selected to minimize irrelevant effects due to
factors such as stimulus clarity, stimulus roundedness, stimulus orientation, and so on). And
finally, low correlations are to be expected if the range of participants is limited. The main
outcome of a VHF task (or any other laterality task) is to determine whether a person is left or
right dominant, not whether there are consistent differences in the degree of left dominance.
So, if only left hemisphere dominant participants are tested (who all show the expected
RVF advantage), one is bound to find low reliability data and low correlations with other tasks
(because the differences in RVF advantage between the participants are largely due to noise). If
one wants to test the validity of a VHFtask, one must compare left dominant with right dominant
participants and check whether the VHF asymmetries of both groups are indeed reversed.
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Using these criteria, Hunter and Brysbaert (2008) were able to show that a word naming
VHF task with short word stimuli is a valid measure of speech dominance, as assessed with
fMRI and functional transcranial Doppler sonography. In the present study, we investigate
whether a good VHF task is also able to reveal the left hemisphere dominance for tool
recognition. To further make sure that the VHF asymmetry for tool recognition is related to the
task and not to a general attention bias towards RVF (e.g., because of the left–right reading
direction of the participants), we additionally presented a task, object recognition, for which no
RVF advantage is expected. According to some authors no consistent VHF asymmetries are
expected for object recognition (for a review, see Biederman & Cooper, 1991). Others have
reported a tendency towards a LVF advantage, in particular when the objects are presented in a
non canonical view (McAuliffe & Knowlton, 2001).
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Objects
Non-Objects
Figure 1: Examples of stimuli used in the Object Recognition Experiment
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(A)
(B)
Figure 2: Examples of stimuli used in the tool recognition experiment. (A) Tools & (B) Non-
Tools.
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Method
Participants
The participants were 20 students from Ghent University. There were 14 females and 6
males; all participants were right-handed with a mean laterality index of 73.9 on the Edinburgh
Handedness Inventory. The experiment took 1.5 h in total. Participants were paid 12€.
Stimuli
For the object recognition task, we took line-drawings of 40 objects and 40 non-objects
from the Line Drawing Library developed at the Laboratory of Experimental Psychology,
University of Leuven, Belgium (van Diepen & De Graef, 1994). The objects included in the list
were those encountered in daily life, such as ball, clock, cup, etc. The non-objects were
unnamable, made up images that matched the objects in general shape. The upper panel of Fig. 1
shows three examples of objects used and the lower panel shows three examples of non-objects
used in the object recognition task.
For the tool recognition task, we used line drawings of 30 tools and 30 non-tools from the
IPNP Pictures database (Snodgrass & Vanderwart, 1980). The tools were familiar in daily life,
such as hammer, saw, screwdriver etc. The objects included familiar objects, such as bottle,
candle, shoe, etc. Care was taken to ensure that the tool and non-tool pictures were perceptually
similar (which imposed a strong limitation on the number of pictures that could be used), so that
the tools on average did not have a different shape from the other objects (tools in general tend to
be elongated and are often drawn with the right slant typical for right-hand use). The upper panel
of Fig. 2 shows three examples of tools used and the lower panel shows three examples of non
tools used as control objects.
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It was not possible to use the same pictures for object/non-object and tool/non-tool tasks,
because the Leuven database did not contain enough pictures of tools, whereas the IPNP
database did not include pictures of non-objects. This was a limitation, but not a real problem
because both tasks were run in separate blocks, and we did not expect carry over effects from
one type of drawing to the other. All pictures were sized to 150 × 150 pixels.
Procedure
Participants started by completing the Edinburgh Handedness inventory. They were then
seated in front of a 17” computer screen at a distance of 80 cm. Before the start of each
experiment the participants were familiarized with the pictures that would be presented, by
giving a tachistoscopic presentation of the stimuli (with the same presentation duration as in the
real experiment).
The sequence of presentations was as follows. First there was a blank screen for 1000 ms.
This was followed by a fixation cross (sized 1◦ of visual angle) in the center of the screen for
300 ms. The fixation cross was then replaced by a slide which included an ARROW of 1◦ of
visual angle in the center pointing to the left or to the right, together with a picture in LVF and a
picture in RVF (extending from 3◦ to 7◦). The duration of the slide was 200 ms. Research by
Walker and McSorley (2006) indicated that participants are not able to initiate an eye movement
within 200 ms when they first have to pay attention to a stimulus at the fixation location. The
pictures in LVF and RVF could depict an object or a non-object in the object recognition task,
and a tool or a non-tool in the tool recognition task. The participants were instructed to direct
their attention to the picture to which the arrow pointed, and to ignore the other picture. If the
picture was an object (or a tool) they had to press with their left and right index fingers
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simultaneously; if the picture represented a non-object (or non-tool) they had to press with their
left and right middle fingers. Responses were registered with an external four button box,
connected to the USB port of the computer. We used bimanual responses to avoid the stimulus–
response compatibility effect (i.e., the fact that responses with the right hand are faster to stimuli
in RVF than LVF, whereas the reverse is true for responses with the left hand). Reaction times
were calculated based on the first key press registered.
Eight types of trials were defined, depending on the VHF the participant had to attend to
(LVF or RVF), whether this VHF contained a picture of an object/tool or non-object/non-tool,
and whether the opposite VHF contained a picture of the same category (e.g., tool–tool) or of the
other category (e.g., tool–nontool). This ensured that over trials the same information was
presented in LVF and RVF.
Each task (object decision, tool decision) started with a practice session of 48 trials,
before the main experimental block was administered. The experimental block was divided into
2 parts having 240 trials each. There was a break of 2–3 min between the two parts. The object
recognition task always preceded the tool recognition task, to avoid participants from recoding
stimuli of the object recognition task as tools. Reaction times of the correct responses and
accuracies were the dependent variables.
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Table 1: Showing comparative RT (percentage error) analysis for the two tasks.
Fig 3: Showing significant RVF facilitation for tools, while no such facilitation is seen for
objects.
LVF RVF
Object Recognition YES NO YES NO
Compatible Distractor 430 (17.5%) 460 (10.8%) 420 (17.6%) 470 (9.7%)
Incompatible Distractor 414 (18.1%) 487 (12.9%) 417 (18.9%) 503 (12.9%)
Tool Recognition
Compatible Distractor 469 (17.5%) 467 (12.1%) 456 (16.2%) 460 (10.7%)
Incompatible Distractor 485 (21.2%) 508 (15.1%) 458 (18.7%) 484 (14.4%)
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Results
First, we compared the two tasks with a 2 ×2 × 2 ×2 omnibus ANOVA, containing
task (object/tool), VHF (LVF/RVF), response (yes/no), and compatibility of the distracter picture
(compatible/ incompatible) as independent variables (Table 1). Distracter compatibility refers to
the arrangement of the pictures in the two visual half fields: A compatible condition is a
condition, in which the pictures of both visual half fields belong to the same category (tool, non-
tool, object, non-object), whereas an incompatible condition refers to a situation in which the
pictures of the visual half fields belong to opposite categories. For the RT data, this resulted in a
significant main effect of task type (object recognition = 451 ms, tool recognition = 474 ms; F
(1, 19) = 5.117, p < 0.05), response type (yes = 444 ms, no = 481 ms; F (1, 19) = 17.589, p <
0.001), and distracter compatibility (compatible = 455 ms, incompatible = 470 ms; F (1, 19) =
43.303, p <0.001). The main effect of VHF was not significant (LVF = 465 ms, RVF = 459 ms;
F (1, 19) = 5.117, p = 0.22).
Most importantly, as predicted, there was a significant interaction between task and VHF
(F (1, 19) = 10.231, p < 0.001), which is shown in Fig. 3. VHF was also involved in a significant
three-way interaction with Task and distracter compatibility (F (1, 19) = 7.685, p < 0.05). The
interpretation of both effects will be clearer when we have a look at the individual tasks.
Finally, there was a significant interaction between response type and distracter
compatibility (F (1, 19) = 24.415, p < 0.001). The compatibility effect was only observed for the
noresponses (t (19) = 56.35, p < 0.001). There was no difference between compatible and
incompatible trials in the yes trials (t (19) = 0.576, p = 0.97). The same omnibus 2 ×2 × 2 × 2
ANOVA on the percentages of error only revealed significant main effects of response type (Yes
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= 18.2, no = 12.4; F (1, 19) = 8.622, p < 0.01) and distracter compatibility (compatible = 14.1,
incompatible = 16.6; F (1, 19) = 12.528, p < 0.01).
We ran separate 2 × 2 × 2 ANOVAs for the two different tasks, to separately
understand the effects of the three variables (visual half field, response type, and distracter
compatibility). For the RTs in the object recognition task, there was no significant effect of
Visual Field (F (1, 19) = 0.616, n.s.), but there were significant effects of response type (F (1,
19) = 33.700, p < 0.01) and distracter compatibility (F (1, 19) = 8.998, p < 0.01). In addition,
there were significant interactions between VHF and Response type (F (1, 19) = 4.510, p < 0.05)
and between response type and distracter compatibility (F (1, 19) = 36.172, p < 0.01). The latter
has been discussed in the omnibus analysis; the former is new and is due to the fact that no
responses were 13 ms faster in LVF than RVF (t (19) = 3.379, p > 0.05), whereas RTs were 3 ms
faster in RVF than LVF for yes responses (t (19) = 0.868, p > 0.05). The 2 × 2 × 2 ANOVA on
the percentages of errors only revealed significant main effects of Response type (F (1, 19) =
15.338, p < 0.01) and distracter compatibility (F (1, 19) = 4.916, p < 0.05). The three- way
interaction was not significant (F (1, 19) = 0.262, p > 0.05).
The 2 ×2 ×2 ANOVA of the RTs in the tool recognition task returned the predicted
effect of VHF (F (1, 19) = 8.477, p < 0.01) with faster responses in RVF (465 ms) than in LVF
(483 ms). There was no significant difference between response types (F (1, 19) = 1.88, p >
0.05), but participants were faster in distracter compatible trials than in distracter incompatible
trials (F (1, 19) = 30.448, p < 0.01). VHF was further involved in a significant interaction with
distracter compatibility (F (1, 19) = 4.848, p < 0.05), because the RVF advantage was smaller
with compatible distracters (10 ms) than with incompatible distracters (25 ms). Finally, as in all
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the previous analyses there was a significant interaction between Response type and distracter
compatibility (F (1, 19) = 7.478, p < 0.05). The three-way interaction was not significant (F (1,
19) = 0.019, p > 0.05). The same ANOVA on the percentages of error only revealed a significant
main effect of Compatibility (F (1, 19) = 12.564, p < 0.05). The effects of VHF and response
type failed to reach significance in this analysis (VHF: F (1, 19) = 2.445, p > 0.05; response
type: F (1, 19) = 3.534, p > 0.05).
As the participants were significantly faster on the object/non-object decision task than
on the tool/non-tool decision task (object recognition = 451 ms, tool recognition = 474 ms; F (1,
19) = 5.117, p < 0.05); we further checked whether task difficulty played a role in the LVF
advantage obtained in the tool/non-tool decision task. The reaction times of each participant in
the tool/non-tool decision task were split into a faster and a slower half and were analyzed with
the same 2 × 2 × 2 ANOVA having VHF, response (yes/no) and compatibility as factors. The
analyses revealed that the VHF advantage was the same in the fast half of the trials (RVF = 365
ms, LVF = 382 ms; F (1, 19) = 18.910, p < 0.01) as in the slow half (RVF = 563 ms, LVF = 581
ms; F (1, 19) = 5.114, p < 0.05). The same analysis for the object recognition task revealed that
the VHF asymmetry was absent both in the fast trials (LVF = 352 ms, RVF = 356 ms) and in the
slow trials (LVF = 543 ms, RVF = 548 ms). Given this pattern of results, it is unlikely that task
difficulty was involved in the LVF advantage for tool recognition.
Discussion
In this article we examined whether we could find evidence for left hemisphere
lateralization of tool recognition with the use of a behavioral VHF experiment. As reviewed in
the Introduction, left hemisphere lateralization of tool knowledge has been well established on
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the basis of neuropsychological and brain imaging data (Frey, 2008; Frey, Funnel, Gerry and
Gazzaniga, 2005; Goldenberg & Spatt, 2009; JohnsonFrey, 2004; Kallenbach et al., 2003; Lewis,
2006; Osiurak et al., 2009; Randerath et al., 2010). Showing a similar effect in a VHF task would
not only make a new lateralized function available for behavioral research with healthy
participants; it would also provide a further validation of the VHF task, which has been
questioned.
Our results showed that the expected RVF advantage for tool recognition is observed, if a
basic protocol is used to make sure that participants perform the task under optimal conditions.
In addition, the same advantage was not observed in a very similar task (object recognition) for
which no VHF asymmetry was expected (Biederman & Cooper, 1991). These findings support
Hunter and Brysbaert’s (2008) conclusion that the VHF paradigm is a valid paradigm when used
properly and that researchers can make use of the VHF task to examine the laterality of cognitive
visual functions.
The finding of no VHF asymmetry in the object recognition task is further interesting,
because it deviates from the object naming task, which induces a RVF/left hemisphere advantage
similar to word naming (Hunter & Brysbaert, 2008). In object naming, however, a small set of 5
pictures is shown repeatedly and participants have to name the picture as fast as possible. In this
task, the bottleneck is not to identify the picture but to pronounce the correct name (which is a
left hemisphere function). The difference between the object naming task and the object
recognition task clearly shows the importance of carefully selecting the proper VHF task for the
function one wants to study.
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The finding of no VHF difference in the object naming task is in line with the existing
literature (Biederman & Cooper, 1991). In one of the more recent studies, McAuliffe and
Knowlton (2001) reported a small (8 ms) LVF/RH advantage by manipulating SOA and object
orientation. As we did not change object orientation or manipulate SOA, we did not expect to
trigger differences in perceptual processing between the hemispheres. At the same time, we saw
some evidence for a LVF advantage on the no responses, against no VHF difference for the yes
responses, leading to a significant interaction between VHF and response type in the object
recognition task. It is not clear whether much attention should be given to this finding until we
know more about its robustness. Possible reasons why right handed participants may find it
easier to give no responses to stimuli in LVF could be related to right hemisphere superiority at
processing non familiar shapes or to the fact that participants spontaneously tend to associate no
responses with “left” and yes responses with “right” (Nuerk, Iversen, & Willmes, 2004).
The fact that we found different results for tool/non-tool decisions and object–non-object
decision further confirms that tools form a special category of objects strongly related to specific
movements (Grafton, Fadiga, Arbib, & Rizzolatti, 1997). Most of the tools in our stimuli pool
(razor, axe, hammer) belonged to the class of manipulable objects, which are associated with
discrete activations in left posterior parietal cortex. Tools (as a class of manipulable objects)
encourage automatic engagement of mechanisms involved in the planning of grasping and
reaching movements, activating the left pre-motor cortex during naming/observation (Frey,
2008). It has been proposed that tools when viewed can be processed not only for identity but
also for how they can be used as opposed to other classes of objects (Creem Regehr & Lee,
2005). This proposal hints to the fact that viewing pictures of tools in comparison to objects is
more likely to trigger activations in the brain regions responsible for simulating motor actions
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closely associated with them even when the actions are not overtly performed (Tucker & Ellis,
1998). As these regions largely lie in the left hemisphere (Frey, 2008) a clear left
hemisphere/right visual field advantage is a logical expectation, which was confirmed by our
results.
A slight complication is that the tool recognition VHF task contains 8 types of trials,
rather than the two conditions of neuroimaging studies. The participants not only respond to
tools in LVF and RVF, but in addition they have to respond to stimuli that evoke a no response,
and they are confronted with compatible or incompatible distracters. Both variables have
significant effects: Participants are faster on yes trials than on no trials, and they are faster on
trials with compatible distracters than on trials with incompatible distracters. Luckily, these
variables do not interact with the RVF advantage to such an extent that they wipe out the main
effect of VHF. In addition, later experiments can zoom in on the effects due to the distracter, to
get a clearer image of the inter-hemispheric dynamics in the tool recognition task. Given that the
distracters influence the processing of the targets, there is crosstalk involved, the origin of which
will be interesting to flesh out (see, e.g., Ratinckx & Brysbaert, 2002, for a similar study in
number processing).
All in all, the present study replicates earlier evidence for the left hemisphere
lateralization of tool use by finding a clear RVF advantage of 17 ms for tool recognition. This is
an important step towards establishing valid behavioral estimates of cerebral asymmetry. The
visual half field task as operationalized here is a viable means to assess the laterality of cognitive
functions, the more so because participants only showed the RVF advantage for the tool
recognition task and not for the object recognition task, where no VHF asymmetry was
predicted. The ease with which VHF studies can be run means that this is a more versatile
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technique to examine the details of tool lateralization. Above, we discussed the possibility to
investigate the inter-hemispheric dynamics. Other topics to address are the extent to which the
effect depends on the type of tools (e.g., manipulable or not), and whether the VHF advantage is
fundamental enough to be observed in a tool/nonobject decision task, or whether in that case
tools are processed like other objects. Further questions are how tool use is lateralized in left-
handed individuals, how important the orientation of the tool is (e.g., typical for left or right hand
use) and whether this interacts with the handedness of the participant. Finally, studies with
atypically lateralized individuals can be expected to yield interesting results, as it would be
fascinating to investigate whether tool representations follow language representations and shift
to the right hemisphere in right dominant individuals. The present study calls for a greater
exchange between behavioral and neuroimaging research by providing a behavioral paradigm
that can be used both as a precursor to brain research and in combination with brain research
(e.g., to see to what extent brain activity differs when the stimulus is presented in LVF or RVF).
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References
Ambrose, S. H. (2001). Paleolithic technology and human evolution. Science, 291, 1748–1753.
Beauchamp, M., Lee, K., Haxby, J., & Martin, A. (2002). Parallel visual motion processing
streams for manipulable objects and human movements. Neuron, 34, 149–159.
Biederman, I., & Cooper, E. E. (1991). Object recognition and laterality: Null effects.
Neuropsychologia, 29(7), 685–694.
Binkofski, F., Dohle, C., Posse, S., Stephan, K. M., Hefter, H., Seitz, R. J., et al. (1998). Human
anterior intraparietal area subserves prehension: A combined lesion and functional MRI
activation study. Neurology, 50, 1253–1259.
Boesch, C., & Boesch, H. (1990). Tool use and tool making in wild chimpanzees. Folia
Primatologica, 54, 86–99.
Bradshaw, J. L., & Nettleton, N. C. (1983). Human cerebral asymmetry. New Jersey: Prentice
Hall.
Bryden, M. P. (1982). Laterality: Functional asymmetry in the intact brain. New York:
Academic Press.
Buccino, G., Binkofski, F., Fink, G. R., Fadiga, L., Fogassi, L., Gallese, V., et al. (2001). Action
observation activates premotor and parietal areas in a somatotopic anner: An fMRI study.
European Journal of Neuroscience, 13, 400–404.
Buxbaum, L. J., Schwartz, M. F., & Carew, T. G. (1997). The role of semantic memory in object
use. Cognitive Neuropsychology, 14, 219–254.
Buxbaum, L. J., Veramonti, T., & Schwartz, M. F. (2000). Function and manipulation tool
knowledge in apraxia: Knowing “what for” but not “how”. Neurocase, 6, 83–97.
Chao, L. L., Haxby, J. V., & Martin, A. (1999). Attribute based neural substrates in temporal
cortex for perceiving and knowing about objects. Nature Neuroscience, 2, 913–919.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 104
Chao, L. L., & Martin, A. (2000). Representation of manipulable manmade objects in the dorsal
stream. Neuroimage, 12, 478–484.
Choi, S. H., Na, D. L., Kang, E., Lee, K. M., Lee, S. W., & Na, D. G. (2001). Functional
magnetic resonance imaging during pantomiming tool use gestures. Experimental Brain
Research, 139, 311–317.
Creem Regehr, S. H., & Lee, J. N. (2005). Neural representations of graspable objects: Are tools
special? Brain Research. Cognitive Brain Research, 22, 457–469.
Decety, J., Perani, D., Jeannerod, M., Bettinardi, V., Tadary, B., Woods, R., et al. (1994).
Mapping motor representations with positron emission tomography. Nature, 371, 600–
602.
Frey, S. H. (2008). Tool use, communicative gesture and cerebral asymmetries in the modern
human brain. Philosophical Transactions of the Royal Society of London Series B, 363,
1951–1957.
Frey, S. H., Funnell, M. G., Gerry, V. E., & Gazzaniga, M. S. (2005). A dissociation between the
representation of tool use skills and hand dominance: Insights from left and right handed
callosotomy patients. Journal of Cognitive Neuroscience, 17(2), 262–272.
Fridman, E. A., Immisch, I., Hanakawa, T., Bohlhalter, S., Waldvogel, D., Kansaku, K., et al.
(2006). The role of the dorsal stream for gesture production. Neuroimage, 29, 417–428.
Goldenberg, G., & Spatt, J. (2009). The neural basis of tool use. Brain, 132, 1645–1655. Grafton,
S. T., Fagg, A. H., Woods, R. P., & Arbib, M. A. (1996). Functional anatomy of pointing
and grasping in humans. Cerebral Cortex, 6, 226–237.
Grafton, S. T., Fadiga, L., Arbib, M. A., & Rizzolatti, G. (1997). Premotor cortex activation
during observation and naming of familiar tools. Neuroimage, 6, 231–236.
Grezes, J., & Decety, J. (2001). Does visual perception of objects afford action? Evidence from a
neuroimaging study. Neuropsychologia, 40, 212–222.
Chapter 2|A right visual field advantage for tool recognition
P.| 105
Heilman, K. M., Rothi, L. J., & Valenstein, E. (1982). Two forms of ideomotor apraxia.
Neurology, 32, 342–346.
Hunt, G. R., & Gray, R. D. (2004). Direct observations of pandanus tool manufacture and use by
a New Caledonian crow (Corvus moneduloides). Animal Cognition, 7, 114–120.
Hunter, Z. R., & Brysbaert, M. (2008). Visual half-field experiments are a good measure of
cerebral language dominance if used properly: Evidence from fMRI. Neuropsychologia,
46, 316–325.
Johnson Frey, S. H. (2004). The neural bases of complex tool use in humans. Trends in
Cognitive Sciences, 8, 71–78.
Johnson Frey, S. H., Newman Norlund, R., & Grafton, S. T. (2005). A distributed left
hemisphere network active during planning of everyday tool use skills. Cerebral Cortex,
15, 681–695.
Kallenbach, M. L., Brett, M., & Patterson, K. (2003). Actions speak louder than functions: The
importance of manipulability and action in tool representation. Journal of Cognitive
Neuroscience, 15(1), 30–46.
Kim, H. (1997). Are subjects’ perceptual asymmetries on auditory and visual language tasks
correlated? A meta analysis. Brain and Language, 58, 61–69.
Knecht, S., Drager, B., Deppe, M., Bobe, L., Lohmann, H., Floel, A., et al. (2000). Handedness
and hemispheric language dominance in humans. Brain, 123, 2512–2518.
Lewis, J. W. (2006). Cortical networks related to human use of tools. Neuroscientist, 12, 211–
231.
Martin, A., Wiggs, C. L., Ungerleider, L. G., & Haxby, J. V. (1996). Neural correlates of
category specific knowledge. Nature, 379, 649–652.
McAuliffe, S. P., & Knowlton, B. J. (2001). Hemispheric differences in object identification.
Brain and Cognition, 45, 119–128.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 106
Moll, J., de OliveiraSousa, R., Passman, L. J., Cunha, F. C., SouzaLima, F., & Andreiuolo, P. A.
(2000). Functional MRI correlates of real and imagined tool use pantomimes. Neurology,
54, 1331–1336.
Nuerk, H.C., Iversen, W., & Willmes, K. (2004). Notational modulation of the SNARC and the
MARC, linguistic markedness of response codes effect. The Quarterly Journal of
Experimental Psychology, 57A, 835–863.
Osiurak, F., Jarry, C., Allain, P., Aubin, Ghisliaine, Etcharry Bouyx, F., et al. (2009). Unusual
use of objects after unilateral brain damage. The technical reasoning model. Cortex, 45,
769–783.
Perani, D., Schnur, T., Tettamanti, M., Gorno Tempini, M., Cappa, S. F., & Fazio, F. (1999).
Word and picture matching: A PET study of semantic category effects.
Neuropsychologia, 37, 293–306.
Randerath, J., Goldenberg, G., Spijkers, W., Li, Y., & Hermsdorfer, J. (2010). Different left
brain regions are essential for grasping a tool compared with its subsequent use.
NeuroImage, 53, 173–180.
Rumiati, R. I., Weiss, P. H., Shallice, T., Ottoboni, G., Noth, J., Zilles, K., et al. (2004). Neural
basis of pantomiming the use of visually presented objects. NeuroImage, 21, 1224–1231.
Ratinckx, E., & Brysbaert, M. (2002). Inter-hemispheric stroop like interference in number
comparison: Evidence for strong inter-hemispheric integration of semantic number
information. Neuropsychology, 16(2), 217–229.
Snodgrass, J. G., & Vanderwart, M. (1980). A Standardized set of 260 pictures: Norms for name
agreement, image agreement, familiarity and visual complexity. Journal of Experimental
Psychology: Human Learning and Memory, 6(2), 174–215.
Tucker, M., & Ellis, R. (1998). On the relations between seen objects and components of
potential actions. Journal of Experimental Psychology: Human Perception and
Performance, 24(3), 830–846.
Chapter 2|A right visual field advantage for tool recognition
P.| 107
van Diepen, P. M. J., & De Graef, P. (1994). Line-drawing library and software toolbox (Psych.
Rep. No. 165). In Laboratory of experimental psychology. Belgium: University of
Leuven.
Voyer, D. (1998). On the reliability and validity of noninvasive laterality measures. Brain and
Cognition, 36, 209–236.
Walker, R., & McSorley, E. (2006). The parallel programming of voluntary and reflexive
saccades. Vision Research, 26, 2082–2093.
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Chapter 3: A validated set of tool pictures with
matched objects and non-objects for laterality
research
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Chapter 3: A validated set of tool pictures with matched objects and
non-objects for laterality research
Neuropsychological and neuroimaging research has established that knowledge related
to tool use and tool recognition is lateralized to the left cerebral hemisphere. Recently,
behavioral studies with the visual half field technique have confirmed the lateralization (Verma
& Brysbaert, 2011; Garcea, Almeida & Mahon, 2012). A limitation of this research was that
different sets of stimuli had to be used for the comparison of tools to other objects, and objects to
non-objects. Therefore, we developed a new set of stimuli containing matched triplets of tools,
other objects, and non-objects. With the new stimulus set we successfully replicated the findings
of no visual field advantage for objects in an object recognition task, combined with a significant
right visual field advantage for tools in a tool recognition task. The set of stimuli is available as
supplementary materials to this article.
Introduction
Manufacturing and using tools have been considered important milestones in the
evolution of the human brain and date back at least 2.5 million years (Ambrose, 2001).
Although tool use has been considered as a typically human skill (Oakley, 1956), there is
evidence that many species ranging from birds (Lefebvre, Nicolakakis, & Boire, 2002) to
elephants (Hart, Hart, McCoy & Sarath, 2001), crows (Hunt, 1996), orangutans (van
This chapter has been accepted for publication as Verma, A., & Brysbaert, M. (in press). A validated set of tool
pictures with matched objects and non-objects for laterality research. Laterality.
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Schaik, Ancrenaz, Borgen, Galdikas, Knott, Singleton, Suzuki, Utami & Merill, 2003), capuchin
monkeys (Westergaard and Fragaszy, 1987), dolphins (Krutzen, Mann, Heithaus, Connor, Beider
& Sherwin, 2005) and chimpanzees (Boesch and Boesch, 1990) engage in various forms of tool
use.
Several definitions have been offered to differentiate “tools” from other objects and “tool
use” from other types of behavior. For example: an early definition of tool use offered by Jane
Goodall describes tool use as, “the use of an external object as a functional extension of the
mouth or beak, hand or claw, in the attainment of an immediate goal” (van Lawick-Goodall,
1970, page 195). Alcock (1972, page 464) defines tool use as “the manipulation of an inanimate
object, not internally manufactured, with the effect of improving an animal’s efficiency in
altering the form or position of some separate object”. Finally, Beck (1980, page 10) defines tool
use as “the external employment of an unattached environmental object to alter more efficiently
the form, position or condition of another object, another organism, or the user itself when the
user holds or carries the tool during or just prior to use and is responsible for the proper and
effective orientation of the tool”. However, Preston (1998) observes that various definitions of
tool use basically attempt to formalize for scientific purposes a “folk category” of tool use which
underwrites the definitions of “tools” found in dictionaries, and hence are simply ‘inadequate’.
Indeed, many examples of animal and human behavior can be cited that may not be covered
within these definitions.
To paraphrase the various possible definitions of tools and tool use that differ in their
scope and usefulness (read Preston, (1998) & Amant & Horton, (2008) for a detailed discussion),
a “tool” has to be an “external”, “inanimate” object employed by a user for a “goal-directed”
action. For the purpose of the current study we followed a definition of tools proposed by Frey
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(2007), who defines “tools as manipulable objects that are used to transform an actor’s motor
output into predictable mechanical actions in order to attain specific goals”. Accordingly, all
objects presented as tools in our study were man-made, hand manipulable and had typical and
well-established uses. For example: a hammer is typically associated with driving nails. Hence,
in the current study the tools are defined in “typical” contexts so that we can interpret the
consequent findings in a constrained frame of reference and avoid ambiguity.
Even though a variety of species have been reported to be engaged in tool use, the
understanding and use of tools in humans goes far beyond the animal skills. Evidence indicates
that humans possess specialized neuronal mechanisms allowing them to understand the
functional properties of tools, both simple and complex (Frey, 2007). Not only does the human
brain have dedicated regions for tool use, these regions are lateralized to the left hemisphere,
which is also the dominant hemisphere for language and related functions (Lewis, 2006, Frey
2004). Indeed, a lot of evidence from clinical studies indicates a major role of the left hemisphere
of the brain in accessing and processing the knowledge of tools and tool use. For instance,
Hermsdorfer, Li, Randerath, Goldenberg & Johanssen (2012) found that patients with left
hemisphere stroke exhibited reduced hand rotation at the bowl and the plate in pantomiming as
well as actual use. Randerath, Goldenberg, Spijkers, Li & Hermsdorfer (2010) found a large area
of lesion overlap was found in the left supramarginal gyrus of patients with impaired tool use
whereas lesion overlap in the left inferior frontal gyrus and left angular gyrus for patients who
were impaired in tool grasping. Also, Goldenberg & Spatt (2009) observed that parietal lesions
involving the left supramarginal gyrus impaired tool use (both common and new) and left frontal
lesions affected tool use and tool knowledge. Further, Osiurak et al. (2009) found that left brain
damaged patients had more difficulties on the unusual use of objects when compared to healthy
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controls or right brain damaged patients. Finally, Goldenberg, Hermsdorfer, Glindemann,
Rorden, and Karnath (2007) examined 44 patients with left sided cerebrovascular accidents, and
found that lesions in the inferior frontal gyrus and adjacent portions of the insula and precentral
gyrus led to defective pantomiming ability.
Adding to the evidence from clinical studies, a large number of neuroimaging studies also
demonstrate greater involvement of left hemisphere areas in tasks related to tool knowledge and
use.
Typically, in neuroimaging research, participants are asked to pantomime specific tool
operations, and the brain activity related to these movements is compared with that of repetitive
limb movements (Choi, Na, Kang, Lee, Lee & Na, 2001), meaningful hand gestures or
meaningless hand movements (Fridman, Immisch, Hanakawa, Bohlhalter, Waldvogel, Kansaku,
Wheaton, Wu, and Hallett, 2006; Grezes & Decety, 2001). Other researchers present participants
with pictures of tools vs. pictures of humans, animals, houses, faces, or even scrambled images,
and measure the differences in brain activity (Beauchamp, Haxby & Martin, 2002; Chao, Haxby
& Martin, 1999; Chao & Martin, 2000). It has been suggested that for such comparisons it is best
to compare tools to other man-made objects, such as houses, because otherwise it is difficult to
be sure that the observed differences in brain activity are specific to tool use or could be due to
other categorical differences, such as that between man-made objects and natural, animate
organisms (Kallebach, Brett, & Patterson, 2003).
Using a variety of tasks and paradigms, neuroimaging research has uncovered a range of
left hemispheric cortical areas important for tool knowledge and tool-use behavior. For instance,
the left ventral pre-central gyrus in the frontal lobe (ventral Premotor cortex, VPMCx), the left
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Intraparietal sulcus (IPS) in the posterior parietal cortex, and the posterior middle temporal gyrus
(PMTG) either in the left hemisphere alone or bilaterally (Beauchamp et al. 2002; Chao &
Martin, 2000; Perani, Schnur, Tettamanti, Gorno Tempini, Cappa, and Fazio,. 1999) have been
linked to tool-identification. Johnson-Frey, Newman-Norlund & Grafton (2005) reported that
sites in the left inferior frontal, inferior parietal and posterior temporal cortices are involved in
planning tool use regardless of the hand used. Finally, Kroliczak & Frey (2009) provided
evidence that the left intraparietal sulcus, supramarginal gyrus, caudal superior parietal lobule
and dorsal pre-motor cortices, are engaged in planning both transitive and intransitive actions.
While multiple accounts implicate the left hemisphere superiority in tool- related
behavior, some evidence for right hemisphere contribution in tool processing has also been
reported (Frey, 2008). Specifically, Hamilton & Grafton (2008) reported that right inferior
parietal and right inferior frontal cortices area encode physical outcomes of actions in the real
world. In a similar vein, Hartmann, Goldenberg, Daumuller & Hermsdorfer (2005) reported that
right brain damaged patients had problems in keeping track of multiple step action sequences,
which might be vital for tool-use behavior. Further, while Frey (2008) demonstrates activations
in the left posterior parietal (pPar), dorsal and ventral premotor cortices along with middle
frontal gyrus and frontal and posterior temporal cortices during tool use pantomimes; he also
reports relatively smaller activations in the homologous right hemisphere sites. Also, left handed
patients have been found to show signs of apraxia following right hemisphere lesions also
(Valenstein & Heilman, 1979; Dobatao, Baron, Barriga, Pareja, Vela & Sanchez Del Rio, 2001).
Finally, left handed participants have also been reported to show greater recruitment of right
parietal, frontal and temporal cortices than right handed participants while listening to the sounds
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made by hand-held tools versus the sounds made by animals, reflecting a possible automatic
activation of praxis representations lateralized to the right hemisphere (Lewis, 2006).
Together, findings from clinical and neuroimaging research indicate that knowledge and
skills related to tools, are represented in functionally specialized networks distributed mainly but
not exclusively over the left hemisphere (Frey, 2004). Frey (2004) postulates two major
networks i.e. the conceptual network that represents tool knowledge and consists of areas
displaying activation during semantic tasks and the skill network which consists of areas
activated during retrieval of tool related skills. Major areas represented in the conceptual network
include the left and right fusiform gyri, the left middle temporal and superior temporal gyrus, the
left ventral premotor cortices, Brodmann’s Areas 44/45 (Broca’s area) and the left medial Frontal
Gyrus. The conceptual network mediates tool observation, tool naming, action word generation
and observing action goals. The skill network comprises of Brodmann’s Areas 7, 39, 40, left
medial and anterior inferior parietal sulcii, left dorsal premotor cortices and left medial frontal
gyrus. The skill network accomplishes skill representation/retrieval, reaching, grasping and
manipulation related activities (for a detailed description of the two networks, see Frey 2004).
Tool-use behavior is accomplished by coordinated functioning of the smaller modules of these
two networks, which carry out specific component functions (Frey, 2004).
To examine whether the lateralization of tool-use skills is affected by handedness, Frey,
Funnell, Gerry and Gazzaniga (2005) examined the relationship between hand dominance and
tool use skills by comparing a right-handed male and a left-handed female callosotomy patient
and found a left hemisphere advantage for pantomiming actions associated with familiar tool-
objects and pictures in both patients. Later, Frey (2008) concluded that tool-use behavior in
majority of humans is lateralized to the left hemisphere, regardless of handedness.
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Although tool-use lateralization appears to be unrelated to handedness, tool-use related
behavior appears to be co-lateralized along with the linguistic capabilities of individuals.
Recently, Vingerhoets, Alderweireldt, Vandemaele, Cai, Van der Haegen, Brysbaert, and Achten
(2013) compared a group of typically lateralized individuals with left hemisphere speech
dominance, to a group of atypically lateralized individuals with right hemisphere speech
dominance (as assessed with fMRI) and found that the brain areas involved in tool pantomiming
were lateralized to the same hemisphere as language production, regardless of handedness.
Additional proof was provided by Uomini & Meyer (2013), who demonstrated with fTCD that
acheulean stone tool production and cued word generation caused almost identical cerebral blood
flow lateralization in their participants; and concluded that stone tool making and language are
served by common neural substrates.
Co-lateralization of tool-making or tool-use along with the linguistic capabilities of
humans has been viewed as a significant clue to the co-evolution of both these behaviors in
humans (Frey, 2008). Several authors (Corballis, 2009; Corballis, 2010; Corballis, Badzakova-
Trajkov & Haberling, 2012; Stout & Chaminade, 2012) have explored hypotheses that propose
that language evolved as a result of advances in manual praxis. More recently, it has been
proposed that the human brain is endowed with a system of mirror neurons for observing and
matching actions, which might be homologous to the macaque mirror neuron system (Rizollatti,
2005; Rizzollatti, Fogasi & Gallese, 2001). Further, it has been argued that this mirror system
has aided the evolution of manual gestures (for e.g. grasping) into meaningful communicative
symbols (akin to modern day sign-language) and later into full fledged language articulated
using the vocal tracts in humans (Rizzollatti & Arbib, 1998; Arbib, 2002; Corballis, 2009, 2010).
Researchers have also linked the incidence of population level right-handedness in humans and
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primates to the evolving culture of tool use that posed demands of manual dexterity both in tool
production and manipulation (Corballis, 2009; Steele & Uomini, 2009). However, some authors
are still looking for alternative explanations for the shared neural substrates of tool and language
functions and even their proximity on the evolutionary time-scale (Stout & Chaminade, 2012).
Finally, the mirror system hypothesis and its implications for co-evolution of language along
with tool-use has been a topic of much speculation in the recent years and provides ample reason
for researchers to engage with research both on tool-use and language. Apart from a vast array of
clinical and neuroimaging research the hemispheric dominance for tool use has also been
examined in behavioral studies. Verma & Brysbaert (2011) used the visual half-field (VHF)
paradigm, in which stimuli are presented to the left and to the right of the fixation point and
participants have to respond to the stimuli. The authors found that while there was no visual field
difference for object recognition, a significant right visual field (RVF) advantage was observed
for tools in the tool recognition task, in line with the left hemisphere dominance for tool
processing. Garcea, Almeida & Mahon (2012) used a lateralized masked priming paradigm to
test for a visual half field asymmetry in tool processing. Using tools and animals as target stimuli
and identical or scrambled versions of the targets as primes, they reported that there was a RVF
advantage in priming effects for tool targets but not for animal targets.
Verma and Brysbaert (2011) argued that the strongest evidence for laterality of tool use
in VHF studies is obtained when a tool recognition task is combined with an object recognition
task. The prediction then is that a RVF advantage will be observed for tool recognition, together
with no VHF advantage for object recognition. This pattern of results rules out the possibility
that the RVF advantage for tool recognition is confounded by an uncontrolled variable (e.g., in
the display of stimuli, in the participants’ attention allocation, or in the fixation of the central
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stimulus). A problem for the approach, however, was that it was impossible to find matched
pictures of tools, non-tool objects and non-objects from the same database. As a result, Verma &
Brysbaert (2011) had to compare pictures of tools vs. non-object tools from one source with
pictures of objects vs. non-objects from another source. A similar problem was present in
Garcea, Almedia, and Mahon (2012), who compared different sets of animals and tools as
stimulus categories. Research would be more straightforward if the same pictures could be used
in all comparisons, both as targets and primes.
To have access to better stimulus materials, we decided to compile a new set of stimuli,
which contains matched triplets of tools, non-tool objects, and non-objects, so that research can
examine object and tool recognition in the same study with the same materials. To test the
validity of the new stimulus set, we tried to replicate the findings of our previous study (Verma
& Brysbaert, 2011). As in that study, we make use of two experiments. First, an Object
Recognition VHF experiment will be run, in which participants are presented with pictures of
objects and non-objects in the left and right visual half-field. The participants have to decide
whether the designated picture displays an object or a non-object using bi-manual responses.
Second, a Tool Recognition VHF experiment will be run, in which the same pictures of objects
are presented with pictures of tools and participants have to decide whether the indicated picture
represents a tool or not. The object recognition experiment acts as a control experiment for the
tool recognition experiment. If no visual field difference is observed for the objects in the first
experiment and a significant RVF advantage for the tools in the tool recognition experiment,
then we can safely assume that the VHF advantage is due to tool-specific brain activity and not
to a confounded variable.
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Method
Participants
A group of 39 undergraduate students from Ghent University took part in both the object
decision experiment and the tool decision experiment. They were all right handed and had
normal or corrected to normal vision. The study in total took slightly over one hour and
participants were paid 12€.
Stimuli
We had three types of stimuli drawn by an artist: pictures of objects, non-objects, and
tools. We explained that it was important to have perceptually similar items that were
comparable in terms of overall shape, contour, luminance, and so on. All stimuli were digitally
generated and were similar to the line drawings of the IPNP pictures database (Snodgrass &
Vanderwart, 1980). The object pictures consisted of line-drawings of familiar objects, such as:
book, boot, maize, asparagus, carrot, palm etc. The tool pictures consisted of line-drawings of
familiar hand-manipulable tools like: knife, hammer, comb, pliers, etc. The non-object pictures
were made in such a way that they would match a pairing of an object and a tool in overall
shape, size, etc. Specifically, all figures were sized 150 x 150 pixels and presented as bitmap
images. The figures extended 3 degrees of visual angle. Figure 1 shows three examples of each
category.
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Objects
Non-Objects
Tools
Figure 1: Showing examples of Objects (Non-tools), Non-Objects and Tools. While Objects
and Non-Objects were used in Experiment 1, Objects and Tools were used in Experiment
2.
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In all, we managed to have 38 triplets of matched pictures representing an object, a tool
and a non-object (see the Appendix). All pictures were sized 150 x 150 pixels. To make sure that
our stimuli were perceived by the participants in the way we intended them, we ran two rating
studies using 6-point Likert scales: the Object Rating Scale (ORS) and the Tool Rating Scale
(TRS). In the ORS, 20 participants rated the ‘objectness’ of the object and non-object stimuli.
For each stimulus they indicated how certain they were that the stimulus represented an object;
with 1 = least certain and 6 = most certain. In the TRS, 20 new participants rated the ‘toolness’
of the tool and object stimuli, indicating with a rating from 1 to 6 how certain they were that the
stimulus in question represented a tool (1 = least certain, 6 = most certain).
Figure 2 shows the results of the rating studies. In the Object Rating Scale, 36 of the 38
non-object stimuli, scored between 1 to 3 points, while 2 scored marginally between 3 and 3.5,
indicating that all non-object stimuli were perceived as non-objects by the participants.
Furthermore, all of the 38 object stimuli scored between 4 to 6 points, indicating that they were
easily distinguishable from the non-objects. In the Tool Rating Scale, 34 out of the 38 non-tool
objects scored between 1 to 3 points, 4 objects scored between 3 and 3.5. On the other hand 30 of
the 38 tool objects scored between 4 to 6 points, while four objects scored between 3 and 4, and
four less than 3. The four pictures with tool scores lower than 3 were all musical instruments,
namely a guitar, saxophone, harp, and pipe. The 4 other objects which were not clearly
categorized were cigarettes, zipper, kettle and wristwatch. All scores can be found in the
Appendix.
We decided to use all stimuli in the validation study, so that we had data about all of
them. Of course, researchers are free to omit the less clear ones if they want to run a study
without ambiguous stimuli.
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(A) Object Rating Scale (B) Tool Rating Scale
Figure 2: Mean ratings of the pictures on the Object Rating Scale (ORS) and the Tool
Rating Scale (TRS). In the object rating scale: a score of 1-3 corresponds to non-objects
and a score of 3-6 corresponds to an object. In the tool rating scale: a score of 1-3
corresponds to an object and a score of 3-6 corresponds to a tool. See the Appendix for the
rating values of the individual stimuli.
0
1
2
3
4
5
6
Non-Objects Objects
ORS Score
0
1
2
3
4
5
6
Objects Tools
TRS Score
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Procedure
Participants were seated in front of a 17” computer screen at a distance of 80 cm. At this
distance, the pictures subtended a visual angle of 4 degrees and were presented laterally between
3-7 degrees from the fixation location. Before the start of each experiment the participants were
familiarized with the pictures that would be presented. They were given a tachistoscopic
presentation of the stimuli (with similar presentation times as in the real experiment) and asked
to name the pictures. They were corrected if needed.
For the first experiment, the pictures of the objects and the non-objects were used and
participants had to decide whether one of the two bilaterally presented stimuli was an object or a
non-object. For the second experiment, the same pictures of the objects were combined with
those of the tools, and the participants had to decide whether one of the two bilaterally presented
stimuli was a tool or not.
On each trial participants were first presented with a blank screen for 1000 ms, followed
by a fixation cross (sized 1 degree of visual angle) at the center of the screen for 300 ms. The
fixation cross was replaced by a display which had a centrally presented arrow (sized 1 degree of
visual angle) pointing to the left or to the right, along with two pictures, one in the left visual
field (LVF) and one in RVF. The duration of the display was 200 ms, based on the research of
Walker & McSorley (2006) showing that participants are unable to initiate an eye movement
within 200 ms if they have to attend to a stimulus at the fixation location (the central arrow in
our case). The stimuli presented in LVF and RVF could represent an object or a non-object (in
Experiment 1), or a tool or a non-tool (in Experiment 2). The stimuli in the VHFs could belong
to the same category (compatible) or a different category (incompatible). Participants were
instructed to attend to the stimulus in the VHF to which the central arrow pointed, and to decide
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whether it represented an object/non-object (Experiment 1) or a tool/non-tool (Experiment 2). In
case the stimulus represented an object (Experiment 1) or a tool (Experiment 2), the participant
had to press two buttons with the index fingers of both hands; otherwise they had to press
buttons with the middle fingers of both hands. We used bi-manual responses to avoid a stimulus-
response compatibility effect (i.e., responses by the right hand are faster to stimuli in RVF and
vice-a-versa). Reaction Times and Accuracy were calculated based on the first key-press
registered. Reaction time measurement started from stimulus offset, like in Verma and Brysbaert
(2011). This means that 200 ms must be added to get the total processing time.
Depending on the VHF of stimulus presentation (LVF or RVF), the stimulus (object/non-
object, tool/non-tool), and whether the stimulus in the contra-lateral visual field was from the
same category (compatible vs. incompatible), eight types of trials could be formed. There were
80 instances of each type in each experiment, giving 640 trials in all. All participants started with
the object vs. non-object decision task, and ended with the tool vs. non-tool task.
Results
The findings of the two experiments are summarized in Figures 3 and 4.
We ran a 2 x 2 x 2 x 2 omnibus ANOVA to compare the two tasks, having Task (Object
recognition vs. Tool recognition), VHF (LVF vs. RVF), Response (yes vs. no), and
Compatibility of the distractor in the opposite VHF (from the same vs. different category) as
repeated measures. For the RT data, we obtained significant main effects of VHF (LVF=412.7
ms vs. RVF=406.7 ms; F (1, 38) = 10.09, p<0.01), Response (Yes= 385.7 vs. No=433.7, F (1,
38) = 123.75, p<0.01), and Compatibility (Incompatible= 419.8 vs. Compatible= 399.6, F (1, 38)
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 126
= 85.57, p<0.01). The main effect of Task was not significant (Object Recognition = 405.1 vs.
Tool Recognition = 414.3, F (1, 28) = 0.24, p>0.05).
Significant interaction effects were: Task x VHF (F (1, 38)= 27.33, p<0.01); Task x
Response (F (1, 38)= 5.87, p<0.05); VHF x Response (F (1, 38)= 11.74, p<0.01); Task x VHF x
Compatibility (F (1,38)= 4.96, p<0.05); Response x Compatibility (F (1,38)= 91.93, p<0.01) and
Task x Response x Compatibility (F (1, 38)= 30.33, p<0.01).
We also calculated the same omnibus ANOVA on percentage accuracy. This revealed
significant a main effect of Compatibility (Incompatible = 87.3% correct vs. Compatible =
89.9%, F (1, 38) = 50.86, p<0.01). The effect of Task was close to significance (Object
Recognition = 89.9 vs. Tool Recognition = 87.2, F (1, 38) = 4.03, p = 0.052). The significant
interaction effects were: Task x VHF (F (1, 38) = 4.57, p<0.05), VHF x Compatibility (F (1, 38)
= 6.09, p<0.05) and Response x Compatibility (F (1, 38) = 16.30, p<0.01). The interpretation of
these effects will be clearer when we have a look at the ANOVAs for the two tasks separately.
Chapter 3|A validated set of tool pictures with matched objects and non-objects
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Figure 3: The results from the object recognition task, showing the lack of a clear VHF
difference (except for the significant LVF advantage for non-objects in the RTs). Left
panel: RT data; right panel: Percentage Acuuracy (P.A.) %.
Figure 4: The results from the tool recognition task, showing the robust RVF advantage in
the presence of a very similar performance level as in the object recognition task. Left
panel: RT data; right panel: Percentage Accuracy (P.A.) %.
350
375
400
425
450
475
500
LVF RVF
RTs
Objects
Non-Objects
75
80
85
90
95
LVF RVF
P.A. (%)
Objects
Non-Objects
350
375
400
425
450
475
500
LVF RVF
RTs Tools
Non-Tools
75
80
85
90
95
LVF RVF
P.A.s (%)
Tools
Non-Tools
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
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We ran a 2 x 2 x 2 ANOVA for each task, i.e. Object Recognition and Tool Recognition,
to understand the effects of VHF, Response and Compatibility better. In the Object Recognition
task, the 2 x 2 x 2 ANOVA on RTs revealed a significant main effect of Response (Yes i.e.
Objects= 376.7 ms vs. No i.e. Non-objects = 433.6) and Compatibility (Incompatible = 415.9 vs.
Compatible = 394.4). The main effect of VHF was not significant (LVF = 403.4 vs. RVF =
406.8, F (1, 38) = 1.88, p >0.05). The significant interactions were VHF x Response (F (1, 38) =
5.44, p<0.05) and Response x Compatibility (F (1, 38) = 110.07, p<0.01). The interaction
between VHF and Response seems to be driven mainly by the no responses (for non-objects):
There was no significant difference in RTs between LVF and RVF for objects (LVF = 377.2 vs.
RVF = 376.2, F(1, 38) = F(1, 38) = 0.088, p>0.05 ) while there was a significant LVF advantage
in RTs for non-objects (LVF = 429.6, RVF = 437.5, F(1, 38) = 9.13, p<0.01). The interaction
between response x compatibility was also mainly driven by the effect of compatibility for non-
objects; non-objects seemed to become particularly salient in case of compatible information
across the visual fields and elicit faster RTs as compared to when stimuli in the two visual fields
were from different categories (Incompatible = 456.2, Compatible = 410.9, F (1, 38) = 130.96,
p<0.01). For the Accuracy data, the 2 x 2 x 2 ANOVA revealed a significant main effect of
compatibility (Incompatible = 88.7, Compatible = 91.2, F (1, 38) = 20.11, p<0.01). The
interaction effects of VHF x Compatibility (F (1, 38) = 4.23, p<0.05) and Response x
Compatibility (F (1, 38) = 14.48, p<0.01) were significant, indicating that overall participants
were more accurate in cases where information across the two visual fields belonged to the same
category. The three way interaction between VHF, Response and Compatibility was not
significant (F (1, 38) = 0.147, p>0.05).
Chapter 3|A validated set of tool pictures with matched objects and non-objects
P.| 129
In the Tool Recognition task, the 2 x 2 x 2 ANOVA for RTs revealed significant main
effects of VHF (LVF = 421.9 ms, RVF = 406.6 ms, (F (1, 38) = 32.74, p< 0.01), Response (yes =
394.8, no = 433.8, F (1, 38) = 53.27, p<0.01) and Compatibility (Incompatible = 423.7,
Compatible = 404.8, F (1, 38) = 58.32, p<0.01). The significant interaction effects were VHF x
Compatibility (F (1, 38) = 5.65, p<0.05) and Response x Compatibility (F (1, 38) = 21.79,
p<0.01). The interaction between VHF and Response failed to reach significance (F (1, 38) =
2.57, p>0.05). In the tool recognition task, participants responded significantly faster to pictures
of tools presented in RVF than in LVF (LVF = 404.6, RVF = 384.9, F (1, 38) = 20.05, p<0.01).
Also participants responded significantly faster to tools in the compatible condition than in the
incompatible condition (incompatible = 399.5, compatible = 390.1, F (1, 38) = 8.51, p<0.01). For
the non-tool objects, participants were also significantly faster in RVF (LVF = 439.2, RVF =
428.4, F (1, 38) = 11.43, p<0.01); also similar to the tools, non-tool objects were responded to
significantly faster in the compatible condition (incompatible = 448.1, compatible = 419.5, F (1,
38) = 78.08, p <0.01). For the Accuracy data, the 2 x 2 x 2 ANOVA revealed significant main
effects of VHF (LVF = 86.7, RVF = 87.8, F (1, 38) = 4.26, p<0.05) and compatibility
(incompatible = 85.8, compatible = 88.6, F (1, 38) = 30.36, p<0.01).
To be sure that the inclusion of the 8 tool stimuli, which did not score above 4 in the Tool
Rating Scale, did not distort the findings; we reanalyzed the data from the tool recognition study
excluding these stimuli. Fortunately, the results did not change at all. There was again a main
effect of VHF (LVF= 420.9 ms vs. RVF = 406.1 ms), F (1, 38) = 35.30, p<.01, Response (yes =
393.2 ms vs. no = 433.8 ms), F (1,38) = 53.48, p <.01, and Compatibility (compatibility = 403.6
ms vs. incompatibility = 423.4 ms), F (1,38) = 60.24. The interaction between VHF x
Compatibility, F (1, 38) = 7.15, p < 0.05 (p= 0.011) and between Response x Compatibility was
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 130
also again significant, F (1, 38) = 21.53, p < 0.01. Finally, the VHF advantage for tools did not
change either (LVF = 412.3 ms vs. RVF = 385.3 ms), F (1, 38) = 25.24, p < 0.01. As the initial
analysis already excluded the incorrect trials; the exclusion of the stimuli did not affect the
percentage accuracy pattern.
All in all, the addition of the less clear stimuli did not make a difference in the pattern of
results; and probably they can be kept included in the stimuli pool.
Discussion
To improve research on tool recognition (in particular, laterality research), we developed
a set of pictures in which tools, non-tool objects, and non-objects were made as similar as
possible (see Figure 1 for examples; see the Appendix for a list of all the picture names; see the
supplementary materials for files of the pictures). To validate the new stimulus materials, we
used them in the two experiments described by Verma and Brysbaert (2011): An object and a
tool recognition experiment. On the basis of our previous results (and in line with the existing
literature), we expected no VHF difference for the object-recognition experiments, whereas a
significant RVF advantage was predicted for the tool recognition experiment.
We indeed obtained a very robust interaction between Task (object recognition vs. tool
recognition) and VHF. The results of the Object Recognition experiment pointed to equal
performance in LVF and RVF for responses to objects, combined with an 8 ms LVF advantage
for responses to non-objects. The latter was also observed in Verma and Brysbaert (2011) and is
not contradictory to the expectations. Non-objects are by definition unnamable, and arguably the
participants resort to a spatial analysis for rejecting these stimuli as existing objects. Because
Chapter 3|A validated set of tool pictures with matched objects and non-objects
P.| 131
spatial analysis predominantly relies on the right hemisphere, especially in the case of right
handers (Vogel, Bowers & Vogel, 2003), a LVF advantage is not surprising.
More importantly, we replicated the predicted RVF advantage for tool recognition. This
was true for the yes-responses to tools (20 ms RVF advantage) and for the no-responses to the
non-tool objects (11 ms RVF advantage). In Verma & Brysbaert (2011) the differences were
respectively 17 ms and 3ms. The RVF advantage becomes even larger if the analysis is limited to
the incompatible trials, when the distractor in the opposite VFH was not from the same category
as the target. Then the difference increases to 26 ms for the tools and to 15 ms for the non-tool
objects.
Also interesting is the finding that overall response times and accuracies were very
similar in both tasks (RT ≈ 410 ms, % correct ≈ 89%). This makes it easier to interpret the
interaction (Loftus, 1978) and is much better than in Verma & Brysbaert (2011), where the
object recognition task (451 ms) was significantly faster than the tool recognition task (474 ms)
and also more accurate (85.2 % vs. 84.2% correct). This illustrates the importance of using the
same, controlled stimuli in both tasks.
To encourage more researchers to investigate tool and object recognition, we make the
new set of stimuli available as supplementary materials. The main omission of the Snodgrass &
Vanderwart (1980) stimulus bank is that it does not have pictures of non-objects. This makes it
impossible for researchers to run object vs. non-object discrimination tasks on these stimuli. In
addition, we found it hard to compile enough well-matched stimulus pairs of tools and non-tool
objects with this stimulus bank. Other pictures databases (e.g., van Diepen & De Graaf, 1994) do
contain pictures of non-objects, but have a shortage of tool pictures. Because the drawing style of
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
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both datasets is different, it is impossible to combine a picture from one set with that of another
set, without introducing all types of low-level visual confounds (e.g., the thickness of the lines or
the level of texture in the picture). Now, we have a set of stimulus materials addressing these
concerns. This should encourage further research into tool use and the lateralization of the skills
involved.
Chapter 3|A validated set of tool pictures with matched objects and non-objects
P.| 133
References
Alcock, J. (1972). The evolution of the use of tools by feeding animals. Evolution, 26, 464-473.
Amant, R. ST., & Horton, T. E. (2008). Revisiting the definition of tool use. Animal Behvaior,
75(4), 1199-1208.
Amborse, S.H. (2001). Paleolithic technology a human evolution. Science, 291, 1748-1753.
Arbib, M. A. (2002) Beyond the mirror system: imitation and evo-lution of langauge. In:
Nehaniv C, Dautenhan K (eds) Imita-tion in animals and artifacts. The MIT Press,
Cambridge, MA, pp 229–280.
Beck, B. B. (1980). Animal Tool Behavior: the Use and Manufacture of Tools. New York:
Garland STPM Press.
Beauchamp, M., Lee, K., Haxby, J., & Martin, A. (2002). Parallel visual motion processing
streams for manipulable objects and human movements. Neuron, 34, 149–159.
Boesch, C. and Boesch, H. (1990). Tool use and tool making in wild chimpanzees. Folia
Primatologica, 54, 86-99.
Chao, L. L., & Martin, A. (2000). Representation of manipulable man-made objects in the dorsal
stream. Neuroimage, 12, 478–484.
Chao, L.L, Haxby, J. V., and Martin, A. (1999). Attribute-based neural substrates in temporal
cortex for perceiving and knowing about objects. Nature Neuroscience, 10 (2), 913-919.
Choi, S. H., Na, D. L., Kang, E., Lee, K. M., Lee, S. W., & Na, D. G. (2001). Functional
magnetic resonance imaging during pantomiming tool-use gestures. Experimental Brain
Research, 139, 311–317.
Corballis, M. C. (2009). The evolution of language. Annals of the New York Academy of
Sciences, 1156: 19–43. doi: 10.1111/j.1749-6632.2009.04423.x
Corballis, M. C. (2010). Mirror neurons and the evolution of language. Brain and Language,
112(1), 25-35.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 134
Corballis, M. C., Badzakova-Trajkov, G., and Haberling, S. (2012). Right hand, left brain:
genetic and evolutionary bases of cerebral asymmetries for language and manual action.
WIREs Cogn Sci 2012, 3:1–17. doi: 10.1002/wcs.158.
Dobato, J. L., Baron, M., Barriga, F. J., Pareja, J. A., Vela, L. & Sanchez Del Rio, M. 2001
Apraxia cruzada secundaria a infarto parietal derecho. Rev. Neurol., 33, 725–728.
Frey, S. H. (2008). Tool use, communicative gesture and cerebral asymmetries in the modern
human brain. Philosophical Transactions of the Royal Society of London Series B, 363,
1951–1957.
Frey, S.H. (2004). The neural bases of complex tool use in humans. Trends in Cognitive
Sciences, 8(2), 71-78.
Frey, S.H. (2007). What puts the how in where? Tool use and the divided visual streams
hypothesis. Cortex, 43, 368-375.
Frey, S.H., Funnell, M.G., Gerry, V. E., and Gazzaniga, M. S. (2005). A dissociation between
the representation of tool-use skills and hand dominance: Insights from Left and Right
Handed Callosotomy Patients. Journal of Cognitive Neuroscience, 17(2), 262-272.
Frey, S.H., Newman-Norlund and Grafton, S.T. (2005). A Distributed Left Hemisphere Network
Active During Planning of Everyday Tool Use Skills. Cerebral Cortex, 15, 681-695.
Fridman, E.A., Immisch, I., Hanakawa, T., Bohlhalter, S., Waldvogel, D., Kansaku, K.,
Wheaton, L., Wu, T., and Hallett, M. (2006). The role of the dorsal stream for gesture
production. Neuroimage, 29, 417-428.
Garcea, F. E., Almeida, J., and Mahon, B.Z. (2012). A right visual field advantage for visual
processing of manipulable objects. Cognitive Affective Behavioral Neuroscience, doi
10.3758/s13415-012-0106-x
Goldenberg, G., & Spatt, J. (2009). The neural basis of tool use. Brain, 132, 1645–1655.
Chapter 3|A validated set of tool pictures with matched objects and non-objects
P.| 135
Goldenberg, G., Hermsdorfer, J., Glindemann, R., Rorden, C., and Karnath, H. O. (2007).
Pantomime of Tool Use Depends on Integrity of Left Inferior Frontal Cortex. Cerebral
Cortex, 17, 2769-2776.
Grezes, J., & Decety, J. (2001). Does visual perception of objects afford action? Evidence from a
neuroimaging study. Neuropsychologia, 40, 212–222.
Hamilton, A. F. de C. and Grafton, S. T. (2008). Action Outcomes Are Represented in Human
Inferior Frontoparietal Cortex. Cerebral Cortex, 18(5), 1160-1168.
Hart, B. L., Hart, L. A., McCoy, M. and Sarath, C. R. (2001). Cognitive behaviour in asian
elephants: Use and modification of branches for fly switching. Animal Behaviour, 62,
839-847.
Hartmann, K., Goldenberg, G., Daumuller, M., Hermsdorfer, J. (2005). It takes the whole brain
to make a cup of coffee: the neuropsychology of naturalistic actions involving technical
devices. Neuropsychologia, 43(4), 625-637.
Hermsdorfer, J., Li, Y., Randerath, J., Goldenberg, G., and Johanssen, L. (2012). Tool use
without a tool: kinematic characteristics of pantomiming as compared to actual use and
the effect of brain damage. Experimental Brain Research, 218, 201-214.
Hunt, G. R. (1996). Manufacture and use of hook-tools by new Caledonian crows. Nature, 379,
249-251.
Kallenbach, M. L., Brett, M., & Patterson, K. (2003). Actions speak louder than functions: The
importance of manipulability and action in tool representation. Journal of Cognitive
Neuroscience, 15(1), 30–46.
Kroliczak, G. and Frey, S.H. (2009). A common network in the Left Cerebral Hemisphere
Represents Planning of Tool Use Pantomimes and Familiar Intransitive Gestures at the
Hand – Independent Level. Cerebral Cortex, 19, 2396-2410.
Kru¨tzen, M., Mann, J., Heithaus, M. R., Connor, R. C., Bejder, L. & Sherwin, W. B. (2005).
Cultural transmission of tool use in bottlenose dolphins. Proceedings of the National
Academy of Sciences, U.S.A., 102, 8939-8943.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 136
Lefebvre, L., Nicolakakis, N. and Boire, D. (2002) Tools and brains in birds. Behaviour, 139,
939-973.
Lewis, J. W. (2006). Cortical networks related to human use of tools. Neuroscientist, 12, 211-
231.
Loftus, G. R. (1978). On interpretations of interactions. Memory and Cognition, 6(3), 312-319.
Oakley, K.P. (1956) Man the tool-maker. London: British Museum.
Osiurak, F., Jarry, C., Allain, P., Aubin, G., Etcharry-Bouyx, F., Richard, I., Bernard, I., Le Gall,
D. (2009). Unusual use of objects after unilateral brain damage. The technical reasoning
model. Cortex, 45, 769–783.
Perani, D., Schnur, T., Tettamanti, M., Gorno Tempini, M., Cappa, S. F., & Fazio, F. (1999).
Word and picture matching: A PET study of semantic category effects.
Neuropsychologia, 37, 293–306.
Preston, B. (1998). Cognition and tool use. Mind and Language, 13, 513-547.
Randerath, J., Goldenberg, G., Spijkers, W., Li, Y., & Hermsdorfer, J. (2010). Different left
brain regions are essential for grasping a tool compared with its subsequent use.
NeuroImage, 53, 173–180.
Rizzolatti, G. (2005). The mirror neuron system and its function in humans. Anat Embryol, 210,
419–421.
Rizzolatti, G., Fogassi, L., Gallese, V. (2001) Neurophysiological mechanisms underlying the
understanding and imitation of action. Nat Rev Neurosci, 2, 661–670.
Rizzolatti, G., and Arbib, M. A. (1998) Language within our grasp. Trends Neurosci, 21, 188–
194.
Steele, J., and Uomini, N. (2009). Can the archaeology of manual specialization tell us anything
about language evolution? A survey of the state of play. Cambridge Archaeological
Journal, 19(1), 97-110.
Chapter 3|A validated set of tool pictures with matched objects and non-objects
P.| 137
Stout, D., and Chaminade, T. (2012). Stone tools, language and the brain in human evolution.
Philosophical Transactions of the Royal Society B: Biological Sciences, 367(1585):75-
87.
Snodgrass, J. G., & Vanderwart, M. (1980). A Standardized set of 260 pictures: Norms for name
agreement, image agreement, familiarity and visual complexity. Journal of Experimental
Psychology: Human Learning and Memory, 6(2), 174–215.
Uomini, N. T., Meyer, G. F. (2013) Shared Brain Lateralization Patterns in Language and
Acheulean Stone Tool Production: A Functional Transcranial Doppler Ultrasound Study.
PLoS ONE 8(8): e72693. doi:10.1371/journal.pone.0072693
Valenstein, E. & Heilman, K. M. 1979 Apraxic agraphia with neglect-induced paragraphia.
Arch. Neurol. 36, 506–508.
van Diepen, P. M. J., & De Graef, P. (1994). Line-drawing library and software toolbox (Psych.
Rep. No. 165). In Laboratory of experimental psychology. Belgium: University of
Leuven.
van Lawick-Goodall, J. (1970). Tool-using in primates and other vertebrates. In: Advances in the
Study of Behavior. Vol. 3 (Ed. By D. Lehrman, R. Hinde & E. Shaw), pp. 195-249. New
York: Academic Press.
Van Schaik, C.P., Ancrenaz, M., Borgen, G., Galdikas, B., Knott, C.D., Singleton, I., Suzuki, A.,
Utami, S.S. and Merrill, M. (2003). Orangutan Cultures and the Evolution of Material
Culture. Science, 299, 102-105.
Verma, A. and Brysbaert, M. (2011). A right visual field advantage for tool-recognition in the
visual half field paradigm. Neuropsychologia, 49, 2342-2348.
Vingerhoets, G., Alderweireldt, A.S., Vandemaele, P., Cai, Q., Van der Haegen, L., Brysbaert,
M., and Achten, E. (2013). Praxis and language are linked: Evidence from co-
lateralization in individuals with atypical language dominance. Cortex, 49 (1), 172-183.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 138
Vogel, J. J., Bowers, C.A. and Vogel, D.S. (2003). Cerebral lateralization of spatial abilities; a
meta-analysis. Brain and Cognition, 52, 197-204.
Walker, R., and McSorley, E. (2006). The parallel programming of voluntary and reflexive
saccades. Vision Research, 46(13), 2082-2093.
Westergaard, G. C. and Fragaszy, D. M. (1987). The Manufacture and Use of Tools by Capuchin
monkeys (Cebus paella). Journal of Comparative Psychology, 101 (2), 159-168.
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P.| 139
Appendix: Triplets of stimuli: objects, non-objects and tools, together with
mean ratings in the Object Recognition Scale (ORS) and the Tool Recognition
Scale (TRS).
Triplet 1
Maize Non Object 1 Broom
(ORS = 5.65 ; TRS = 1.1) (ORS = 2.15) (TRS = 5.35 )
Triplet 2
Fence Non Object 2 Comb
(ORS = 5.5; TRS = 2.15) (ORS = 3.55) (TRS = 5.0)
Triplet 3
Log Non Object 3 Rolling Pin
(ORS = 5.85; TRS = 1.65) (ORS = 1.65) (TRS = 5.3)
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Triplet 4
Airplane Non Object 4 Anchor
(ORS = 5.89; TRS = 2.5) (ORS = 1.57) (TRS = 4.55)
Triplet 5
Ship Non Object 5 Iron
(ORS = 5.84; TRS = 2.1) (ORS = 1.84) (TRS = 5.35)
Triplet 6
Curtain Non Object 6 Harp
(ORS = 6.0; TRS = 1.55) (ORS = 1.31) (TRS = 2.6)
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Triplet 7
Finger Non Object 7 Pistol
(ORS = 5.89; TRS = 3.05) (ORS = 1.52) (TRS = 4.35)
Triplet 8
Pear Non Object 8 Guitar
(ORS = 5.94; TRS = 1.2) (ORS = 1.84) (TRS = 2.75)
Triplet 9
Lamp Non Object 9 Hand-drill
(ORS = 5.89; TRS = 2.0) (ORS = 1.94) (TRS = 5.9)
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Triplet 10
Chocolate Non Object 10 Sharpener
(ORS = 5.42; TRS = 1.25) (ORS = 2.36) (TRS = 5.4)
Triplet 11
Pumpkin Non Object 11 Kettle
(ORS = 5.73; TRS = 1.2) (ORS = 1.36) (TRS = 3.7)
Triplet 12
Bouquet Non Object 12 Pipe
(ORS = 5.73; TRS = 1.1) (ORS = 1.68) (TRS = 3.2)
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Triplet 13
Mushroom Non Object 13 Umbrella
(ORS = 5.84; TRS = 1.15) (ORS = 2.0) (TRS = 4.2)
Triplet 14
Band-aid Non Object 14 Wristwatch
(ORS = 5.65; TRS = 3.35) (ORS = 1.63) (TRS = 3.55)
Triplet 15
Flower Non Object 15 Razor
(ORS = 5.89; TRS = 1.1) (ORS = 1.1) (TRS = 5.2)
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Triplet 16
Twig Non Object 16 Zipper
(ORS = 5.84; TRS = 1.7) (ORS = 1.26) (TRS = 3.4)
Triplet 17
Shoe Non Object 17 Wrench
(ORS = 5.94; TRS = 2.15) (ORS = 1.52) (TRS = 6.0)
Triplet 18
Carrot Non Object 18 Toothbrush
(ORS = 5.68; TRS = 1.05) (ORS = 1.78) (TRS = 5.2)
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Triplet 19
Sausage Non Object 19 Stethoscope
(ORS = 4.73; TRS = 1.1) (ORS = 1.52) (TRS = 5.2)
Triplet 20
Candle Non Object 20 Spoon
(ORS = 5.84; TRS = 3.15) (ORS = 2.26) (TRS = 5.25)
Triplet 21
Boot Non Object 21 Shovel
(ORS = 5.57; TRS = 2.3) (ORS = 1.78) (TRS = 5.6)
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Triplet 22
Pillar Non Object 22 Screwdriver
(ORS = 5.68; TRS = 1.9) (ORS = 1.68) (TRS = 5.9)
Triplet 23
Bottle-gourd Non Object 23 Saxophone
(ORS = 4.0; TRS = 1.1) (ORS = 1.63) (TRS = 3.0)
Triplet 24
Incline Non Object 24 Saw
(ORS = 5.26; TRS = 3.4) (ORS = 2.04) (TRS = 6.0)
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Triplet 25
Pamphlet Non Object 25 Ruler
(ORS = 5.68; TRS = 2.9) (ORS = 2.52) (TRS = 5.0)
Triplet 26
Spring-onion Non Object 26 Pliers
(ORS = 5.52; TRS = 1.15) (ORS = 2.05) (TRS = 5.9)
Triplet 27
Sunflower Non Object 27 Pan
(ORS = 5.63; TRS = 1.1) (ORS = 1.89) (TRS = 4.65)
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Triplet 28
Asparagus Non Object 28 Pen
(ORS = 5.47; TRS = 1.04) (ORS = 1.31) (TRS = 5.05)
Triplet 29
Palm Non Object 29 Mop
(ORS = 5.73; TRS = 1.15) (ORS = 2.52) (TRS = 5.6)
Triplet 30
Feather Non Object 30 Knife
(ORS = 5.78; TRS = 2.6) (ORS = 1.94) (TRS = 5.8)
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Triplet 31
Bone Non Object 31 Hammer
(ORS = 5.78; TRS = 1.65) (ORS = 1.89) (TRS = 6.0)
Triplet 32
Ice-cream Non Object 32 Funnell
(ORS = 5.94; TRS = 1.1) (ORS = 1.42) (TRS = 5.2)
Triplet 33
Cactus Non Object 33 Fork
(ORS = 5.73; TRS = 1.1) (ORS = 1.63) (TRS = 5.35)
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Triplet 34
Book Non Object 34 Dustpan
(ORS 6.0; TRS = 1.85) (ORS = 2.21) (TRS = 5.35)
Triplet 35
Celery Non Object 35 Paint-brush
(ORS = 5.42; TRS = 1.15) (ORS = 3.31) (TRS = 5.7)
Triplet 36
Flag Non Object 36 Axe
(ORS = 5.73; TRS = 2.35) (ORS = 2.73) (TRS = 5.85)
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Triplet 37
Beans Non Object 37 Needle
(ORS = 5.73; TRS = 1.15) (ORS = 3.21) (TRS =4.85)
Triplet 38
Chimney Non Object 38 Cigarettes
(ORS = 5.89; TRS = 1.9) (ORS = 1.42) (TRS = 1.55)
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Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
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Chapter 4: Symmetry Detection in Typically and
Atypically Speech Lateralized Individuals: A Visual
Half-field Study
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Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
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Chapter 4: Symmetry Detection in Typically and Atypically Speech
Lateralized Individuals: A Visual Half-field Study
Visuospatial functions are typically lateralized to the right cerebral hemisphere, giving
rise to a left visual field advantage in visual half-field tasks. In a first study we investigated
whether this is also true for symmetry detection off fixation. Twenty right-handed participants
with left hemisphere speech dominance took part in a visual half-field experiment requiring them
to judge the symmetry of 2-dimensional figures made by joining rectangles in symmetrical or
asymmetrical ways. As expected, a significant left visual field advantage was observed for the
symmetrical figures. In a second study, we replicated the study with 37 left-handed participants
and left hemisphere speech dominance. We again found a left visual field advantage. Finally, in
a third study, we included 17 participants with known right hemisphere dominance for speech
(speech dominance had been identified with fMRI in an earlier study; Van der Haegen et al,
2011). Around half of these individuals showed a reversed pattern, i.e. a right visual half-field
advantage for symmetric figures while the other half replicated the left visual-field advantage.
These findings suggest that symmetry detection is indeed a cognitive function lateralized to the
right hemisphere for the majority of the population. The data of the participants with atypical
speech dominance are more in line with the idea that language and visuospatial functions are
lateralized in opposite brain hemispheres than with the idea that different functions lateralize
independently, although there seems to be more variability in this group.
This chapter has been published as Verma, A., van der Haegen, L., & Brysbaert, M. (2013). Symmetry detection in
typically and atypically lateralized individuals: a visual half field study. Neuropsychologia, 51, 2611-2619.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
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Introduction
The brain is divided in a left and a right half. Decades of research have shown through a variety
of methods that a number of cognitive functions are unequally represented in both hemispheres.
Asymmetries have been documented in both structure and functioning. For instance, the planum
temporale region of the brain has been found to be larger in the left than in the right hemisphere
(for recent reviews, see Amunts, 2010; Greve, Van der Haegen, Cai, Stufflebeam, Sabuncu,
Fischl, & Brysbaert, in press). In most people language is lateralized to the left hemisphere. This
hemisphere has also been reported to be superior in processing local elements, while the right
hemisphere has been reported to be specialized in processing global elements (Bradshaw &
Nettleton, 1981). Along the same lines it has been pointed out that the left hemisphere is good at
categorical decisions whereas the right hemisphere is relatively better at coordinate decisions
(Kosslyn, 1987). Finally, the two hemispheres are supposed to be differentially adept at
processing spatial frequency; the left hemisphere has an advantage for processing higher spatial
frequencies, whereas the right hemisphere would be better at processing low spatial frequencies
(Sergent, 1983).
Several fundamental principles (e.g., analytic vs. holistic) have been proposed to
understand the asymmetries of the two hemispheres (both structural and functional), but these
have not been very successful (Hellige, 1993). Hugdahl (2000) observed that of all dichotomies
put forward none has produced more consistent findings than the traditional distinction between
language functions in the left hemisphere and a range of visuospatial functions in the right
hemisphere. He argued that the functional asymmetry of the brain is the result of evolutionary
pressure towards specialization for behaviors unique to the evolution of modern man. The
emergence of language capabilities is one of the most plausible candidates to serve as a
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
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fundamental force for a functional division of the brain into a right and left half. Another facility
of humans that can serve this function is the ability to represent the 3-dimensional environment
as a visuospatial map. While the ability and need to communicate symbolically may have led to
the evolution of the left hemisphere as specialized in language and related functions, the right
hemisphere specialization could be due to the fact that orientation in space required rapid
identification of objects and their relations. Hence, according to Hugdahl (2000) the language-
left hemisphere and the visuospatial right hemisphere dichotomy is the guiding principle to
understand brain asymmetries in human cognitive performance.
While many studies have documented the left hemisphere dominance for language
processing, comparatively little behavioral research has been dedicated to the functions of the
right hemisphere. Most of these studies were done with the visual half-field (VHF) task. In this
task stimuli are presented in the left and right parafovea, and more efficient processing in the left
visual field (LVF) than in the right visual field (RVF) is interpreted as evidence for right brain
laterality. Bryden (1982) pointed out that on the basis of this evidence the right hemisphere is
likely to be better able to handle a variety of cognitive functions, such as spatial abilities
(Benton, Hannay & Varney, 1975), face recognition (Geffen, Bradshaw & Wallace, 1971), and
emotional expression (Ley & Bryden, 1981). The specialization for spatial abilities was attested
by LVF advantages for lightness discrimination (Davidoff, 1975), color perception (Hannay,
1979; Pennal, 1977), dot detection (Davidoff, 1977; Umilta, Salmaso, Bagnara, & Simion, 1979),
dot localization (Bryden, 1976), perception of line orientation (Atkinson & Egeth, 1973),
stereopsis (Carmon & Bechtoldt, 1969), and depth perception (Kimura & Durnford, 1974).
Music perception was another function ascribed to the right hemisphere (e.g., Gates &
Bradshaw, 1977) and Hughdahl (2000) further pointed to the critical involvement of the right
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parietal cortex in the allocation of attention, as exemplified by hemineglect after damage to this
region (but not to the left homologue). It must be noted, however, that most of these studies
reflect lateralization in relative terms. While many visual field advantages have been
corroborated by later neuro-imaging studies, it is often the case that the tasks evoke bilateral
activation, with one hemisphere being more active than the other.
The initial findings with the VHF task and other related behavioral paradigms (such as
dichotic listening) have since been replicated and extended with the use of neuroscientific
methods like fMRI, PET, MEG, etc. Shulman, Pope, Astafiev, McAvoy, Snyder, & Corbetta
(2010) used fMRI to measure hemispheric asymmetries during shifts of spatial attention evoked
by a peripheral cue stimulus and during target detection at the cued location. They found right
hemisphere dominant activity at the temporoparietal junction during the shifting of spatial
attention. During later target detection they also observed a more wide-spread right hemisphere
dominant activity in the frontal, parietal and temporal cortices. Yovel, Tambini, & Brandman
(2008) and Hemond, Kanwisher, & Op de Beeck (2007) correlated the much documented LVF
advantage for face detection with fMRI-measured brain activity, and argued that it was related to
a processing asymmetry in the fusiform gyrus (FFA). Also based on fMRI data, Mashal, Faust,
Tendler, & Jung-Beeman (2008) claimed that the right hemisphere plays a major role in solving
semantic ambiguities and in processing non-salient meanings of idiomatic expressions. In a
related domain, Marinkovic, Baldwin, Courtney, Witzel, Dale, & Halgren, E. (2011) on the basis
of MEG data proposed that activations stemming from the right prefrontal cortex play a vital role
in joke appreciation and consequently in humor understanding. Other evidence for right
hemispheric specialization was obtained by Klosterman, Loui, & Shimamura (2009), who
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
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examined retrieval of agrammatical musical sequences (i.e. non-verbalizable sequences of tones)
and found that particularly the right posterior parietal cortex (PPC) was involved.
In the present research, we examined whether symmetry detection is another right
hemisphere dominant task. Symmetry refers to the property of a visual object where in two
(ormore) parts of the object are separated by an imaginary axis and related to each other.
Symmetry can be of various types. Mirror symmetry refers to situations where the two half
planes obtained by dividing the object/display along an in visible central axis are mirror images
of each other. Cases where the central axis is vertical manifest vertical symmetry, those where
the central axis is horizontal manifest horizontal symmetry, and when the axis is diagonal the
pattern reflects diagonal symmetry. Rotational symmetry is found when the rotation of a pattern
aligns with the original pattern. Because symmetry perception is particularly efficient when the
symmetry axis coincides with the vertical midline (Herbert & Humphreys, 1996), a further
distinction is made between symme-try at fixation (when the stimulus is in the center of the
visual field) and symmetry off fixation (when the stimulus is in parafoveal vision).
Symmetry is everywhere in the visual world and thus it is no surprise that biological
vision systems are endowed with adaptive strategies for perceiving and utilizing this property
(Wagemans, 1995). Pigeons can discriminate and classify shapes on the basis of symmetry
(Delius & Nowak, 1982) and experiments with human infants have provided evidence for
aninnate preference of sym- metric patterns (Bornstein, Ferdinandsen, & Gross, 1981). Symme-
try is also easily detected in random dot configurations presented for less than 150ms
(Barlow&Reeves, 1979). This is particularly true for the detection of vertical symmetry at
fixation (Royer, 1981).
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Symmetry is used in various other visuospatial functions as well. Koffka (1935) noted
that it was a helpful cue for figure- ground segregation, which was empirically confirmed for
vertical mirror symmetry by Machilsen, Pauwels, and Wagemans (2009). Marr (1982) proposed
that symmetry is an important non- accidental feature for determining the principal axis of a
shape, prior to deriving an object centered description relative to this axis. Bayliss and Driver
(1994) suggested that memory representa- tions of objects involved in formation about their
symmetry. Finally, studies have shown superior recognition for faces in case of symmetric facial
features; hence demonstrating the importance of symmetry in face perception (Little & Jones,
2006; Rhodes, Peters, Lee, Morrone, & Burr, 2005; Troje & Bulthoff, 1997).
Because of the importance of symmetry detection, authors have speculated about whether
it could be a basic, preattentive feature used for image segmentation, just like orientation,
brightness, color, or movement. Kootstra, de Boer, & Schomaker (2011), for instance, found that
when participants were viewing complex photographic images, their early fixations
predominantly were on highly symmetrical areas of the image. The authors further showed that a
computational model of eye guidance, including symmetry information to predict eye-
movements, outperformed the existing models based on contrast features. On the other hand,
Gurnsey, Herbert, & Kenemy (1998) reported evidence that the detection of vertical bilateral
symmetry embedded in random noise is poor unless the axis of symmetry is at the point of
fixation, and they argued that symmetry does not play a role in image segmentation until an
object has been fixated. This message was recently repeated by Roddy and Gurnsey (2011), who
showed that symmetrical stimuli in parafoveal vision are subject to interference from other
stimuli (crowding) and on the basis of this finding argued that symmetry is not special to the
early visual system (see Olivers & van der Helm,1998, for a similar argument).
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Whatever the exact status of symmetry detection in human perception (preattentive or
not), no author denies its importance for visuospatial cognition.Consequently we hypothesized
that it was likely to bea right-hemisphere function and to give rise to a significant LVF advantage
in a VHF task. Examination of the literature revealed some hints to such an effect. As far as we
could ascertain, four studies have provided evidence for right lateraliza- tion of symmetry
detection.
In a study by Corballis & Roldan (1974), participants were presented with lateralized
tachistoscopic dot patterns and had to tell whether these were symmetrical around the vertical
axis or not. It was found that the yes-responses were 11ms faster in LVF than RVF, suggesting
different abilities for processing symmetry in the two hemispheres. Brysbaert (1994) examined
the effects of lateral preferences (handedness, footedness, eye and ear preference) on VHF
asymmetries and used symmetry detection as one of the tasks. He reported a small but significant
LVF advantage for the task. More recently, Wilkinson & Halligan (2002) examined stimulus
bisection in LVF and RVF (i.e., the so-called landmark task) and reported that stimulus
symmetry contributed to the performance in LVF but not in RVF. From this finding they
concluded that “the detection of visual symmetry is preferentially lateralized to the right
hemisphere” (p. 1045). These findings were confirmed in a later fMRI study (Wilkinson &
Halligan, 2003) when it was found that the presence/absence of symmetry corresponded to
activity in the right anterior cingulate gyrus, an area associated with a variety of higher level
attentional functions. The superior perception of line bisection in LVF was associated with
activation in the right superior temporal gyrus.
However, other studies failed to find evidence for right hemisphere superiority in
symmetry perception. Herbert & Humphrey (1996), for instance, examined whether the quick
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perception of vertical symmetry at fixation could be due to interhemispheric comparison and
indeed found that the detection of vertical symmetry at fixation was anomalous in two persons
born without corpus callosum, but relatively normal for presentation off fixation. More
importantly for the present purpose, they did not report a significant advantage for stimuli
presented in LVF.
Neuroscientific methods also point to a strong bilateral brain activation in symmetry
detection tasks. In an fMRI study, Tyler et al. (2005) presented observers with symmetric and
random dot patterns. The symmetric configurations were found to selectively activate a region in
the dorsolateral occipital cortex (DLO) and activity did not differ significantly between
hemispheres. Sasaki et al. (2005) also reported that symmetrical patterns (both of dots and lines)
activated the extrastriate visual cortex in human and non-human primates (areas V3A, V4, V7
and LO); they did not observe hemispheric differences either (at least none were reported in the
ms). Finally, Cattaneo et al. (2011) used TMS to investigate the neural correlates of symmetry
perception. As expected, they found that pulses to DLP affected symmetry detection, whereas
pulses to V1/V2 did not have an adverse effect. Importantly for the present discussion, no
hemispheric differences were reported (in one analysis there even was a tendency towards left-
hemisphere dominance). For the correct interpretation of the neuroscientific findings it is
important to keep in mind that they all involved large stimuli (up to 20 degree of visual angle)
extending into both VHFs. As illustrated by Herbert & Humphrey (1996), particularly for
vertical symmetry there is a likely difference between symmetry perception at fixation and
symmetry detection off fixation, with strong interhemispheric interactions in the former case.
In the present study, we first examined whether we could replicate the LVF advantage for
parafoveal symmetry detection in right-handed participants, as reported in the four studies
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discussed above. One reason why other researchers may have failed to find the effect is that not
all VHF studies adhere to good methodological standards (Hunter & Brysbaert, 2008). In
particular, it has been found that VHF asymmetries are much more stable and consistent when
independent information is presented simultaneously in LVF and RVF and participants have to
respond to the stimulus indicated by a central arrow. Because of the bilateral presentation, the
influence of attention capture by the stimulus onset is reduced. In addition, the simultaneous
arrival of information in the two hemispheres gives the dominant hemisphere more chances to
outperform the non-dominant hemisphere. Also, the central arrow forces the participant to pay
attention to the fixation location before stimulus onset. Therefore, we first wanted to see whether
the LVF advantage for parafoveal symmetry detection can be replicated under suitable
methodological conditions (Experiment 1). To further extend the results, the same experiment
was tested in a group of left-handed subjects with typical left hemispheric speech lateralization
(Experiment 2). Their lateralization was assessed with two VHF naming tasks and in some cases
confirmed with an fMRI silent word generation task, comparing left and right hemisphere
activity in Broca’s area (see Hunter & Brysbaert, 2008; Van der Haegen, Cai, Seurinck &
Brysbaert, 2011, for further details). Finally, left-handers with known atypical right speech
lateralization took part in the VHF task (Experiment 3). This allowed us to test whether the
lateralizations of speech and symmetry detection are statistically independent or whether there is
a bias to have both functions separated (see Cai, Van der Haegen, & Brysbaert, 2013, for a recent
review of this literature).
Experiment 1
Research about symmetry detection has been done with very different stimulus materials
ranging from simple dot patterns to polygons and complex art displays (Carmody, Nodine &
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Locher, 1977; Locher & Nodine, 1989; Locher & Wagemans, 1993; Donnely, Humphreys, &
Riddoch, 1991). Here, we chose to use symmetric and asymmetric arrangements of rectangles,
because these stimuli were used in previous studies suggesting a right-hemisphere advantage for
symmetry detection (Brysbaert, 1994; Wilkinson & Halligan, 2002, 2003).
Method
Participants
Participants were 20 right-handed students from Ghent University. Handedness was
assessed with a Dutch translation of the Edinburg Handedness Inventory (Oldfield, 1971). A
questionnaire about eye preference, ear preference, and footedness was also administered (Porac
& Coren, 1981). Participants were asked to use a number between -3 and -1 to indicate their
degree of left side preference and between +1 and +3 to indicate their degree of right side
preference (Brysbaert, 1994). Miles’ (1930) test of eye-dominance was also administered to the
participants. Finally, all participants had been diagnosed as left lateralized for speech production
in an earlier fMRI study by Van der Haegen et al. (2011).
Stimuli
The stimuli were figures made in black lines against a white background. They were
made by joining three horizontal rectangles, one above another giving rise to a symmetric or an
asymmetric arrangement (Figure 1). There were 60 different symmetric and 60 different
asymmetric stimuli. They were up to 4° wide and 2° high.
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Symmetric Shapes
Asymmetric Shapes
Figure 1: Two examples of the symmetric and the asymmetric shapes used as stimuli in the
experiments. All stimuli were made by joining three horizontal rectangles that could differ
in length.
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Procedure
Participants were seated in front of a 17 in. computer screen at a distance of 80 cm.
Before the start of each session, they were familiarized with the stimuli, by giving them a central
tachistoscopic presentation of the various stimuli on the computer screen.
Stimulus presentation followed the VHF protocol outlined by Hunter and Brysbaert
(2008). A trial started with the presentation of a blank screen for 1000 ms. Then a fixation cross
(sized 1degree of visual angle) appeared at the centre of the screen for 300 ms. Participants were
instructed to focus on the cross when it appeared. The cross was followed by a slide with two
stimulus figures presented left and right at a distance of 3 degree from the fixation location, and a
centrally presented arrow (sized1degree of visual angle). The arrow could point towards LVF or
RVF and participants had to respond to the stimulus at the side indicated. Because stimulus
presentation was bilateral and participants had to process the central arrow, the stimuli could be
presented for 200 ms without running the risk of fast saccades to one of them (Walker &
McSorley, 2006). The stimuli appearing in LVF or RVF could be symmetric or asymmetric. For
symmetric stimuli participants had to press buttons with their left and right index fingers
simultaneously; for asymmetric stimuli they had to press with the left and right middle fingers.
___________________________________________________________________________
1 In other experiments we sometimes present stimuli of both the compatible and the incompatible type in the
distractor VHF (e.g., Hunter & Brysbaert, 2008). We did not do so here, because it would have required us to make
the experiment longer if we wanted to have a decent number of observations in all conditions. Based on pilot testing
we also had the fear that bilateral symmetry presentation might be too salient (i.e., would elicit particularly fast
responses). As the participants were instructed to constantly fixate at the center of the screen and to respond as
rapidly as possible to the indicated stimulus, we did not have the impression that they were able to make use of any
redundancy in the distractor stimulus, an impression that seems to be borne out by the findings.
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
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Bimanual responses were used to avoid the stimulus-response compatibility effect (i.e.thefactthat
responses with the right hand are faster to stimuli in RVF while responses with the left hand are
faster to stimuli in LVF).
There were four types of trials depending on the direction of the central arrow and
whether or not the target stimulus was symmetric or asymmetric. The four types were Left
Symmetric (central arrow pointing towards LVF, symmetric figure presented in LVF), Left
Asymmetric (central arrow pointing towards LVF, asym- metric figure in LVF), Right
Symmetric (central arrow pointing towards RVF, symmetric figure in RVF), and Right
Asymmetric (central arrow pointing towards RVF, asymmetric figure in RVF). The stimulus in
the non-target VHF was always incompatible with the target stimulus (i.e., if asymmetric figure
had to be attended to, the distractor stimulus was of the asymmetric type). The specific stimuli
(out of the 60 possibilities) were randomly selected by the experiment presentation software.The
experiment was preceded by 40 practice trials, while the main block contained 160trials (40 trials
of each type). As there were 120 stimuli and 200 trials each involving 2 randomly drawn stimuli,
some trials contained a stimulus in LVF or RVF that had been shown before. Stimulus repetition
does not affect the VHF asymmetry in Hunter and Brysbaert (2008) protocol, not even with word
stimuli (e.g., Van der Haegen et al., 2011). As a matter of fact, Hunter and Brysbaert (2008)
recommend the repetition of stimuli over VHFs, as this ensures that the stimulus materials
presented in LVF and RVF are matched. In the present studies there were no indications either
that the asymmetry was different in the first half of the experiment than in the last half.
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Results
Separate 2 X 2 analyses of variance (ANOVAs) were run on the reaction times (RT) of
the correct trials and the percentages of errors (PE). The factors were VHF (left and right) and
Stimulus Type (Symmetric and Asymmetric). For the RT data, this resulted in a significant main
effect of VHF (LVF = 484 ms, RVF = 522 ms; F (1, 19) = 12.859, p < 0.01). Also, a significant
main effect of Stimulus Type was observed (Symmetric = 485ms, Asymmetric = 521ms; F (1,
19) = 20.299, p < 0.01). The interaction of VHF and Stimulus Type was not significant, F (1, 19)
= 1.748, p = 0.202; although there was a trend towards a larger LVF advantage for symmetric
figures than for asymmetric figures on the basis of the mean scores. For symmetric figures, the
LVF advantage was 55ms while for asym- metric figures the advantage was only 23 ms. In all,
16 out of the 20 right-handed participants showed the left-visual field advan- tage for symmetric
figures, while only 12 participants showed the advantage for asymmetric figures.
For the error data, the main effect of VHF was significant, (LVF=13.7%, RVF=19.3%; F
(1, 19) =14.129, p<0.01). There was no significant effect of Stimulus Type, but the interaction
between VHF and Stimulus Type was significant (F (1,19) = 8.058, p<0.05), because the LVF
advantage was larger for symmetric than asymmetric pictures. In terms of errors 18/20
participants showed an LVF advantage for symmetric figures, while only 8 participants showed
the LVF advantage for asymmetric figures.
The fact that a high number of participants show the difference is reassuring as it confirms that
the LVF advantage is not due to a small number of participants with very large asymmetries.
Also the fact that the advantage is larger for symmetric figures than for asymmetric figures
provides support for our speculation that the advantage can be attributed specifically to
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
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symmetry detection and is not due to the visual properties of the 2-d shapes we used as stimuli.
The data are shown in Figure 2.
We also checked for any kind of practice effects for the symmetric and asymmetric
stimuli by comparing the first and second halves of each of the four conditions, but did not find
any statistically significant difference, neither in terms of RT nor accuracy.
Discussion
In the first experiment we sought to investigate whether we could replicate the LVF advantage
for symmetry detection reported in a few studies primarily aimed at other variables (the influence
of lateral preferences on VHF asymmetries; Brysbaert, 1994; and the contribution of stimulus
symmetry to performance on the landmark task; Wilkinson & Halligan, 2002). In both RTs and
PEs, our hypothesis of right hemisphere dominance was confirmed for right-handers with known
left hemisphere speech dominance. The effect was larger for symmetric stimuli than for
asymmetric stimuli, a finding that is often reported in yes/no-decision tasks. Indeed, in many
lexical decision experiments the robust RVF advantage is only observed for words and not for
non-words (Howell & Bryden, 1987; Laine & Koivisto, 1998; Measso & Zaidel, 1990; Mohr et
al. 1994; Nieto et al. 1999). In the next experiment we investigate what happens in left-handers
with typical left hemispheric language lateralization.
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Figure 2: A LVF advantage for symmetry detection in right-handers (left panel: RT; right
panel: PE). The VHF asymmetry is clearer for symmetric pictures (responses) than for
asymmetric pictures (responses), in line with the observation in lexical decision that the
VHF asymmetry is clearer for yes-responses to words than for the slower no-responses to
non-words. Error bars indicate the 95% confidence intervals and are based on the error
terms of the VHF * Stimulus type ANOVA (Masson & Loftus, 2003).
400
450
500
550
600
650
LVF RVF
RTs
(m
s)
Symmetric
Asymmetric
0
5
10
15
20
25
30
35
LVF RVF
PEs
Symmetric
Asymmetric
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Experiment 2
Now that we have shown an LVF advantage for most right-handers with confirmed left
hemispheric speech lateralization when taking strict methodological considerations into account,
the next step is to evaluate the robustness of this effect. In general, more variability of functional
brain organization has been found in left-handers (Bradshaw & Nettleton, 1981), making them a
suitable group to test the reproducibility of the LVF advantage observed in Experiment 1. Part of
the variability in left-handers is due to the fact that they more often have atypical speech
dominance. It is estimated that 20-25% of the left-handers have atypical dominance (Knecht et
al., 2000), against only 1-5% of the right-handers. In addition, it might be expected that left-
handed participants with left speech dominance show more variability in the laterality scores of
various functions than right-handers. In genetic models of hand preference, left-handedness is
thought to be the result of a gene generating random laterality preferences (e.g., McManus,
1985). This may lead to more cross-lateralization of functions (such as speech production and
symmetry detection) in left-handers than in right-handers.
In Experiment 2, we first tested the VHF asymmetry for symmetry detection in a rather
large group of left-handers, who were comparable to the participants of Experiment 1 in terms of
left hemisphere language functioning. In Experiment 3, we looked at a smaller group with known
right hemisphere speech dominance, to see what consequences a specialization shift from the left
to the right inferior frontal gyrus has for the brain functions underlying symmetry detection.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
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Method
Participants
Participants were 37 left-handed participants from Ghent University. The group originally
consisted of 19 individuals who had been confirmed as left hemisphere speech dominant with
fMRI (for more details, see Van der Haegen et al., 2011). Because the findings with the original
group were somewhat ambiguous (a clear trend, but no significance), we nearly doubled the
group to maximize the power of the study1. We were unable to scan the additional individuals,
but they were selected on the basis of a VHF word and picture naming task. All had a clear RVF
naming advantage of more than 20 ms in one of the tasks, and no LVF advantage in the other
task. Based on the results of Hunter & Brysbaert (2008) and Van der Haegen et al. (2011), we
can be confident that this approach reduced the chances of including an atypically lateralized
participant to almost zero. The 37 left-handers were given the same test as in Experiment 1 and
were paid for participating in the experiment.
Stimuli and Procedure
The stimuli and the procedure were exactly the same as in Experiment 1.
Results
We ran a 2 x 2 ANOVA with VHF (2 levels: LVF, RVF) and Stimulus type (2 levels:
Symmetric, Asymmetric) as factors. For the reaction time (RT) data, the ANOVA yielded neither
a significant main effect of VHF nor Stimulus type. However, the interaction effect was
significant (F (1, 36) = 16.28, p < 0.01). For the percentage error data, there was no significant
main effect of VHF or Stimulus type either. Again, the interaction was significant (F (1,36) =
1 The authors thank an anonymous reviewer for this suggestion.
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
P.| 173
10.75, p<0.01). One-way ANOVAs indicated that the VHF effect was significant for the
symmetric stimuli (RT: LVF = 519 ms, RVF = 553 ms, F (1, 36) = 13.34, p<0.01; PE: LVF =
18.5%, RVF = 26.5%, F (1, 36) = 15.42, p < 0.01) and for the asymmetric stimuli. However, for
the latter, the direction was opposite with evidence of a RVF advantage, which was significant
for RT (LVF = 562 ms, RVF = 546 ms; F (1, 36) = 5.29, p < 0.05), but not for PE (LVF =
21.6%, RVF = 17.7%; F (1, 36) = 2.93, p=.095).
When we looked at the individual data, we saw that 29/37 (78.4%) of the participants
showed the LVF advantage for the symmetric stimuli in terms of RTs, and 28/37 (75.7%) in
terms of accuracy. For the asymmetric stimuli, 25/37 (67.5%) of the participants had the opposite
RVF advantage in RTs, and 23/37 (62.1%) in terms of accuracy.
Discussion
In line with the right-handed group of Experiment 1, the left dominant left-handers of
Experiment 2 had a clear LVF advantage for symmetric stimuli, although the size of the advange
(RT = 34 ms, PE = 8.0%) tended to be smaller than in Experiment 1 (RT = 55 ms, PE = 13.7%).
At the same time, there was evidence for more distributed processing in left-handers than in
right-handers, as we observed some evidence for a RVF advantage in the processing of
asymmetric stimuli (Figure 3).
In terms of individual differences, there were few indications that the LVF advantage for
symmetric stimuli was less stable in left-handers than in right-handers, as the percentage of
participants showing the effects was remarkable similar for RT (16/20 or 80% in right-handers
vs. 29/37 or 78.4% in left-handers). For accuracy there was a trend towards less consistency in
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
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left-handers (18/20 or 90% of the right-handers vs. 28/37 or 75.7% of the left-handers made
fewer errors in the LVF condition).
Experiment 3
In a final experiment, we addressed the question whether different functions lateralize
independently or whether atypical speech dominance creates atypical laterality for visuospatial
functions as well. The first view says that verbal and visuospatial abilities are independent
functions and, therefore, lateralize separately. This possibility was first raised by Bryden,
Hecaen, & DeAgostini (1983) who reported that “an analysis of the concurrent incidence of
aphasia and spatial disorder in 270 patients with unilateral brain damage suggests that the two
functions are statistically independent” (p. 249). Although aphasia was more frequent after left
hemisphere damage and spatial disorders after right hemisphere damage, the incidence of
combined disorders was not less than predicted on the basis of statistical independence. From
this finding Bryden et al. (1983) concluded that the complementary specialization of the
hemispheres is not causal in nature and that atypical laterality of one function has no implication
for the other. Similar suggestions were made by Kosslyn (1987), Whitehouse & Bishop (2009),
Badzakova-Trajkov, Häberling, Roberts, & Corballis (2010), and Pinel & Dehaene (2010).
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
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Panel A: Left Dominant (typically lateralized) participants
Panel B: Right Dominant (atypically lateralized) participants
Figure 3: VHF asymmetries of left-handers as a function of language dominance. Panel A
shows the performance of the left hemisphere dominant (typically lateralized) participants
(left: RT; right: PE). Panel B shows the performance of the right hemisphere dominant
(atypically lateralized) participants. For the symmetric figures, there is a clear interaction
between VHF and cerebral dominance (a LVF advantage for the typically lateralized
participants and a trend towards RVF advantage for the atypically lateralized
participants). Contrary to the findings of the participants with language and motor control
in the same hemisphere, the left-handed participants with LH language control tended to
show an opposite VHF advantage for the asymmetric figures than the symmetric figures
(top panel). Error bars indicate the 95% confidence intervals and are based on the error
terms of the VHF * Stimulus type ANOVA (Masson & Loftus, 2003).
400
450
500
550
600
650
LVF RVF
RTs
(ms)
Symmetric
Asymmetric
0
5
10
15
20
25
30
35
LVF RVF
PEs
Symmetric
Asymmetric
400
450
500
550
600
650
LVF RVF
RTs
(ms)
Symmetric
Asymmetric
0
5
10
15
20
25
30
35
LVF RVF
PEs
Symmetric
Asymmetric
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The alternative view says that atypical laterality of language will result in reversed
laterality for other functions. Such a result can be expected on the basis of the cognitive
crowding hypothesis (Lansdell, 1969; Levy, 1969; Teuber, 1974). According to this hypothesis,
visuospatial abilities cannot fully develop in the language hemisphere and are “crowded out” to
the other brain half. Supporting evidence for this theory was recently reported by Cai, Van der
Haegen & Brysbaert (2013) who ran an fMRI study on a visuospatial attention task (the
landmark task) with the same participants as in the present study. In the landmark task brain
activity was compared between an experimental condition, in which participants had to judge
whether a vertically displayed line bisected a horizontal line in the middle, and a control
condition, in which participants had to indicate whether the vertical line touched the horizontal
line. The landmark task is known to activate a dorsal fronto-parietal pathway in the right
hemisphere. Cai et al. (2013) found that their data were almost completely in line with the
crowding hypothesis: Whereas 15 of 16 participants with LH speech dominance showed the
expected RH asymmetry, all 13 participants with RH speech had a reversed LH laterality in the
landmark task. The authors argued that the complementarity pattern had been obscured in
previous studies, because inadequate comparison conditions had been used and/or the reliability
of the measures had not been ascertained, so that measurement noise could have been mistaken
for independence of cognitive functions.
Given the findings of Cai et al. (2013), it would be interesting to know whether their
results can be replicated with the present symmetry task. The predictions are straightforward.
According to the cognitive crowding hypothesis, we should observe a reversed RVF advantage
for symmetric stimuli in participants with right hemisphere language dominance. In contrast,
according to the statistical independence hypothesis, atypical lateralization of language should
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
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have no influence on the laterality of symmetry detection and, hence, participants with right
speech dominance should show the same LVF advantage for symmetric stimuli. Seventeen left-
handers with known atypical RH dominance (Van der Haegen et al., 2011) took part in the
symmetry detection task. Given the data of Experiment 2, this is a rather small sample. However,
it is the best we could achieve, given the difficulty to find participants with atypical brain
asymmetry.
Method
Participants
Participants were 17 left-handed participants from Ghent University who were recruited
from the study by Van der Haegen et al. (2011). They were all identified as being clearly
atypically right lateralized for speech by the fMRI study. Participants were paid for their
participation.
Stimuli and Procedure
The stimuli and the procedure were exactly the same as in Experiments 1 and 2.
Results
The data are shown in the lower part of Figure 3. As in Experiment 2, we performed 2 x 2
ANOVAs on the RTs en PEs with VHF (2) and Stimulus type (2) as factors. There was no
significant main effect of VHF, neither for RT (LVF = 578 ms, RVF = 562 ms; F (1, 16) = 1.59,
p=.22), nor for PE (LVF = 19.2%, RVF = 16.6%; F (1, 16) = 2.24, p=.15). The main effect of
stimulus type was significant for RT (symmetric = 554 ms, asymmetric = 586 ms; F (1, 16) =
7.56, p<0.05), but not for PE (symmetric = 18.3%, asymmetric = 17.4%; F(1,16) = .09, p=.76).
Although the interaction between VHF and Stimulus type was not significant (RT: F(1,16) = .05,
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
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p=.81, PE: F(1,16) = .37, p=.55), we ran one-way anova for the symmetric and asymmetric
stimuli separately, given their central roles in our prediction. For symmetric figures, there was a
RVF advantage of 19 ms and 4.7%, but this failed to reach significance both in RT (LVF = 563
ms, RVF = 544 ms; F (1,16) = .852, p=.370) and PE (LVF = 20.7%, RVF = 16.0 %; F (1,16) =
1.415, p=0.252). For the asymmetric figures, a similar but even smaller trend to RVF advantage
was found, which was far from significant, both in RT (LVF = 592 ms, RVF = 579 ms, F (1,16)
= .699, p=.416) and PE (LVF = 17.7%, RVF = 17.1% ; F(1,16) = .034, p= 0.857).
In terms of individual scores, for the symmetric stimuli in the reaction time (RT) data
only 8 out of 17 participants had the RVF advantage predicted by the crowding hypothesis while
9 participants showed a LVF advantage. For the percentage of errors, 9 out of 17 participants
had a RVF advantage while the other 8 participants showed a LVF advantage. For the
asymmetric stimuli, in terms of reaction times 9 out of 17 participants displayed the RVF
advantage for RT and 8 out of 17 participants for PE.
To further test the relationship between speech dominance and laterality of symmetry
detection, we correlated the VHF differences in RT obtained in the present experiment with the
participants’ speech laterality indices, as reported by Van der Haegen et al. (2011). These
laterality indices were based on the difference in brain activity in Broca’s area between the left
and the right hemisphere (measured with fMRI) while the participants were silently generating
words starting with a target letter (see Van der Haegen et al., 2011, for further details about the
task and the calculation of the laterality index). This analysis was limited to the 19 left-handed
participants of Experiment 2 and the 17 left-handed participants of Experiment 3, who took part
in the earlier fMRI study, as the speech laterality index could not be calculated for the 18
additional participants of Experiment 2 and we wanted to avoid a confound with handedness
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
P.| 179
(therefore excluding the right-handed participants from Experiment 1). There was a positive
correlation of r = .299 (N = 36, p= .076) for symmetric figures (indicating that participants with a
strong LH dominance for language showed a larger LVF advantage for symmetry detection)
while only a correlation of 0.144 (N = 36, p = 0.403) was found for asymmetric figures.
Discussion
Experiment 3 revealed a trend towards a RVF advantage for parafoveal symmetry detection in
participants with atypical right hemispheric speech dominance. This finding is more in line with
the predictions of the cognitive crowding hypothesis than the statistical independence hypothesis,
which would have been confirmed if the participants with atypical speech dominance had shown
a LVF advantage as well. This suggests that the consequences of atypical speech laterality go
beyond language-related functions. Cai et al. (2013) reached the same conclusion on the basis of
the landmark task. At the same time, it must be acknowledged that there was much more
variability among the participants with atypical speech dominance, because the RVF advantage
was found in only half of the sample. As a result, the RVF advantage was not statistically
significant. So, although the data point against the statistical independence hypothesis, they do
not point against a view of more variability in participants with atypical speech dominance.
Further of interest is the observation that the VHF advantage was the same for symmetric
and asymmetric figures, in line with the results of Experiment 1 and opposite to those of
Experiment 2. A possible interpretation could be that the left-handed LH dominant participants
of Experiment 2 had their control centers for speech and dominant hand in opposite hemispheres,
whereas for all other participants these centers were in the same hemisphere (either LH or RH).
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 180
Future studies with larger samples of atypically lateralized subjects are needed to confirm
the explorative findings of Experiment 3. In conjunction with the correlational analysis of the
lateralization indices and VHF differences, these data do give a first indication that symmetry
detection lateralizes to the language non-dominant hemisphere.
General discussion
In this paper we addressed two questions:
a) Whether symmetry detection is a right hemisphere function resulting in a LVF advantage
in a VHF-paradigm.
b) Whether the VHF advantage differs in people with typical and atypical language
dominance.
For the first question we sought to replicate a pattern we discerned in the literature (Corballis
& Roldan, 1974; Brysbaert, 1994; Wilkinson & Halligan, 2002, 2003) but which had mainly
been investigated as a secondary phenomenon. Given that symmetry detection is a fast-acting
visual function and given that most visuospatial functions are lateralized to the right in the
majority of people, we hypothesized that we should observe a robust LVF advantage in a
properly run VHF task (Hunter & Brysbaert, 2008). We indeed were able to do so (Experiments
1 and 2). For the correct interpretation of this finding it is important to keep in mind that the
symmetry detection we studied consisted of symmetry outside the fixation location. As discussed
in the introduction, there is evidence that symmetry detection at fixation may be based on other
processes (Herbert & Humphrey, 1996) with bilateral involvement of the extrastriate dorsolateral
occipital cortex (Cattaneo et al., 2011; Sasaki et al., 2005; Tyler et al., 2005).
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
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We used Hugdahl’s (2000) distinction between language and visuospatial functions as the
basis of our prediction. However, we do not want to exclude the possibility that the finding is in
line with other hypotheses of brain asymmetry as well. One of these hypotheses is the spatial
frequency hypothesis (Sergent, 1983; De Valois & De Valois, 1988; Kosslyn, Chabris, Marsolek
& Koenig, 1992). According to this hypothesis, the right hemisphere is specialized in processing
low spatial frequencies, whereas the left hemisphere is better at processing high spatial
frequencies. Our data are in line with this hypothesis if we assume that the symmetry decision in
our task was based on low spatial frequency information. Indeed, some early theories postulated
that symmetry detection largely depended on low level spatial grouping (Barlow & Reeves,
1979; Julesz, 1979). However, more recent models of symmetry perception no longer assume a
dominance of low-frequency information but include filters of different frequencies and
orientations, which are used flexibly as a function of stimulus complexity (Dakin & Hess, 1997;
Poirier & Wilson, 2010).
Another hypothesis of hemispheric specialization is that the right hemisphere may be
specialized in identifying the global forms of stimuli, whereas the left hemisphere would be more
specialized at processing details (Lamb, Robertson, & Knight, 1989, 1990). Our data are in line
with this view if we can assume that the symmetry perception for our stimuli was based on the
global form of the stimulus. There indeed seem to be two particularly informative regions of
information for symmetry perception: one around the symmetry axis and one consisting of the
stimulus outline (Wenderoth, 1995).
The two alternative views illustrate that the division between language processing vs.
visuospatial processing need not be the only distinction explaining the right hemisphere
dominance for symmetry detection in the stimuli we used. An intriguing possibility of the
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P. | 182
alternative views is that different types of stimuli may induce different hemispheric superiorities
(and VHF advantages) for more complex figures or figures with asymmetries in the details. This
could also explain why not all studies have found a LVF-advantage for symmetry perception,
which is an attractive option for future research.
The second question addressed in this paper is what consequences atypical language
laterality has for the lateralization of other functions. This is still a much under-investigated issue
in brain research. At first, researchers assumed complementarity of the brain hemispheres with a
causal role of speech laterality. Lateralization of speech implied that all language-related
functions were localized in the same hemisphere, and that other functions, in particular
visuospatial functions, were forced to the other hemisphere. An example of this view is the
cognitive crowding hypothesis (Lansdell, 1969; Levy, 1969; Teuber, 1974), discussed in the
Introduction (see also Plaut & Behrmann, 2011, for a recent computational implementation of
this view).
The complementarity view was questioned by Bryden et al. (1983), who observed a higher
incidence of combined language and spatial disorders after unilateral brain damage than
predicted. In their view, the pattern of results was more in line with a statistical independence
interpretation, according to which there is bias to left lateralization of language and a bias to
right lateralization of visuospatial functions, but no cross-talk between both biases. Such an
interpretation was in line with the modularity model of the brain that became dominant in the
1980s (Fodor, 1983). According to this model, the brain consisted of several independent
(encapsulated) modules functioning autonomously. The idea was taken up by several laterality
researchers (e.g., Kosslyn, 1987; Brysbaert, 1994) and is still used as a framework for the
interpretation of brain imaging data (Badzakova-Trajkov, Häberling, Roberts, & Corballis, 2010;
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
P.| 183
Pinel & Dehaene, 2010). Surprisingly, when it was investigated in the largest group of people
with atypical speech dominance examined thus far, the statistical independence idea failed to
predict the findings (Cai et al., 2013). As a matter of fact, the findings were almost completely
in line with the complementarity view (only one exception on a total of 29 participants tested).
Our data (Experiment 3) are also more in favor of the complementarity view than the
statistical independence view. Whereas right-handed and left-handed participants with LH
speech dominance showed a LVF advantage of 30 ms and more (Experiments 1 and 2), left
handed participants with RH dominance showed a reverse RVF advantage of some 20 ms
(Experiment 3). According to the statistical independence hypothesis, atypical lateralization of
language should have had no influence on the laterality of symmetry detection and, hence, all
groups should have shown the same LVF advantage for symmetry detection. At the same time,
there was quite some variability in the data of the RH dominant participants, preventing the RVF
advantage from being significant. Therefore, it is safer to consider Experiment 3 as a pilot
experiment to be backed up and extended by future investigations.
Conclusion
In the present study, we set out to determine whether symmetry detection off fixation is a
cognitive function lateralized to the right hemisphere, like the other visuospatial functions. For
this purpose we chose a behavioral VHF task along the lines recommended by Hunter &
Brysbaert (2008). In two experiments we found a clear LVF advantage for the detection of
symmetrical figures in LH speech dominant participants. In the last experiment we observed a
trend towards a reversed RVF advantage for participants with RH speech dominance. These
findings are in line with the proposal that visuospatial functions lateralize to the brain half
opposite to the hemisphere involved in language processing (Hugdahl, 2000).
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P. | 184
References
Amunts, K. (2010) Structural Indices of Asymmetry. In K. Hugdahl , & R. Westerhausen (Eds.)
The Two Halves of the Brain (pp. 145-175). The MIT Press: Cambridge, Massachusetts,
London, England.
Atkisnon, J., & Egeth, H. (1973) Right hemisphere superiority in visual orientation matching.
Canadian Journal of Psychology, 27, 152-158.
Barlow, H.B. & Reeves, B.C. (1979).The versatility and absolute efficiency of detecting mirror
symmetry in random dot displays. Vision Research, 19, 783–93.
Bayliss, G.C. & Driver, J. (1994). Parallel computation of symmetry but not repetition within
single visual shapes. Visual Cognition, 1, 377-400.
Benton, A.L., Hannay, H.J. & Varney, N.R. (1975). Visual perception of line orientation in
patients with unilateral brain disease. Neurology, 25, 907-910.
Bornstein, M.H., Ferdinandsen, K., & Gross, C.G. (1981) Perception of symmetry in infancy.
Developmental Psychology, 17, 82-86.
Bradshaw, J.L. & Nettleton, N.C. (1981). The nature of hemispheric specialization in man.
Behavioral and Brain Sciences, 4, 51-63.
Badzakova-Trajkov, G., Häberling, I.S., Roberts, R.P., & Corballis, M.C. (2010) Cerebral
Asymmetries: Complementary and Independent Processes. PLoS ONE 5(3): e9682.
doi:10.1371/journal.pone.0009682
Bryden, M. P. (1982). Laterality: functional asymmetry in the intact brain. New York: Academic
Press.
Bryden, M.P. (1976) Response bias and hemispheric differences in dot-localization. Perception
and Psychophysics, 19, 23-28.
Bryden, M.P., Hecaen, H., & De Agostini, M. (1983) Patterns of Cerebral Organization. Brain
and Language, 20, 249-262.
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
P.| 185
Brysbaert, M. & d’Ydewalle, G. (1990). Individual analysis of laterality data. Neuropsychologia,
28, 901-916.
Brysbaert, M. (1994). Lateral preferences and visual field asymmetries: Appearances may have
been overstated. Cortex, 30, 413-429.
Cai, Q., Lavidor, M., Brysbaert, M. Paulignan, Y., & Nazir, T.A. (2008). Cerebral lateralization
of frontal lobe language processes and the lateralization of the posterior visual word
processing system. Journal of Cognitive Neuroscience, 20, 672-681.
Cai, Q., Paulignan, Y. Brysbaert, M., Ibarrola, D., & Nazir, T.A. (2010). The left ventral
occipito-temporal response to words depends on the language lateralization but not on
visual familiarity. Cerebral Cortex, 20, 1153-1163.
Cai, Q., van der Haegen, L., & Brysbaert, M. (2013). Complementary hemispheric specialization
for language production and visuospatial attention. PNAS, 110(4), e322-330.
Carmody, D.P., Nodine, C.F., & Locher, P.J. (1977). Global detection of symmetry. Perceptual
and Motor Skills, 45, 1267-1273.
Carmon, A., & Bechtoldt, H.P. (1969) Dominance of the right cerebral hemisphere for
stereopsis. Neuropsychologia, 7, 29-39.
Cattaneo, Z., Mattavelli, G., Papagno, C., Herbert, A., & Silvanto, J. (2011). The role of the
human extrastriate visual cortex in mirror symmetry discrimination: A TMS-adaptation
study. Brain and Cognition, 77, 120-127.
Corballis, M.C. & Roldan, C.E. (1974). On the perception of symmetrical and repeated patterns.
Perception and Psychophysics, 16(1), 136-142.
Cotton, S.M., Crewther, D.P., & Crewether, S.G. (2005). Measurement error: Implications for
diagnosis and discrepancy models of developmental dyslexia. Dyslexia, 11, 186-202.
Dakin, S.C. & Hess, R.F. (1997). The Spatial Mechanisms Mediating Symmetry Perception.
Vision Research, 37 (20), 2915-2930.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 186
Davidoff, J.B. (1975). Hemispheric differences in the perception of lightness. Neuropsychologia,
13, 121-124.
Davidoff, J.B. (1977) Hemispheric differences in dot detection. Cortex, 13, 434-444.
De Valois, R. L., & De Valois, K. K. (1988). Spatial Vision. Oxford University Press: New York.
Delius, J.D. & Nowak, B. (1982) Visual symmetry recognition by pigeons. Psychol. Res. 44,
199-212.
Donnely, N., Humphreys, G.W., & Riddoch, M.J. (1991). Parallel computation of primitive
shape descriptions. Journal of Experimental Psychology: Human Perception and
Performance, 17, 561-570.
Fodor, J.A. (1983). The modularity of mind. MIT Press: EH, MK, JCM.
Gates, A., & Bradshaw, J.L. (1977). Music perception and cerebral asymmetries. Cortex, 13,
390-401.
Geffen, G., Bradshaw, J.L., & Wallace, G. (1971). Interhemispheric effects on reaction time to
verbal and non-verbal visual stimuli. Journal of Experimental Psychology, 87, 415-422.
Greve, D., Van der Haegen, L., Cai, Q., Stufflebeam, S., Sabuncu, M., Fischl, B., & Brysbaert,
M. (in press). A surface-based analysis of language lateralization and cortical asymmetry.
Journal of Cognitive Neuroscience.
Gurnsey, R., Herbert, A.M., & Kenemy, J. (1998). Bilateral symmetry embedded in noise is
detected accurately only at fixation. Vision Research, 38, 3795-3803.
Hannay, H.J. (1979). Asymmetry in reception and retention of colors. Brain and Language, 8,
191-201.
Hellige, J.B. (Ed.) (1993). Hemispheric Asymmetry: What’s Right And What’s Left. Harvard
University Press: Cambridge, Massachusetts, London, England.
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
P.| 187
Hemond, C.C., Kanwisher, N.G., & Op de Beeck, H.P. (2007) A Preference for Contralateral
Stimuli in Human Object- and Face-Selective Cortex. PLoS ONE 2(6): e574.
doi:10.1371/journal.pone.0000574
Herbert, A.M. & Humphreys, G.K. (1996). Bilateral Symmetry Detection: Testing a ‘callosal’
hypothesis. Perception, 254, 463-480.
Howell, J.R. & Bryden, M.P. (1987). The effects of word orientation and imageability on visual
half-field presentations with a lexical decision task. Neuropsychologia,25,527-538.
Hugdahl, K. (2000) Lateralization of Cognitive Processes in the Brain. Acta Psychologica, 105,
211-235.
Hunter, Z. R., & Brysbaert, M. (2008). Visual half-field experiments are a good measure of
cerebral language dominance if used properly: Evidence from fMRI. Neuropsychologia,
46, 316–325.
Julesz, B., & Chang, J. (1979). Symmetry perception and spatial frequency channels. Perception,
8, 711–718.
Kimura, D., & Durnford, M. (1974) Normal studies on the functioning of the right hemisphere in
vision. In S.J. Dimond and J.G. Beaumont (Eds.) Hemisphere function in the human
brain. Elek Science: London.
Klosetrman, E., Loui, P. & Shimamura, A.P. (2009). Activation of right parietal cortex during
memory retrieval of nonlinguistic auditory stimuli. Cognitive, Affective and Behavioral
Neuroscience, 9(3), 242-248.
Knecht, S., Dra¨ger, B., Floel, A.,Lohmann, H., Breitenstein, C., Deppe, M., Henningsen, H., &
Ringelstein, E-B. (2001). Behavioural relevance of atypical language lateralization in
healthy subjects. Brain, 124, 1657– 1665.
Knecht, S., Drager, B., Deppe, M., Bobe, L., Lohmann, H., Floel, A., Ringelstein, E-B., &
Heningsen, H. (2000). Handedness and hemispheric language dominance in healthy
humans. Brain, 123, 2512–2518.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 188
Knecht, S., Jansen, A., Frank, A., van Randenborgh, J., Sommer, J., Kanowski, M., & Heinze,
H.J. (2003). How atypical is atypical language dominance?. Neuroimage, 18, 917-927.
Koffka, K. (1935) Principles of Gestalt Psychology. Harcourt, Brace and World: New York.
Kootstra, G., de Boer, B. & Schomaker, L.R.B. (2011). Predicting Eye Fixations on Complex
Visual Stimuli Using Local Symmetry. Cognitive Computation, 3(1), 223-240,
doi: 10.1007/s12559-010-9089-5.
Kosslyn, S.M. (1987). Seeing and imagining in the cerebral hemispheres: A computational
approach. Psychological Review, 94, 148-175.
Kosslyn, S.M., Chabris, C.F., Marsolek, C.J., & Koenig. O. (1992). Categorical versus
coordinate spatial relations: computational analysis and computer simulations. Journal of
Experimental Psychology: Human Perception and Performance, 18, 562–77.
Lamb, M.R., Robertson, L.C., & Knight, R.T. (1989). Attention and interference in the
processing of hierarchical patterns: inferences from patients with right and left temporal-
parietal lesions. Neuropsychologia, 17, 619–27.
Lamb, M.R., Robertson, L.C., & Knight, R.T. (1990). Component mechanisms underlying the
processing of hierarchically organised patterns: inferences from patients with unilateral
cortical lesions. Journal of Experimental Psychology: Learning and Memory , 16, 471–
83.
Lansdell, H. (1969). Verbal and non-verbal factors in right-hemisphere speech: Relationa to
early neurological history. Journal of Physiological and Comparative Psychology, 69,
734-738.
Laine, M. & Koivisto, M. (1998). Lexical access to inflected words as measured by lateralized
visual lexical decision. Psychological Research, 61, 220-229.
Levy, J. (1969). Possible basis for the evolution of lateral specialization of the human brain.
Nature, 224, 614-625.
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
P.| 189
Ley, R.G., & Bryden, M.P. (1981) The right hemisphere and emotion. In G. Underwood & R.
Stevens(Eds.) Aspects of Consciousness (Vol 2). Academinc Press: New York.
Little, A. C., & Jones, B. C. (2006). Attraction independent of detection suggests special
mechanisms for symmetry preferences in human face perception. Proceedings of the
Royal Society B, 273, 3093–3099.
Locher, P. & Wagemans, J. (1993). The effects of element type and spatial grouping on
symmetry detection. Perception, 22, 565-587.
Locher, P.J. & Nodine, C.F.(1989). The perceptual value of symmetry. Comp. Math. Appl., 17,
475-484.
Machilsen, B., Pauwels, M., & Wagemans, J. (2009). The role of vertical mirror symmetry in
visual shape detection. Journal of Vision, 9, 1-11.
Marinkovic, K., Baldwin, S., Courtney, M.G., Witzel, T., Dale, A.M., & Halgren, E. (2011)
Right hemisphere has the last laugh: neural dynamics of joke appreciation. Cognitve
Affective Begavioral Neuroscience, 11, 113-130. DOI 10.3758/s13415-010-0017-7
Marr, D. (1982) Vision: A computational investigation into the human representation and
processing of visual information. Freeman: San Fransisco, CA.
Mashal N., Faust, M., Hendler, T., & Jung-Beeman, M. (2008) Hemispheric differences in
processing the literal interpretation of idioms: Converging evidence from behavioral and
fMRI studies, Cortex, 1-13, doi:10.1016/j.cortex.2007.04.004
Masson, M. E. J., & Loftus, G. R. (2003). Using confidence intervals for graphically based data
interpretation. Canadian Journal of Experimental Psychology, 57, 203-220.
Measso, G. & Zaidel, E. (1990). Effect of response programming on hemispheric differences in
lexical decision. Neuropsychologia, 28(7), 635-646.
McManus, I. C. (1985). Handedness, language dominance and aphasia: a genetic model.
Cambridge University Press: Psychological Medicine, Monograph Supplement No.8.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 190
Miles, W. R. (1930). Ocular dominance in human adults. Journal of General Psychology, 3,
412–420.
Mohr, B., Pulvermuller, F. & Zaidel, E. (1994). Lexical decision after left, right, and bilateral
presentation of function words, content words and non-words: Evidence for
interhemispheric interaction. Neuropsychologia, 32(1), 105-124.
Nieto, A., Santacruz, R., Hernandez., Camacho-Rosales, J. & Barraso., J. (1999). Hemispheric
Asymmetry in Lexical Decisions: The effects of Grammatical Class and Imageability.
Brain and Language, 70, 421-436.
Oldfield, R.C. (1971). The Assesment and Analysis of Handedness: The Edinburgh Inventory.
Neuropsychologia, 9, 97-113.
Olivers, C. N. L, & van der Helm, P. A. (1998). Symmetry and selective attention: A
dissociation between effortless perception and serial search. Perception & Psychophysics,
60, 1101-1116.
Pennal, B.E. (1977). Human cerebral asymmetry in color discrimination. Neuropsychologia, 15,
563-578.
Pinel, P., & Dehaene, S. (2010). Beyond Hemispheric Dominance: Brain Regions Underlying the
Joint Lateralization of Language and Arithmetic to the Left Hemisphere. Journal of
Cognitive Neuroscience, 22(1), 48-66.
Plaut, D.C., & Behrmann, M. (2011). Complementary neural representations for faces and
words: A computational exploration. Cognitive Neuropsychology, 28, 251-275.
Poirier, F.J.A.M. & Wilson, H.R. (2010). A biologically plausible model of human shape
symmetry perception. Journal of Vision, 10(1):9, 1-16.
Porac, C., & Coren, S. (1981). Lateral preferences and human behavior. New York: Springer-
Verlag.
Rhodes, G., Peters, M., Lee, K., Morrone, M. C., & Burr, D. (2005). Higher-level mechanisms
detect facial symmetry. Proceedings of the Royal Society, 272, 1379–1384.
Chapter 4|Symmetry Detection in Typically and Atypically Lateralized Individuals
P.| 191
Roddy, G., & Gurnsey, R. (2011). Mirror symmetry is subject to crowding. Symmetry, 3, 457-
471.
Royer, F.L. (1981). Detection of symmetry. Journal of Experimental Psychology: Human
Perception and Performance, 7, 1186-1210.
Sasaki, Y., Vanduffel, W., Knutsen, T., Tyler, C. & Tootell, R. (2005). Symmetry activates
extrastriate visual cortex in human and nonhuman primates. Proceedings of the National
Academy of Sciences of the United States of America, 102, 3159-3163. [Pubmed][Article]
Sergent, J. (1983). The role of the input in visual hemispheric asymmetries. Psychological
Bulletin, 93, 481-514.
Shulman, G.L., Pope, D.L.W., Astafiev, S.V., McAvoy, M.P., Snyder, A.Z., & Corbetta, M.
(2010) Right Hemisphere Dominance During Spatial Selective Attention and Target
Detection Occurs Outside the Dorsal Fronto-Parietal Network. The Journal of
Neuroscience, 30(10), 3640-3651.
Teuber, H.L. (1974). Why Two Brains? In F. O. Schmidts and F.G. Worden (Eds.) The
neurosciences: Third study program, (pp. 71-74). MIT Press: Cambridge, MA.
Troje, N. F., & Bulthoff, H. H. (1997). How is bilateral symmetry of human faces used for
recognition of novel views? Vision Research, 38, 78–89.
Tyler, C.W., Baseler, H.A., Kontsevich, L.L., Likova, L.T., Wade, A.R. & Wandell, B.A. (2005).
Predominantly extra-retinotopic cortical response to pattern symmetry. NeuroImage, 24,
306-314.
Umilta, C., Salmaso, D., Bagnara, S., & Simion, F. (1979) Evidence for right-hemisphere
superiority and for a serial search strategy in a dot detection task. Cortex, 15, 597-608.
Van der Haegen, L., Cai, Q., & Brysbaert, M. (2012). Colateralization of Broca's area and the
visual word form area in left-handers : fMRI evidence. Brain and Language, 122, 171-
178.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 192
Van der Haegen, L., Cai, Q., Seurinck, R., & Brysbaert, M. (2011). Further fMRI validation of
the visual half field technique as an indicator of language laterality: A large-group
analysis. Neuropsychologia, 49, 2879-2888.
Vingerhoets, G., Alderweireldt, A., Vandemaele, P., Cai, Q., Van der Haegen,
L., Brysbaert, M., & Achten, E. (in press). Praxis and language are linked:
Evidence from co-lateralization in individuals with atypical language
dominance. Cortex.
Wagemans J, van Gool L, Swinnen V, & van Horebeek J. (1993). Higher-order structure in
regularity detection. Vision Research, 8, 1067–1088.
Wagemans, J. (1995) Detection of visual symmetries. Spatial Vision, 9(1), 9-32.
Walker, R., & McSorley, E. (2006). The parallel programming of voluntary and reflexive
saccades. Vision Research, 46, 2082–2093.
Wenderoth, P. (1995). The role of pattern outline in bilateral symmetry detection with briefly
flashed dot patterns. Spatial Vision, 9, 57-77. [PubMed]
Wenderoth, P. (1995). The role of pattern outline in bilateral symmetry detection with briefly
flashed dot patterns. In C.W. Tyler (Ed.), Human symmetry perception and its
computational analysis (pp. 49-70). Mahwah, NJ: Lawrence Erlbaum Associates.
Whitehouse, A.J.O., & Bishop, D.V.M. (2009) Hemispheric division of function is the result of
independent probabilistic biases. Neuropsychologia, 47 (8-9), 1938-1943.
Wilkinson, D.T. & Halligan, P.W. (2002). The effects of stimulus symmetry on landmark
judgments in left and right visual fields. Neuropsychologia, 1045-1058.
Wilkinson, D.T. & Halligan, P.W. (2003). Stimulus symmetry affects the bisection of figures but
not lines: evidence from event-related fMRI. Neuroimage, 20, 1756-1764.
Yovel, G., Tambini, A., & Brandman, T. (2008). The asymmetry of the fusiform face area is a
stable individual characteristic that underlies the left-visual field superiority for faces.
Neuropsychologia, 46, 3061-3068.
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Chapter 5: Evidence for Right Hemisphere
Superiority in Figure Matching & Judging Negative
Emotions from Facial Expressions
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Chapter 5|Evidence for right hemisphere superiority in figure matching and judging negative emotions
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Chapter 5: Evidence for Right Hemisphere Superiority in Figure
Matching & Judging Negative Emotions from Facial Expressions
While there has been plenty of research investigating the lateralization of left-hemisphere
cognitive functions, limited research has been conducted on right hemisphere functions. In this
study, we investigated the lateralization of figure comparison using our VHF paradigm and also
sought to compare existing theories of facial emotion recognition i.e. right hemisphere
hypothesis& the valence hypothesis, respectively. We were able to replicate a significant
LVF/right hemisphere advantage for figure comparison. The results for the facial emotion
recognition experiments were not conclusive, though indications favored the right hemisphere
hypothesis. Finally, we were able to discern that participants are faster for responding to ‘yes’
responses with their index fingers; in the experiments using our HF-paradigm.
Introduction
For several decades, functional asymmetries between the two cerebral hemispheres have
been the focal point of laterality research. Asymmetries have been reported for both structure and
function of the two hemispheres (for a review on structural asymmetry see Amunts, 2010; for a
review on functional asymmetries, see Hugdahl & Westerhausen, 2010).
Several of the observed asymmetries in behavior have been viewed together as
dichotomies of function between the two hemispheres of the brain. Common examples are:
language versus visuospatial functions (Davidson & Hugdahl, 1995), local versus global
processing (Bradshaw & Nettleton, 1981), categorical versus co-ordinate decisions (Kosslyn,
1987) and processing of high versus low spatial frequencies (Sergent, 1983). Hugdahl (2000)
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points out that of all these dichotomies, only the language versus visuo-spatial processing
dichotomy has given the most consistent account of experimental results over time.
While there has been a large body of research involving language/verbal material
supporting left/dominant hemisphere superiority, studies of cerebral laterality with visuo-spatial
measures have been less numerous (Gur et al., 2000; Unterrainer et al., 2000 & Kimura, 2004).
One of the reasons for this could be that few tasks used in the visuo-spatial paradigms were
found to produce the same consistent and robust results as exhibited by the word- processing
paradigms, which yield reliable and replicable evidence for a left hemisphere advantage
(Whitehouse, Badcock, Groen & Bishop, 2009). Consequently, there has been a disparity in the
amount of research dedicated to the functions of the left compared to the right hemisphere. This
presents a case for encouraging more research with right hemisphere capabilities; and recently a
number of researchers have taken up the challenge.
Most of the early research about right hemisphere functions used the visual half field
paradigm, which makes use of the organization of the human visual system to judge the
adeptness of a particular hemisphere at a particular task by tachistoscopically presenting stimuli
to either the left or the right visual half-fields (LVF or RVF). Better performance on the stimuli
presented in the left visual field is taken as evidence for superior right hemisphere stimulus
processing and vice-a-versa.
With this paradigm the right hemisphere was found to be efficient at a variety of visual
and spatial processing tasks, such as: spatial abilities (Benton, Hannay & Varney, 1975), face
recognition (Geffen, Bradshaw & Wallace, 1971), identification of emotional expression (Ley, &
Bryden, 1979), lightness discrimination (Davidoff, 1975), color perception (Hannay, 1979), dot
Chapter 5|Evidence for right hemisphere superiority in figure matching and judging negative emotions
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localization (Bryden, 1976), line orientation (Atkinson & Egeth, 1973) and depth perception
(Kimural & Durnford, 1971). Most of the time, however, the left visual field advantage was
small, suggesting that the right hemisphere superiority was not due to unilateral specialization
but due to relative degrees of lateralization.
In recent times, the use of neuroimaging technology has extended and validated the
earlier behavioral findings about right hemisphere functions. In fMRI studies, the right
hemisphere has additionally been found to mediate in spatial attention (Shulman, Pope, Astafiev,
McAvoy, Snyder & Corbetta 2010), solving semantic ambiguities (Mashal, Faust, Hendler &
Jung-Beeman, 2008), joke appreciation (Marinkovic, Baldwin, Cortney, Witzel, Dale, and
Haldgren, 2011), and even appreciating agrammatical musical sequences (Klostermann, Loui &
Shimamura, 2009). Others like Yovel, Tambini, & Brandman (2008) and Hemond, Kanwisher &
Op de Beeck (2007) found dedicated areas in the right hemisphere; specifically the fusiform
gyrus related to face processing.
In a TMS study, Battelli, Herpich, Tyler, Grossman & Agosta (2013) found evidence for
a major role of the right hemisphere in temporal aspects of attention. Also in a TMS study,
Hirnstein, Westerhausen & Hugdahl (2013) found a role for the right planum temporal (PT) in
stimulus selection and (stimulus driven) auditory attention. Finally, Bona, Herbert, Toneatto,
Silvanto & Cattaneo (2013) found evidence for right hemisphere specialization in symmetry
detection and grouping in an fMRI-guided TMS study.
All in all, with improvements in methodology there has been an array of findings in
recent times illuminating the various functions in which the right hemisphere takes the lead.
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In the current series of experiments we investigate whether the results with the visual
half-field paradigm become more convincing if we use our own visual half-field protocol
(Hunter & Brysbaert, 2008; Verma & Brysbaert, 2011; Verma, van der Haegen & Brysbaert,
2013). This protocol stresses the importance of bilateral stimulus presentation, bimanual
responses, the use of matched stimuli in the visual half-fields, and the need for a sufficiently
large number of trials to get stable results.
Using this paradigm we have demonstrated reliable right hemisphere superiority for
symmetry detection in typically lateralized right and left handed individuals, whereas indications
of reversed left hemisphere superiority for symmetry detection in atypically lateralized left
handed individuals were observed (Verma, et al., 2013). The results regarding symmetry
detection from the visual half-field paradigm have already been corroborated by similar findings
from a TMS study reported by Bona et al. (2013). Also, the same paradigm has been used
successfully for replicating twice the left hemisphere lateralization for tool recognition reported
in neuroimaging studies (Verma & Brysbaert, 2011, submitted). Hence, we had good hopes that
this particular visual half-field paradigm could return more consistent left visual field advantages
than reported in the past. We decided to concentrate on two right hemisphere functions, which
fall in the purview of visual processing, i.e. figure comparison and facial emotion perception.
Figure comparison involves asking participants to compare a black irregular polygon
presented in the target visual field (left or right) to a same or different polygon presented 200 ms
earlier in central vision. Participants have to indicate by means of a bimanual key press response
whether the comparison and target polygons match or not. Performance is measured in terms of
reaction times (RTs) and accuracy. This particular task has been used in a series of experiments
by (Hausmann and Gunturkun (1999, 2000) and is reported to reveal a robust left visual field
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advantage, hence indicating a right hemisphere involvement (Rode et al., 1995; Hausmann &
Gunturkun, 1999; Hausmann, Becker, Gather & Gunturkun, 2002). One likely reason for this is
that the polygons cannot be named easily and hence require visuo-spatial processing to be
compared.
The other right hemisphere function we have chosen to investigate involves judgment of
emotion from facial expressions. Recognizing emotions embedded in facial expressions, is a
specialized function that requires a fair degree of sophistication. At least two types of
information need to be accessed when interacting with faces, i.e. identity of the face & the
emotional expression on the face. Evidence indicates that these two information channels may be
handled by separable and independent subsystems (Bruce & Young, 1986; Young, McWeeny,
Hay & Ellis, 1986; Posamentier, & Abdi, 2003). It is known that the processes involved in the
identification of emotional expression from faces engage the right and the left hemispheres
differentially, though the exact role of the hemispheres is still a cause of considerable debate
(Adolphs, Jansari & Tranel, 2001; Najit, Bayer & Hausmann, 2013).
Two major theories have been put forward to explain the functional cerebral asymmetry
for perception of emotion from faces, namely the Right Hemisphere Hypothesis and the Valence
Specific Hypothesis (Adolphs, et al., 2001). The right hemisphere hypothesis proposes that all
emotions are processed preferentially by the right hemisphere whereas the valence specific
hypothesis postulates that the right hemisphere is specialized for processing negative emotions
(anger, fear, sadness & disgust) and the left hemisphere for processing positive emotions
(happiness, surprise) (Najit et al., 2013, Adoplhs, et al., 2001).
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A number of studies have used the VHF paradigm to evaluate the competing hypotheses
(Hugdahl, Iversen, Ness & Flaten, 1989; Hugdahl, Iversen & Johnsen, 1993; Van Strien & Van
Beek, 2000; Rodway, Wright & Hardie, 2003; Alves, Aznar-Casanova, & Fukusima, 2009;
Stafford & Bandaro, 2010; Jansari, Rodway & Gonclaves, 2011). Typically, such a study
involves presenting emotionally salient human or chimeric faces to either the left visual half field
or the right visual half field, or both; and participants are asked to identify, discriminate or match
the facial expression of the target stimuli (Najit, et al., 2013). Performances in the respective
visual fields are compared to assess the involvement of each hemisphere in emotion recognition
as a whole and also their efficiency in processing specific emotions.
Evidence has been reported for both the right hemisphere hypothesis (Borod, Cicero,
Obler, Welkowitz, Erhan, Santschi, Grunwald, Agosti & Whalen, 1998; Burt & Perrett, 1997)
and the valence specific hypothesis (Canli, 1999; Jansari, Tranel & Adolphs, 2000; Adolphs, et
al., 2001). Furthermore, the task has been used to compare the hemispheric asymmetry for facial
emotion perception in left and right-handed participants and reported evidence indicating that the
right hemisphere advantage in facial emotion perception is independent of handedness (van
Strien and van Beek, 2000). A recent study, which also reviewed the earlier literature on the
competing hypotheses, also failed to find conclusive evidence in favor of either the right
hemisphere or the valence specific hypothesis. Instead they reported a consistent right
hemisphere advantage for a subset of negative emotions only, i.e. anger, fear & sadness
suggesting a “negative valence model” (Najit et al., 2013).
In the first experiment of this study we asked participants to match a black irregular
polygon presented centrally to a polygon presented 200 milliseconds later in a target visual field
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(left or right) indicated by a central arrow. Going by the literature, we hypothesized a clear left
visual field/right hemisphere advantage for this task.
For facial emotion perception, we decided to compare instances of a positive emotion
(happiness) with two different instances of negative emotions (sadness & disgust) in separate
experiments. Accordingly, in the second experiment we compared the recognition of happy
versus sad faces and in the third experiment we compared the recognition of happy versus
disgusted faces. If the right hemisphere hypothesis holds, an overall left visual field/right
hemisphere advantage should be found across the two experiments on all types of emotional
faces; else a left visual field/right hemisphere advantage should be found for sad & disgusted
faces, while a right visual field/left hemisphere advantage should be found for the happy faces in
the two experiments.
Experiment 1: Figure Matching Experiment
Method
Apparatus
The experiment was carried out using a 17” CRT monitor placed at a distance of 80 cm
from the participant. The experiment was carried out using the presentation software E-Prime
2.0. A response box was used to register bi-manual key-press responses.
Participants
Forty-one right-handed undergraduate students from the Gent University participated in the
experiment. They were paid 15 € to participate in the session.
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Stimuli
The stimuli consisted of 80 filled black irregular polygons, having an unfixed number of
sides; sized at 150 x 150 pixels. These stimuli have also been used in earlier studies (Rode et al.,
1995; Hausmann & Gunturkun, 1999; Hausmann, Becker, Gather & Gunturkun, 2002). Some
examples are given in figure 1.
Figure 1: Examples of the irregular polygons used in Exp. 1. In total 80 different polygons
were used in the experiment so that they could not easily be learned.
Procedure
Before the start of the main session participants were familiarized with the stimuli used in
the experiment. A trial started with a blank screen presented for 1000ms; followed by a fixation
cross presented at the centre of the screen for 300ms. The fixation cross was replaced by a
polygon presented at the same location for 200ms. A slide with an arrow at the center and one
polygon on each side of the arrow was presented after that, again for 200ms. The arrow could
point either towards the LVF or the RVF and the participants were to respond to the visual field
pointed to by the arrow. The stimulus offset was replaced by a blank screen, as there was no
mask presented. Participants responded to the blank screen and decided whether the polygon
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presented at the indicated visual field matched the centrally presented polygon by pressing with
the index fingers of both hands on the response box; if not, they pressed with the middle fingers
of both hands. There were 8 types of trails keeping the 3 factors (VHF, Match, and
Compatibility) in mind. Compatible trials here refer to the cases where stimuli in both the visual
fields matched the central polygon; all other instances would be considered incompatible trials.
Overall, there were 60 instances of the 8 types of trials in mind; hence in total 480 trials divided
into two blocks and presented in two blocks. Reaction times and accuracy were measured.
Reaction time measurement began at stimulus offset, when the blank screen appeared; the upper
limit was set at 3000 ms.
Results
The results of the first experiment are shown in Table 1. For the RT analyses, only the
correct trials were included. We started with a 2 x 2 x 2 ANOVA keeping VHF (2; LVF, RVF),
Match (2, Matched, Unmatched) and Compatibility (Compatible, Incompatible) as factors. The
main effect of visual half field turned out to be insignificant, F (1, 40) = 0.97, p>.05. The main
effect of match, came out to be significant, F (1, 40) = 35.77, p< 0.01; indicating that the match
trials were faster (Match = 472 ms, Unmatch = 505ms). The main effect of compatibility was
also found to be significant, F (1, 40) = 12.17, p< 0.01; indicating that the trials on which
compatible i.e. similar information was presented to both the visual half fields were faster
(Compatible = 478ms, Incompatible = 498ms). The significant interactions were, VHF x Match,
F (1, 40) = 8.91, p < 0.01; VHF x Compatibilty, F (1, 40) = 13.21, p< 0.01 and Match x
Compatibilty, F (1, 40) = 12.42, p < 0.01. We also compared the reaction times for match trials
in the incompatible condition for the left and right visual half fields respectively, and found a
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significant left visual field advantage for match trials; F (1,40) = 4.00, p< 0.05; indicating that
match trials in the left visual field were faster (LVF = 467ms, vs. RVF = 484ms).
---------------------------------------------------------------------------------------------------------------------
Match Unmatch
LVF RVF LVF RVF
Compatible 472 (79%) 465 (76%) 503 (89%) 473 (77%)
Incompatible 467 (83%) 484 (80%) 522 (88%) 521 (88%)
--------------------------------------------------------------------------------------------------------------------
Table 1: The performance of participants in reaction times (and percentage accuracy) for
the different conditions. The difference in incompatible match trials over the left and right
visual fields of 17 ms was significant.
---------------------------------------------------------------------------------------------------------------------
For the data on percentage accuracy, we followed the same analysis scheme. We again
first performed the 2 x 2 x 2 ANOVA keeping VHf (2; lvf, rvf), Match (2; match, unmatch) and
Compatibility (2; compatible, incompatible) as factors. The Main effect of visual half field
turned out to be significant, F (1, 40) = 5.93, p < 0.05 (p = .019); indicating that the participants
were more accurate in the left visual field. Further, the main effect of Match, also came out to be
significant, F (1, 40) = 11.62, p< 0.01. Finally, the main effect of compatibility was found to be
significant as well, F (1, 40) = 6.95, p < 0.05 (p = 0.012). Significant interactions were, VHF x
Compatibility, F (1, 40) = 5.01, p<.05; and VHF x Match x Compatibility, F (1, 40) = 17.25,
p<.01.
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Discussion
Experiment 1 was set up to see whether our VHF paradigm (Hunter & Brysbaert, 2008;
Verma & Brysbaert, 2011; Verma, van der Haegen & Brysbaert, 2013) would give stronger
evidence for right hemisphere involvement in figure matching than the existing paradigms. The
results confirm the hypothesis of a left visual half-field/right hemisphere superiority (especially
for the accuracy data), but can hardly be called overly convincing. In particular, for the
compatible trials, there was a tendency for RVF advantage in RTs (but not in accuracy).
Remember than in these trials, the same pictures were presented in LVF and RVF and
participants had to respond to the picture indicated by the arrow. The clearest results were found
on the incompatible - match trials where two difference pictures were show and the picture to be
responded to, agreed with the previous comparison picture shown in central vision. We will
return to this condition in the General Discussion. First we present the data of the emotion
recognition experiments.
Experiment 2: Happy-Sad Facial Emotion Recognition
Method
Apparatus
The apparatus used in Experiment 1 was also used in this experiment.
Participants
The same participants, who participated in the earlier experiment, took part in this experiment.
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Stimuli
57 Happy & Sad faces of the same persons were used as stimuli; obtained from the Radboud
Faces Database (RaFD) (Langner, Dotsch, Bijlstra, Wigboldus, Hawk & Knippenberg, 2010).
All the faces were sized at 150 x 226 pixels. Figure 2 shows two examples.
Procedure
All the participants were familiarized with the faces stimuli before the start of the main
experimental session. A trial started with a blank screen for 1000ms, followed by a fixation cross
presented for 300ms. Later, a slide with an arrow presented at the center and a face stimulus on
both sides of the arrow, was presented for 200ms. The face stimuli on the two sides of the arrow
could be either happy or sad, or both happy or both sad. A difference with Experiment 1 was that
the identity of the faces differed in LVF and RVF, so that the same picture was not shown in
both VHFs. The central arrow could either point towards the LVF or the RVF and the
participants had to respond to the visual field indicated by the arrow. Participants were instructed
to decide whether the face stimulus in the target visual field was happy or sad. Participants
responded to a blank screen at the offset of the slide with the arrow and two face stimuli. The
blank screen stayed on till a maximum of 1500 ms or terminated as soon as the key press
response was made.
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Figure 2: Examples of happy and sad stimuli used in Experiment 2.
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To indicate a happy face, the participants were asked to press with the index fingers of
both hands; and to indicate a sad face, they were asked to press with the middle fingers of both
hands. Keeping the three factors in minds (VHF, Facial expression & Compatibility) there were
8 types of trials. The main experimental session consisted of 50 x 8 types of trials, leading to
overall 400 trials divided over two blocks presented to the participants with a gap of 3-4 minutes.
The main experimental session was preceded by a practice block which consisted of 40 trials.
Results
The results are shown in Table 2.
---------------------------------------------------------------------------------------------------------------------
Compatible Incompatible
LVF RVF LVF RVF
Happy 411 (85%) 418 (84 %) 415 (85%) 428 (85%)
Sad 449 (86%) 456 (85%) 463 (86%) 475 (84%)
----------------------------------------------------------------------------------------------------------------------------
Table 2: Depicting the performance of participants in reaction times (percentage accuracy)
in the Happy-Sad experiment
---------------------------------------------------------------------------------------------------------------------
The RT analysis was limited to the correct trials. In a 2 x 2 x 2 ANOVA with VHF (2;
lvf, rvf), Facial expression (2; happy, sad) and Compatibility (2; compatible, incompatible) as
Chapter 5|Evidence for right hemisphere superiority in figure matching and judging negative emotions
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factors, the main effect of visual half-field was marginally significant, F (1, 40) = 3.24, p = .07;
hinting towards the finding that across all stimuli participants were slightly faster in the lvf than
in the rvf (lvf = 435 ms vs rvf = 444 ms). Another significant main effect was Face type, F (1,
40) =60.56, p< 0.01; indicating that participants were faster for happy faces than sad faces.
(Happy face = 418 ms vs. Sad face = 461 ms). Finally, the main effect of compatibility was also
found to be significant. F (1, 40) = 19.17, p< 0.01; indicating that participants were faster for
compatible trials (Compatible = 433 ms vs. Incompatible = 446 ms). None of the interaction
effects came out significant.
We also did separate ANOVAs for the happy and sad faces. For the happy faces, we did a
2 x 2 ANOVA keeping VHF (2; Lvf, rvf) and Compatibility (2; compatible, incompatible) as
factors. The main effects of visual half field and compatibility came out to be non-significant.
Also, the interaction between vhf x compatibility was found to be non significant.
For the sad faces, the same 2 x 2 ANOVA was performed keeping VHF (2; Lvf, rvf) and
Compatibility (2; compatible, incompatible) as factors. For the sad faces, the main effect of
visual half field was found to be insignificant. The main effect of compatibility was found to be
significant, F (1, 40) = 25.86, p< 0.01. The interaction between VHF x Compatibility did not
come out as significant.
For percentages of accuracy, we carried out an omnibus ANOVA, which had 3 factors
(VHF(2) X Face (2) X Compatibility(2). None of the main effects came out as significant. There
were no differences in terms of visual half-field (LVF= 85.9 pc vs. RVF = 85.1 pc); face type
(happy = 85.2 pc vs. sad = 85.8 pc) and even compatibility (incompatible = 85.6 pc vs.
compatible = 85.3 pc). None of the interactions between the three factors were significant.
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Discussion
The data from Experiment 2 again provide limited support for a right hemisphere
involvement in het perception of emotion on human faces. There was a next to significant LVF
advantage across the board, which was the same for happy and sad faces. This finding is in line
with the right hemisphere hypothesis, and against the valence specific hypothesis (sees the
introduction). More important (and disappointing) for us was the finding that the LVF advantage
turned out to be rather weak, making it difficult to introduce manipulations in the design and
examine the effects.
While preparing the stimulus materials for Experiment 2, it struck us that for most faces
the teeth were visible when the person was happy (see Figure 2). To investigate the impact of
this possible confound, we included a third experiment, in which the teeth were visible in the
conditions with both positive and negative emotions. This was possible by comparing happy
versus disgusted emotions (Figure 3). The face stimuli with disgusted facial expression are
comparable to the stimuli with happy facial expression, as the teeth are equally visible in both
the cases and the only difference is the facial expression. Furthermore, the disgusted expression
also serves as a good candidate to test the valence specific hypothesis because it is a “negative
valence” expression.
Experiment 3: Happy-Disgusted Facial Emotion Recognition
In Experiment 3, we compared the face stimuli with happy and disgusted facial
expressions.
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Method
Apparatus
The same apparatus that was used in the earlier experiments was used in this experiment.
Participants
The same participants, who took part in the earlier two experiments, participated in this
experiment too.
Stimuli
The 57 happy faces used in the earlier experiment were used in combination with faces of
the same persons bearing the disgusted expression obtained from the Radboud Faces Database
(RaFD) (Langner, Dotsch, Bijlstra, Wigboldus, Hawk & Knippenberg, 2010).
Procedure
All the participants were familiarized by the faces stimuli before the start of the main
experimental session. A trial started with a blank screen for 1000ms, followed by a fixation cross
presented for 300ms. Later, a slide with an arrow presented at the center and a face stimulus on
each side of the arrow, was presented for 200ms. The face stimuli on the two sides of the arrow
could be either happy or disgusted, or both happy or both disgusted. As in Experiment 2, the
faces were always from different persons. The central arrow could either point towards the LVF
or the RVF and the participants had to respond to the visual field indicated by the arrow.
Participants were instructed to decide whether the face stimulus in the target visual field was
happy or disgusted. Participants responded to a blank screen at the offset of the slide with the
arrow and two face stimuli. The blank screen stayed on till a maximum of 1500 ms or terminated
as soon as the key press response was made.
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P. | 214
Figure 3: The stimuli used in Experiment 3. When people show a disgusted face their teeth
are visible, just as when they are laughing. This allowed us to check whether the visibility
of the teeth was responsible for the data observed in Experiment 2.
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To indicate a disgusted face, the participants were asked to press with the index fingers of
both hands; and to indicate a happy face, they were asked to press with the middle fingers of
both hands. Keeping the three factors in minds (VHF, Face & Compatibility) there were 8 types
of trials. The main experimental session consisted of 50 x 8 types of trials, lead to overall 400
trials divided into two blocks presented to the participants with a gap of 3-4 minutes. The main
experimental session was preceded by a practice block which consisted of 40 trials.
Results
The main findings are shown in Table 3.
---------------------------------------------------------------------------------------------------------------------
Compatible Incompatible
LVF RVF LVF RVF
Happy 498(77%) 501 (77 %) 503 (74%) 513 (74%)
Disgusted 465 (81%) 478 (78%) 484 (78%) 500 (77%)
---------------------------------------------------------------------------------------------------------------------------
Table 3: The performance of the participants in reaction times (and percentage accuracy)
in the Happy-Disgusted experiment.
---------------------------------------------------------------------------------------------------------------------
The analyses of the RT data were limited to correct trials only. We began by a 2 x 2 x 2
ANOVA, with VHF (2; lvf, rvf), Facial expression (2; happy, disgusted) and Compatibility (2;
compatible, incompatible) as factors. In this ANOVA, the main effect of VHF did not turn out to
be significant, F (1, 40) = 2.74, p > 0.05. In contrast, the main effect of face type was significant,
F (1, 40) = 13.41, p < 0.01; indicating that the participants were faster for the disgusted faces
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 216
(Happy = 504 ms vs. Disgusted = 482 ms). The other significant main effect was of
compatibility, F (1, 40) = 15.33, p < 0.01; indicating that the participants were faster for
compatible trials. The only other significant effect was the interaction between face x
compatibility, F (1, 40) = 5.87, p < 0.05, because the compatibility effect was larger for
disgusted faces than for happy faces.
For the sake of clarity, we also performed 2 x 2 ANOVAs with VHF (lvf, rvf)) and
compatibility (compatible, incompatible) as factors for the happy and disgusted faces separately.
For the disgusted faces, we found a next to significant effect of visual field F (1,40) = 3.23, p =
0.08; hinting at the fact that the participants were slightly faster in recognizing the disgusting
faces presented in the left visual field (lvf = 474 ms vs. rvf = 489 ms). The main effect of
compatibility was also found to be significant, F (1, 40) = 17.29, p < 0.01; indicating that the
participants were faster for compatible trials (compatible = 471ms vs. incompatible = 492 ms).
The interaction between vhf x compatibility was not significant.
For the happy faces, the main effect of Compatibility was, F (1, 40) = 4.49, p < 0.05;
indicating that the participants were faster on compatible trials (compatible = 500 ms vs.
incompatible = 508 ms). The main effect of VHF was not significant (LVF = 501 ms vs. RVF =
507 ms); also the interaction between VHF x Compatibility was not significant.
The analysis of percentage accuracy data followed the same scheme as that of the RTs. In
the omnibus ANOVA none of the main effects was significant; no differences were observed in
terms of VHF (LVF = 77.7 pc vs. RVF = 76.7 pc), Face (Happy = 75.9 pc vs. Disgusted = 78.6
pc) or Compatibility (incompatible = 76.0 pc vs. compatible = 78.5 pc). Given these null effect,
we do not report the separate analyses for the happy and disgusted faces.
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Discussion
There are two noteworthy findings in this experiment. The first is that we again find weak
evidence for a LVF advantage, in line with the right hemisphere hypothesis for emotional
processing. The findings are very similar to those of Experiment 2, making it unlikely that the
results of Experiment 2 were a confound of the visibility of the teeth in the happy conditions.
A second remarkable finding is that the responses to the happy faces in Experiment 3 are
slower than those to the disgusted faces, whereas in Experiment 2 they were faster than those to
the sad faces. This suggests that positive emotions are not always responded to faster than
negative emotions. As a matter of fact, it looks like the difference between the emotions may be
part of a larger pattern we can discern in our paradigm.
One of the features of our paradigm is that the participants have to make binary decisions.
These usually are yes-no decisions (tool vs. non-tool, object vs. non-object, symmetric vs. not,
similar or not). Throughout the experiments, we found that responses to the yes-trials were faster
than those to the no-trials. In addition, the VHF asymmetry was larger for the yes-trials than for
the no-trials.
What Experiments 2 and 3 suggest is that not so much the yes-no distinction is important,
but the distinction between responding with the digits vs. the middle fingers. There is a
considerable literature in experimental psychology about so-called markedness effects.
‘Markedness’ refers to a condition in which the response alternatives do not have equal strength,
but one is dominant over the other or is preferentially associated with one type of response than
with another. In numerical cognition, for instance, it has been noticed that even numbers are
faster responded to with the right hand, whereas the reverse is true for odd numbers. This is
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
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called the linguistic markedness association of response codes (MARC) effect (Willmes &
Iversen, 1995; Neurk, Iversen & Willmes, 2004; Cho & Proctor, 2007). Berch et al. (1999)
proposed that the MARC effect is due to “compatibility between the linguistically marked
adjectives ‘left’ and ‘odd’ and the unmarked adjectives ‘right’ and ‘even’” (p. 296).
Proctor and Cho (2006), in their polarity correspondence account, attributed the
markedness effects to a tendency participants have to translate response alternatives along a ‘+’
vs ‘-’ polarity dimension. In this view markedness can be considered as a form of polarity coding
(Cho & Proctor, 2007). Among the various tasks to which the polarity correspondence account
applies, we find up vs. down, right vs. left mapping, even vs. odd, above vs. below (Cho &
Proctor, 2003; Proctor, Wang & Wu, 2002; Weeks & Proctor, 1990). To this sequence we could
add: digits vs. middle fingers.
Indeed, when we look back upon the series of experiment run in this thesis, we always
find that the digit responses are faster than the middle-finger responses, and tend to show
stronger VHF asymmetries. What Experiments 2 and 3 suggest, is that the fingers indeed may
make the difference, rather than the allocation of responses to the fingers. Indeed, the positive
emotion happiness was responded to faster in Experiment 2 than the negative emotion sadness
but the negative emotion disgust was responded to faster in Experiment 3 than the positive
emotion happiness (the ideal test would, of course, be to compare the same emotions in both
experiments, assigned to the different fingers; unfortunately, there was no time any more to run
this pair of experiments).
To get an idea of the statistical robustness of the polarity effect in our paradigm, we ran a
combined analysis of the RT data for the three experiments put together, to compare the ‘digits’
Chapter 5|Evidence for right hemisphere superiority in figure matching and judging negative emotions
P.| 219
and the ‘middle-fingers’ responses. A similar, response type (2) x vhf (2) ANOVA was done.
The main effect of response type came out significant F (1, 40) = 72.54, p < 0.01; indicating that
over all three experiments “digits” responses were faster (digits = 463ms vs. middle-fingers =
500 ms). The main effect of visual half field was also significant, F (1, 40) = 4.59, p <0.05;
indicating an overall lvf/right hemisphere advantage ( lvf = 476 ms vs. rvf = 487 ms). The
interaction between response type x vhf did not come out significant, F (1, 40) = 2.31, p > 0.05;
but separate analyses indicated a significant lvf/right hemisphere advantage the “digits”
responses (matched, happy, and disgusted combined: lvf = 455 ms vs. rvf = 471 ms; F (1, 40) =
5.5, p < 0.05) and not for the “middle-fingers” responses (unmatched, sad, happy combined: lvf
= 496 ms vs. rvf = 503 ms; F (1, 40) = 1.66, p > 0.05).
General Discussion
In this study, we examined whether the VHF paradigm we have been developing in this
thesis (Hunter & Brysbaert, 2008; Verma & Brysbaert, 2011, Verma, Van der Haegen, &
Brysbaert, 2013) is better than the existing ones to uncover right hemisphere functions. To our
regret, this is not really the case. Whereas the findings with the paradigm are quite clear for left
visual field functions such as word and picture naming (Hunter & Brysbaert, 2008; Van der
Haegen, Cai, Seurinck, & Brysbaert, 2011) and tool recognition (Verma & Brysbaert, 2011,
submitted), the results for right hemisphere tasks seem to yield rather small LVF advantages that
struggle to exceed the threshold of statistical significance. This may be an indication of the fact
that right hemisphere functions are less lateralized than left hemisphere function, or it may be an
indication that we have not yet found the best tasks to study right hemisphere functions. In any
case, the findings of the present series of experiments suggest that our paradigm itself with
bilateral stimulus presentation, bimanual responses and a large number of trials is not enough to
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P. | 220
improve the situation. We were successful in finding a left visual field/right hemisphere
advantage for polygon matching, a finding that has been reported in earlier experiments (Rode et
al., 1995; Hausmann & Gunturkun, 1999; Hausmann, Becker, Gather & Gunturkun, 2002) and
for emotion recognition (Natale, Gur & Gur, 1983; Davidson, Ekman, Saron, Senulis & Friesen,
1990), but our data do not stand out as particularly convincing. As a result, although our data are
more in line with the right hemisphere hypothesis for emotion recognition than the valence
specific hypothesis, they are not more conclusive than those published before (Killgore &
Yergelun-Todd, 2007; Najit et al., 2013).
One element that has come out of the present series of experiments, though, is that the
assignment of responses to the fingers seems to be important. Responses assigned to the digit
fingers seem to be faster than responses assigned to the middle fingers, in line with Cho and
Proctor’s (2007) suggestion that positive responses are faster than negative responses. This will
be specifically the case when in addition the responses differ in polarity as well (e.g., same
responses tend to be seen as positive whereas different responses tend to be seen as negative),
but the results of Experiment 3 suggest that this is not a necessity. When the negative response
‘disgust’ was assigned to the digit fingers, participants responded faster to this emotion than to
happiness. Further parametric research is indicated to find out whether this enables some further
improvements for our paradigm, as it looks like VHF differences are stronger for response
alternatives assigned to the digit fingers than for response alternatives assigned to the middle
fingers.
The fact that the assignment of emotions to response alternatives has an effect on
response speed also puts some existing claims about emotion recognition into doubt. Earlier
studies (Kirita & Endo, 1995; Adolphs, Jansari & Tranel, 2001; and Leppanen & Hietanen,
Chapter 5|Evidence for right hemisphere superiority in figure matching and judging negative emotions
P.| 221
2003) have suggested an advantage for recognizing happy faces over neutral faces or other
emotional expressions. Our results suggest that this may be due to the correspondence with
response polarity rather than with the speed of emotion recognition. In addition, Experiment 2
made us aware that one has to be very careful with the visibility of the teeth as strong indicator
of happiness. One of the possible reasons for the happy face advantage in comparison with “sad”
faces could be that the visible teeth in the happy faces might be acting as a visual cue for the
participants and helping them discriminate the happy from the sad faces. Such a proposal finds
support in a study by Calvo, Nummenmaa & Avero (2010) who conclude that the happy face
recognition advantage might rely initially on featural properties. Kirita & Endo (1995) on the
other hand attribute the happy face advantage to spatial information in the happy faces, also
proposing that the human face recognition system might be selectively tuned for recognizing
face stimuli.
To conclude, we have re-affirmed the left visual field/right hemisphere advantage for
polygon matching and emotion recognition, but have not found that our VHF paradigm is better
for these functions than the existing VHF paradigms. At the same time, our results suggest that
response polarity may be an important factor in VHF tasks with binary responses.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 222
References
Adolphs, R., Jansari, A., & Tranel, D. (2001). Hemispheric perception of emotional valence from
facial expressions. Neuropsychology, 15(4), 516.
Alves, N. T., Aznar-Casanova, J. A., & Fukusima, S. S. (2009). Patterns of brain asymmetry in
the perception of positive and negative facial expressions. Laterality: Asymmetries of
Body, Brain and Cognition, 14, 256–272. doi:10.1080/13576500802362927
Amunts, K. (2010). 6 Structural Indices of Asymmetry. The Two Halves of the Brain, 145.
Atkinson, J., & Egeth, H. (1973). Right hemisphere superiority in visual orientation
matching. Canadian Journal of Psychology/Revue canadienne de psychologie, 27(2),
152.
Battelli, L., Herpich, F., Tyler, S., Grossman, E., & Agosta, S. (2013). Right hemisphere
dominance in temporal attention: a TMS study. Journal of Vision,13(9), 1199-1199.
Benton, A., Hannay, H. J., & Varney, N. R. (1975). Visual perception of line direction in patients
with unilateral brain disease. Neurology, 25(10), 907-907.
Berch, D. B., Foley, E. J., Hill, R. J., & Ryan, P. M. (1999). Extracting parity and magnitude
from Arabic numerals: Developmental changes in number processing and mental
representation. Journal of Experimental Child Psychology, 74, 286–308.
Bona, S., Herbert, A., Toneatto, C., Silvanto, J., & Cattaneo, Z. (2013). The causal role of the
lateral occipital complex in visual mirror symmetry detection and grouping: An fMRI-
guided TMS study. Cortex, 51, 46-55.
Borod, J. C., Cicero, B. A., Obler, L. K., Welkowitz, J., Erhan, H. M., Santschi, C., . . . Whalen,
J. R. (1998). Right hemisphere emotional perception: Evidence across multiple channels.
Neuropsychology, 12, 446–458. doi:10.1037/0894-4105.12.3.446
Bradshaw, J. L., & Nettleton, N. C. (1981). The nature of hemispheric specialization in
man. Behavioral and Brain Sciences, 4(01), 51-63.
Chapter 5|Evidence for right hemisphere superiority in figure matching and judging negative emotions
P.| 223
Bruce, V., & Young, A. (1986). Understanding face recognition. British journal of
psychology, 77(3), 305-327.
Bryden, M. P. (1976). Response bias and hemispheric differences in dot localization. Perception
& Psychophysics, 19(1), 23-28.
Burt D. M., Perrett D. I. (1997). Perceptual asymmetries in judgements of facial attractiveness,
age, gender, speech and expression. Neuropsychologia 35 685–693.10.1016/S0028-
3932(96)00111-X
Calvo, M. G., Nummenmaa, L., & Avero, P. (2010). Recognition advantage of happy faces in
extrafoveal vision: Featural and affective processing. Visual Cognition, 18(9), 1274-
1297.
Canli, T. (1999). Hemispheric asymmetry in the experience of emotion: A perspective from
functional imaging. The Neuroscientist, 5(4), 201-207.
Cho, Y. S., & Proctor, R. W. (2003). Stimulus and response representations underlying
orthogonal stimulus–response compatibility effects. Psychonomic Bulletin & Review, 10,
45–73.
Cho, Y. S., & Proctor, R. W. (2007). When is an odd number not odd? Influence of task rule on
the MARC effect for numeric classification. Journal of Experimental Psychology:
Learning, Memory, and Cognition, 33(5), 832.
Davidoff, J. B.(1975).Hemispheric differences in the perception of lightness. Neuropsychologia,
13, 121–124.
Davidson, R. J., Ekman, P., Saron, C. D., Senulis, J. A., & Friesen, W. V. (1990). Approach-
withdrawal and cerebral asymmetry: Emotional expression and brain physiology:
I. Journal of personality and social psychology, 58(2), 330.
Durnford, M., & Kimura, D. (1971). Right hemisphere specialization for depth perception
reflected in visual field differences.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 224
Geffen, G., Bradshaw, J. L., & Wallace, G. (1971). Interhemispheric effects on reaction time to
verbal and nonverbal visual stimuli. Journal of Experimental Psychology, 87, 415-22.
Gur, R. C., Alsop, D., Glahn, D., Petty, R., Swanson, C. L., et al. (2000). An fMRI study of sex
differences in regional activation to a verbal and a spatial task. Brain and Language, 74,
157–170.
Hausmann, M., & Gunturkun, O. (1999). Sex differences in functional cerebral asymmetries in a
repeated measures design. Brain and Cognition, 41(3), 263–275.
Hausmann, M., & Güntürkün, O. (2000). Steroid fluctuations modify functional cerebral
asymmetries: the hypothesis of progesterone-mediated interhemispheric
decoupling. Neuropsychologia, 38(10), 1362-1374.
Hausmann, M., Becker, C., Gather, U., & Güntürkün, O. (2002). Functional cerebral
asymmetries during the menstrual cycle: a cross-sectional and longitudinal
analysis. Neuropsychologia, 40(7), 808-816.
Hemond, C. C., Kanwisher, N. G., & Op de Beeck, H. P. (2007). A preference for contralateral
stimuli in human object – and face – selective cortex. PLoS ONE, 2(6), e574,
http://dx.doi.org/10.1371/journal.pone.0000574.
Hirnstein, M., Westerhausen, R., & Hugdahl, K. (2013). The Right Planum Temporale Is
Involved in Stimulus-Driven, Auditory Attention–Evidence from Transcranial Magnetic
Stimulation. PloS one, 8(2), e57316.
Hugdahl, K. (2000). Lateralization of cognitive processes in the brain. Acta
psychologica, 105(2), 211-235.
Hugdahl, K., & Westerhausen, R. (Eds.). (2010). The two halves of the brain: Information
processing in the cerebral hemispheres. MIT Press.
Hugdahl, K., Iversen, P. M., & Johnsen, B. H. (1993). Laterality for facial expressions: Does the
sex of the subject interact with the sex of the stimulus face? Cortex; A Journal Devoted to
the Study of the Nervous System and Behavior, 29, 325–331.
Chapter 5|Evidence for right hemisphere superiority in figure matching and judging negative emotions
P.| 225
Hugdahl, K., Iversen, P. M., Ness, H. M.,&Flaten, M. A. (1989). Hemispheric differences in
recognition of facial expressions: A VHF-study of negative, positive, and neutral
emotions. The International Journal of Neuroscience, 45, 205–213.
doi:10.3109/00207458908986233
Hunter, Z. R., & Brysbaert, M. (2008). Visual half-field experiments are a good measure of
cerebral language dominance if used properly: Evidence from
fMRI.Neuropsychologia, 46(1), 316-325.
Jansari, A., Rodway, P., & Goncalves, S. (2011). Identifying facial emotions: Valence specific
effects and an exploration of the effects of viewer gender. Brain and Cognition, 76, 415–
423. doi:10.1016/j.bandc.2011.03.009
Jansari, A., Tranel, D., & Adolphs, R. (2000). A valence-specific lateral bias for discriminating
emotional facial expressions in free field. Cognition & Emotion,14(3), 341-353.
Killgore, W. D., & Yurgelun-Todd, D. A. (2007). The right-hemisphere and valence hypotheses:
Could they both be right (and sometimes left)? Social Cognitive and Affective
Neuroscience, 2, 240–250. doi:10.1093/scan/nsm020
Kimura, D. (2004). Human sex differences in cognition, fact, not predicament. Sexualities
Evolution & Gender, 6, 45–53.
Kirita, T., & Endo, M. (1995). Happy face advantage in recognizing facial expressions. Acta
Psychologica, 89(2), 149-163.
Klosetrman, E., Loui, P., & Shimamura, A. P. (2009). Activation of right parietal cortex during
memory retrieval of nonlinguistic auditory stimuli. Cognitive,Affective and
BehavioralNeuroscience, 9(3), 242–248.
Kosslyn, S. M. (1987). Seeing and imagining in the cerebral hemispheres: a computational
approach. Psychological review, 94(2), 148.
Langner, O., Dotsch, R., Bijlstra, G., Wigboldus, D. H., Hawk, S. T., & van Knippenberg, A.
(2010). Presentation and validation of the Radboud Faces Database. Cognition and
Emotion, 24(8), 1377-1388.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 226
Leppänen, J. M., & Hietanen, J. K. (2003). Affect and face perception: odors modulate the
recognition advantage of happy faces. Emotion, 3(4), 315.
Ley, R. G., & Bryden, M. P. (1979). Hemispheric differences in processing emotions and
faces. Brain and Language, 7(1), 127-138.
Marinkovic, K., Baldwin, S., Courtney, M. G., Witzel, T., Dale, A. M., & Halgren, E.
(2011).Right hemisphere has the last laugh: Neural dynamics of joke apprecia- tion.
Cognitve Affective Begavioral Neuroscience, 11, 113–130, http://dx.doi.org/
10.3758/s13415-010-0017-7.
Mashal, N., Faust, M., Hendler, T., & Jung-Beeman, M. (2008). Hemispheric differences in
processing the literal interpretation of idioms: Converging evidence from behavioral and
fMRI studies. Cortex, 1–13, http://dx.doi.org/ 10.1016/j.cortex.2007.04.004.
Najt, P., Bayer, U., & Hausmann, M. (2013). Models of hemispheric specialization in facial
emotion perception—a reevaluation. Emotion, 13(1), 159.
Natale, M., Gur, R. E., & Gur, R. C. (1983). Hemispheric asymmetries in processing emotional
expressions. Neuropsychologia, 21(5), 555-565.
Nuerk, H. C., Iversen, W., & Willmes, K. (2004). Notational modulation of the SNARC and the
MARC (linguistic markedness of response codes) effect.Quarterly Journal of
Experimental Psychology Section A, 57(5), 835-863.
Posamentier, M. T., & Abdi, H. (2003). Processing faces and facial
expressions. Neuropsychology review, 13(3), 113-143.
Proctor, R. W., & Cho, Y. S. (2006). Polarity correspondence: A general principle for
performance of speeded binary classification tasks. Psychological Bulletin, 132, 416–
442.
Proctor, R. W., Wang, H., & Vu, K.-P. L. (2002). Influences of different combinations of
conceptual, perceptual, and structural similarity on stimulus–response compatibility.
Quarterly Journal of Experimental Psychology: Human Experimental Psychology, 55(A),
59–74.
Chapter 5|Evidence for right hemisphere superiority in figure matching and judging negative emotions
P.| 227
Rode, C., Wagner, M., & Gunturkun, O. (1995). Menstrual cycle affects functional cerebral
asymmetries. Neuropsychologia, 33(7), 855–865.
Rodway, P., Wright, L., & Hardie, S. (2003). The valence-specific laterality effect in free
viewing conditions: The influence of sex, handedness, and response bias. Brain and
Cognition, 53, 452–463. doi:10.1016/ S0278-2626(03)00217-3
Sergent, J. (1983). The role of the input in visual hemispheric asymmetries. Psychological
Bulletin, 93, 481-514.
Shulman, G. L., Pope, D. L. W., Astafiev, S. V., McAvoy, M. P., Snyder, A. Z., & Corbetta, M.
(2010).Right hemisphere dominance during spatial selective attention and target
detection occurs outside the dorsal fronto - parietal network. The Journal of
Neuroscience, 30 (10) , 3640–3651.
Stafford, L. D., & Brandaro, N. (2010). Valence specific laterality effects in free viewing
conditions: The role of expectancy and gender of image. Brain and Cognition, 74, 324–
331. doi:10.1016/j.bandc.2010.09.001
Unterrainer, J., Wranek, U., StaVen, W., Gruber, T., & Ladurner, G. (2000). Lateralized
cognitive visuospatial processing: is it primarily gender-related or due to quality of
performance? A HMPAO-SPECT study. Neuropsychobiology, 41, 95–101.
Van der Haegen, L., Cai, Q., Seurinck, R., & Brysbaert, M. (2011). Further fMRI validation of
the visual half field technique as an indicator of language laterality: A large-group
analysis. Neuropsychologia, 49(10), 2879-2888.
van Strien, J. W., & van Beek, S. (2000). Ratings of emotion in laterally presented faces: Sex and
handedness effects. Brain and Cognition, 44, 645–652, doi:10.1006/brcg.1999.1137.
Verma, A., & Brysbaert, M. (2011). A right visual field advantage for tool-recognition in the
visual half-field paradigm. Neuropsychologia, 49(9), 2342-2348.
Verma, A., Van der Haegen, L., & Brysbaert, M. (2013). Symmetry detection in typically and
atypically speech lateralized individuals: A visual half-field
study.Neuropsychologia, 51(13), 2611-2619.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 228
Weeks, D. J., & Proctor, R. W. (1990). Salient-features coding in the translation between
orthogonal stimulus–response dimensions. Journal of Experimental Psychology:
General, 119, 355–366.
Whitehouse, A. J., Badcock, N., Groen, M. A., & Bishop, D. V. (2009). Reliability of a novel
paradigm for determining hemispheric lateralization of visuospatial function. Journal of
the International Neuropsychological Society,15(06), 1028-1032.
Willmes, K., & Iversen, W. (1995 April). On the Internal Representation of Number Parity.
Paper presented at the Spring Annual Meeting of the British Neuropsychological Society,
London.
Young, A. W., McWeeny, K. H., Hay, D. C., & Ellis, A. W. (1986). Matching familiar and
unfamiliar faces on identity and expression. Psychological research, 48(2), 63-68.
Yovel, G., Tambini, A., & Brandman, T. (2008). The asymmetry of the fusiform face area is a
stable individual characteristic that underlies the left-visual field superiority for faces.
Neuropsychologia, 46, 3061–3068.
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Chapter 6: General Discussion
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Chapter 6: General Discussion
The main aim of the current thesis was to test the Visual Half-Field paradigm put forward by
Hunter & Brysbaert (2008), for investigating the lateralization of cognitive functions in general,
and the lateralization of non-verbal right hemisphere functions in particular. In the course of the
thesis, I was able to test one left hemisphere lateralized task (tool-recognition), and three right
hemisphere lateralized cognitive functions (symmetry detection, figure comparison and facial
emotion detection). I was also able to develop a standardized set of stimuli related to object and
tool recognition (i.e. pictures of objects, non-objects and tools) by replicating the earlier tool-
recognition study. Finally, I was able to test the lateralization of symmetry detection in a sample
of left-handed atypically lateralized individuals, and report indications of reverse lateralization
for symmetry detection in these atypically lateralized individuals.
In the next section, I will provide an overview of the studies undertaken during the thesis.
I will briefly discuss the purpose of each study and interpret the results and their significance in a
broader perspective. In the final section, I will attempt to draw conclusions on the basis of all
these studies put together and lay down directions for future research.
In chapter 2, I presented the first behavioral VHF-study investigating tool-recognition. In
a visual half-field paradigm, we presented tool-objects and non-tool objects, bilaterally, in a tool-
recognition experiment. The target visual field was cued by a centrally presented arrow, and
participants were asked to respond with ‘yes’ for a tool and ‘no’ for a non-tool. Bi-manual key-
press responses were elicited and reaction times and accuracy were measured. Also, to be sure
that the lateralization (VHF asymmetry) obtained for tools in comparison to non-tool objects
were not due to attentional biases; we conducted a separated object recognition experiment. In an
Chapter 6|General Discussion
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identical experimental set up; participants were asked to respond ‘yes’ for objects (i.e. non-tools
in the tool-recognition experiment) and ‘no’ for non-objects. Whereas the laterality of tools has
been pre-established in a range of clinical and neuroimaging studies (Frey, 2008), no clear
lateralization has been proposed for object recognition (Biedermann & Cooper, 1991).
In accordance with our hypotheses, we did not find a VHF asymmetry for objects
in the object recognition experiment; but we found a significant RVF/left hemisphere advantage
for tools in the tool recognition experiment. These results were important for a number of
reasons. Firstly, as we were able to replicate the left hemispheric lateralization of tool
recognition in our behavioral visual half-field paradigm, it became clear that the visual half-field
paradigm is a valid paradigm to investigate the lateralization of cognitive functions. Secondly,
now a new left hemisphere lateralized function, i.e. tool recognition is made available for
researchers to experiment with. We have approached tool recognition in a standard recognition
paradigm. Future experiments can now go ahead and experiment with more specific nuances.
This is interesting for new researchers, as they can now use our behavioral paradigm as the point
of departure and then take the participants to the scanner (as in fMRI) with the same tasks. For
instance, an experiment could be designed presenting tools in orientations that could be left/right
hand manipulable and see if the behavioral VHF asymmetry towards the RVF still holds.
Further, the visual half-field paradigm itself can be used to investigate the laterality of various
other cognitive functions as well. As the VHF experimental set up performed as we predicted, it
also presents a case for being used as a precursor to fMRI experiments investigating the
lateralization of cognitive functions in general. Thirdly, that we did not find a VHF asymmetry
for object recognition which implies that the VHF paradigm is sensitive to subtle differences
between classes of stimuli.
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Although, we took care to follow the recommendations of Hunter & Brysbaert (2008)
while designing the object and tool recognition experiments; we had to accept a particular
problem when selecting the stimuli. We discovered that while there were stimulus banks with
pictures of objects available that could be used as tools and non-tools for the tool-recognition
experiment, it was difficult to find matching non-objects pictures for our object recognition
experiment. For this reason, we had to conduct the two experiments using stimuli from two
different databases, i.e. stimuli (objects and non-objects) for the object recognition experiment
were drawn from one database (van Diepen & De Graaf, 1994) and stimuli (tool objects and
non-tool objects) for the tool recognition experiment were drawn from another database
(Snodgrass & Vanderwart, 1980). To tackle this problem, we paid an artist to draw stimuli for us
which could be used in both experiments. The artist was commissioned to draw matched sets of
objects (non-tool objects), non-objects and tools. As these three categories of stimuli were made
by the same person, using the same resources and maintaining the same parameters, they were
now more comparable in image criteria (size, overall shape etc). We decide to standardize these
stimuli by replicating the earlier two experiments.
So, in chapter 3, we present a study that was undertaken primarily to standardize the
pictures of objects, non-objects and tools, in order to make such stimuli available to future
researchers. The basic idea was to replicate the object recognition and tool recognition
experiments with these new stimuli and see if the VHF asymmetry for tools could be replicated,
or even enhanced by the use of better stimuli. More importantly, the participants see the same
stimuli in both experiments, hence, the data from the two experiments were mutually more
comparable. The three categories of stimuli (i.e. the objects, non-objects and tool-objects) were
organized in triplets. Each triplet comprised of a single specimen from each of the three
Chapter 6|General Discussion
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categories and care was taken that specimens in a triplet were matched on criteria such as size,
overall shape etc.
To start, we asked 20 participants to rate the object-non object stimuli on a 6-point likert
scale, i.e. Object Non-Object Rating Scale, for their object-ness. To our benefit, most of the
stimuli were rated as expected, i.e. stimuli made as objects were rated as objects and those made
as non-objects were rated as non-objects. Next we used a different 6-point likert scale, i.e. Tool
Non-tool Rating scale, wherein we asked participants to rate stimuli on their tool-ness. The
stimuli which were earlier rated as objects in the Object Non-Object Rating Scale were included
along with the stimuli which were made as tools. To guide participants, a basic definition of a
tool was provided in the instructions. For the most part objects constructed as tools were rated
high on tool-ness, while those rated low on tool-ness were included as non-tools in the
subsequent experiment.
We replicated the object recognition and tool recognition experiments, following
the same protocol as in the earlier study. In the object recognition experiment, we found no VHF
asymmetry for objects, but a significant LVF/right hemisphere advantage for non-objects. As,
non-objects are unnameable figures, it is probable that the participants used spatial analysis to
distinguish the non-objects from the objects; hence, the LVF/right hemisphere advantage for
non-objects was not surprising. In the tool recognition experiment we found the expected
significant RVF/left hemisphere advantage for tool recognition. The RVF advantage for tools
was even more enhanced as compared to the earlier study; it rose from 17ms (for the
incompatible condition) to 26ms (for the incompatible condition). Surprisingly, the same objects
that did not show a VHF asymmetry in the object recognition experiment showed a LVF
asymmetry in the tool recognition experiment. This inconsistent VHF asymmetry for objects is
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not surprising (Biedermann & Cooper, 1991). More importantly, the new pictures of objects,
non-objects and tools were correctly classified in the Likert scales, and in the object and tool
recognition experiments. These pictures have now been made available for use by the research
community interesting object or tool recognition on our lab website <
http://crr.ugent.be/archives/1594 >.
Having established in the earlier two studies, that the VHF paradigm works well for a left
lateralized cognitive function (i.e. tool recognition), I decided to test the paradigm for a cognitive
function lateralized to the right hemisphere. It has been asserted by Hugdahl (2000) that the
language-visuospatial dichotomy has produced the most consistent VHF asymmetries. Hence it
was decided to choose a visuospatial function for investigation, i.e. symmetry detection.
In chapter 4, I decided to investigate the lateralization of symmetry detection using our
VHF paradigm. Symmetry detection is an important visuospatial function that helps us make
sense of our visual world. For instance, it has been found to be important for figure ground
segregation and face recognition (Koffka, 1935; Little and Jones, 2006). While there was
behavioral evidence for a right hemisphere role in symmetry detection (Corballis & Roldan,
1974; Brysbaert, 1994), the neuroimaging evidence regarding the lateralization of symmetry
detection was not clear (Tyler, Baseler, Kontsevich, Likova, Wade, and Wandell, 2005;
Cattaneo, Mattavelli, Papagno, Herbert, and Silvanto, 2011).
We hypothesized that symmetry detection as a cognitive function is lateralized to the
right hemisphere, and would yield a LVF/right hemisphere advantage in our VHF paradigm. In
order to separate the effects of handedness on the VHF asymmetry for symmetry detection,
separate experiments were performed for right handed and left handed participants.
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To start with, a group of 20 right handed undergraduate students participated in the
symmetry detection experiment. These students were also expected to be typically lateralized for
speech dominance, i.e. left hemisphere dominant. The stimuli were formed of three rectangles
arranged on top of each other, in the form of a composite figure that could be symmetrical or
asymmetrical along the vertical axis. We used bilateral presentation and participants were asked
to respond ‘yes’ if they saw a symmetrical figure in the target visual field (cued by the central
arrow) and ‘no’ for an asymmetrical figure. Bimanual key-press responses were registered and
reaction times and accuracy were measured.
The data from the right handed participants confirmed our hypotheses. We observed a
significant main effect of visual half-field and stimulus type. A significant LVF/right hemisphere
advantage for symmetry detection was observed in 80% of the participants. The results provided
a clear indication of the right hemisphere lateralization of symmetry detection in typically
lateralized right handed individuals.
Next we investigated the lateralization of symmetry detection in left handed participants.
While a large percentage of left handed individuals are also typically lateralized for speech,
about 20-25% of left handed individuals are right hemisphere speech dominant (Knecht, Drager,
Deppe, Bobe, Lohmann, & Floel, 2000). Hence, the left handed participants were segregated into
typically and atypically lateralized groups; this was done by one of my colleagues, Lise Van der
Haegen in one of her earlier studies (Van der Haegen, et al., 2011) and the two groups
participated in the symmetry detection experiment separately.
In Experiment 2, 37 typically lateralized left handed individuals participated in the
symmetry detection experiment. In this experiment, we did not find main effects for either visual
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half field or stimulus type, instead, a significant interaction between vhf and stimulus type was
found. On a closer examination, we found that 29 out of 37, i.e. 78.4 % of the left handed
typically lateralized individuals showed a LVF/right hemisphere advantage for the symmetric
stimuli. Hence, even though the right hemisphere role in symmetry detection was clear, the
findings were not as strong as in the case of right handed participants.
In experiment 3, 17 left handed atypically lateralized participants took part in the
symmetry detection experiment. While the two earlier experiments had confirmed that symmetry
detection is lateralized to the right hemisphere in typically lateralized left speech dominant
individuals irrespective of their handedness, this experiment was expected to provide an insight
into the lateralization of symmetry detection in atypically lateralized individuals. In accordance
with the crowding hypothesis (Cai et al., 2013; Lansdell, 1969; Teuber, 1974) we hypothesized a
reversed lateralization of symmetry detection in these individuals, i.e. a RVF/left hemisphere
advantage was expected. The data from this experiment, however, were not very clear. Only
around 50 % of the participants i.e. 8 out of 17 for RTs and 9 out of 17 for percentage errors
showed the expected RVF/left hemisphere lateralization for symmetry detection, while the other
participants showed the signs of a LVF/right hemisphere advantage. It should be noted, however,
that the sample consists of a small number of atypically lateralized individuals. Research with a
larger sample may provide a clearer picture. We did not have access to more of the atypically
lateralized participants, and hence, it is still unclear whether symmetry detection may be
lateralized to the left hemisphere in atypically lateralized individuals.
However, the experiments presented in Chapter 4, are important for a range of reasons.
Firstly, it can be safely said that symmetry detection (off fixation) is lateralized to the right
hemisphere in typically lateralized individuals, irrespective of their handedness. Secondly, while
Chapter 6|General Discussion
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earlier studies had used stimuli like random dot stereograms (for e.g. Corballis & Roldan, 1974)
or investigated symmetry detection indirectly (Wilkinson & Halligan, 2002), the current study
established the lateralization of symmetry detection more directly, using more ecologically valid
stimuli (i.e. geometrical shapes). Thirdly, the first two experiments also provided evidence for
the fact that VHF asymmetries are better predicted by speech dominance than handedness; as,
both groups of typically speech lateralized individuals demonstrated a LVF/right hemisphere
advantage for symmetry detection. Finally, although the results of the third experiment were not
clear, they surely indicate that lateralization of various cognitive functions in the atypically
lateralized individuals needs to be investigated. Indeed, there is already evidence that certain
visuospatial functions may be lateralized to the opposite hemisphere as well (Cai et. al., 2013).
In light of this finding, more research needs to be done with atypically lateralized individuals.
Hunter & Brysbaert (2008) also indicated that one of the best ways to test the validity of a VHF
task was to test with right hemisphere dominant individuals. To this effect, we concede that we
were limited by the number of participants in Experiment 3. However, there were indications that
symmetry detection was lateralized to the left hemisphere in some participants in whom
language was lateralized to the right hemisphere. Hence, more research on symmetry detection
with a larger sample of atypically lateralized individuals might be required to ascertain whether
the lateralization of symmetry detection gets reversed.
We had by now tested the visual half-field paradigm for one left hemisphere and one
right hemisphere lateralized cognitive function, and found that the tasks in the paradigm perform
reasonably well. It was decided to investigate the lateralization of few other cognitive functions
which were assumed to be lateralized to the right hemisphere.
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In Chapter 5, we decided to investigate the lateralization of figure comparison and facial
emotion detection. Figure comparison is a visuospatial task, wherein participants are asked to
compare a black irregular polygon presented in the target visual field (left or right, cued by a
central arrow) to a similar polygon presented centrally 200ms earlier. Participants were asked to
respond ‘yes’ if the target polygon matched the polygon presented earlier and ‘no’ if it did not.
Bimanual key-press responses were registered, and reaction times (RTs) and accuracy were
measured. The figure comparison task had been used in earlier studies and shown to reveal a
significant LVF/right hemisphere advantage (Rode et. al., 1995; Hausmann & Gunturkun, 1999,
2000). One of the reasons for the observed right hemisphere advantage could be that the
polygons were unnameable figures, and hence participants would have been more inclined to use
spatial analysis rather than a verbal strategy or remembering a name.
We decided to replicate the figure comparison task with our new VHF paradigm and test
whether the paradigm would yield a stronger LVF advantage than reported before. This would
give us information about the efficiency of our paradigm relative to that of previous paradigms.
As expected, we were able to find a significant LVF advantage in trials where the
participants were able to match the two polygons. While we did not observe a main effect of
visual half-field in RTs, we found a significant main effect for visual half-field in the percentage
accuracy data. Such a finding may be due to the fact that the overall effect was smaller for RTs,
but more clearly present for the accuracy data; something that had also been observed in earlier
studies. All in all, we were able to replicate the LVF/right hemisphere advantage for figure
comparison, but the data with our paradigm was not more convincing than the existing data.
Chapter 6|General Discussion
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In a final task, we decided to put our VHF paradigm to a tougher test. Facial emotion
judgment is an important cognitive function which helps us operate in a social environment and
has been the subject of investigation for psychologists in general and laterality researchers in
particular. While it has been known that facial emotion detection engages both hemispheres
differentially, the exact role of the two hemispheres is still an issue of considerable debate (Najit
et al., 2013). Further, two major competing theories have been offered to explain the role of the
cerebral hemispheres in facial emotion detection, i.e. the right hemisphere hypothesis and the
valence hypothesis, respectively. While the former asserts that all emotions are detected by the
right hemisphere predominantly, the latter hypothesis proposes that the right hemisphere
specializes in detecting negative emotions and the left hemisphere of the brain specializes in
detecting negative emotions. Several studies have provided evidence in favor of and against both
theories, though none have been conclusive. Most notable of these is a recent study by Najit et al.
(2013) where they compared the two hypotheses directly and failed to find evidence for either of
them.
We decided to test the two theories of facial emotion judgment using our VHF paradigm.
For this reason we chose a positive emotion (happiness) and a negative emotion (sadness) and
presented participants with a simple emotion recognition task. Participants were presented with
either happy or sad faces, bilaterally, and were asked to respond ‘yes’ if they saw a happy target
face and ‘no’ if they saw a sad target face (indicated by an arrow). Bimanual responses were
registered and RTs and accuracy were measured. We found a marginally significant main effect
of visual half-field, indicating that participants were faster for judging both happy and sad faces
in the left visual half-field. The other major finding was that participants were faster for happy
faces. While the first finding may be taken as support for the right hemisphere hypothesis; the
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effect was only marginally significant (p = 0.07) and separate analysis for happy and sad faces
failed to corroborate the fact that the participants were consistently faster for judging emotions in
the lvf/right hemisphere. On the other hand, we were intrigued by the observation that
participants were much faster at detecting the happy faces (p< 0.01). A possibility was that the
participants were using a visual cue (the teeth) to recognize happy faces over sad faces.
To control for the possible confound, we decided to contrast the happy faces with another
negative emotion. We chose to contrast the happy faces with disgusted faces, in which the teeth
were also displayed. Participants were again presented with a simple emotion recognition
experiment. They now had to respond ‘yes’ to disgusted faces and ‘no’ to happy faces. Having
ruled out the confounding variable of ‘teeth’ as visual cue, we hoped to get clearer results.
Unfortunately, again we failed to find a main effect of visual half-field. Interestingly,
participants were faster at responding to disgusted faces as compared to happy faces in this
experiment. The other notworthy finding was a close to significant LVF/right hemisphere
advantage for disgusted faces (p= 0.08). While this may be viewed as an indication for support to
the right hemisphere hypothesis, one must admit that this finding is far from conclusive.
All in all, the experiments with facial emotion detection using our VHF paradigm did not
present conclusive results. More specifically, we did not find evidence in favor of either of the
two competing hypotheses. However, one of the findings in the last experiment stands out; that
happy faces were responded to more slowly than the disgusted faces. This finding was important
for two reasons; firstly, it shows that positive emotions are not always responded to faster than
negative emotions and secondly, this finding seems to be indicative of a larger pattern inherent to
our VHF paradigm.
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According to the recommendations made by Hunter & Brysbaert (2008), in all
experiments under our VHF paradigm, participants have to make binary decisions (e.g. ‘yes’ for
happy and ‘no’ for sad etc). Importantly, it can be observed that the participants have been faster
for ‘yes’ responses for all experiments, throughout the thesis. Also, it can be observed that VHF
asymmetries have been larger for the ‘yes’ responses. These findings align with the so-called
marked-ness effects in binary responses, wherein it has been proposed that participants are faster
for one type of response alternative over the other (Willems & Iversen, 1995). This has also been
explained using the polarity coding hypothesis by Cho & Proctor (2007). In all the experiments
of the thesis, we have observed that participants responded more rapidly with their index fingers
for ‘yes’ responses.
To test the markedness effect, we combined the performance of the participants in the
three experiments of Chapter 5 and analyzed for a 2 x 2 ANOVA (Response Type, VHF). In line
with our expectations, participants were faster for responses with the index fingers. Also,
participants were significantly faster in the LVF/right hemisphere. Given the assumed right
hemispheric nature of the three tasks, this finding is not surprising.
The findings reported in the three experiments presented in Chapter 5, are interesting in
their own right. While we have been able to replicate the LVF advantage for figure comparison
and even partially for facial emotion detection; the findings are not entirely convincing. These
results may point towards two possibilities. One, the right hemisphere functions may not be so
strongly lateralized and hence it will always be difficult to find strong visual field advantages for
tasks investigating right hemisphere functions, Or secondly, the VHF task may not be strong
enough in itself to uncover the subtle visual field effects for right hemisphere functions. Given
the findings from Chapters 2, 3 and 4; I am more inclined to put away the second possibility.
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While one can say that Chapters 2 and 3 basically investigated the same cognitive function, i.e.
tool recognition, known to be strongly left-lateralized, the findings from Chapter 4 must be taken
into account before dismissing the merits of the VHF paradigm for investigating the right
hemisphere function. Indeed, the VHF paradigm was able to uncover subtle visual half-field
advantage for symmetry detection. Also, it should be noted that a significant LVF advantage was
observed for non-objects in the object recognition experiment in chapter 3. Also, it has been
suggested that it is generally difficult to find consistent and robust effects for right hemisphere
functions (Whitehouse, Badcock, Green & Bishop, 2009). Unfortunately though, our VHF
paradigm failed to solve the debate on facial emotion detection. However, a new finding surfaced
during the analyses in Chapter 5. We discovered that polarity or markedness turned out to be an
important factor in our VHF paradigm. Over the experiments in the thesis, participants have been
faster for ‘yes’ responses with their ‘index fingers’, and VHF asymmetries have been clearer for
these responses. More research using the VHF paradigm may be desirable further to investigate
the impacts of polarity on visual half-field effects.
The Visual Half-Field Paradigm: Conclusions
Over the course of this thesis I have conducted many experiments using the visual half field
(VHF) paradigm proposed by Hunter & Brysbaert (2008). While the paradigm performed well as
far as the left lateralized function, i.e. tool recognition was concerned, the results with right
hemisphere lateralized functions were not completely convincing. However, we have been able
to set up a standard VHF paradigm which has a good chance of being successful if the protocol is
followed. Further, as more and more different cognitive functions are tested using the VHF
paradigm; we can expect more of its strengths and weaknesses to be discovered.
Chapter 6|General Discussion
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For future research, more right hemisphere functions need to be investigated using the
VHF paradigm. As pointed out, investigators may also want to investigate various factors like
response polarity, and see how they impact VHF asymmetries. One of the important aspects of
research into right hemisphere functionshas been the non-uniformity of stimuli used throughout
the various studies across laboratories. In our view, researchers using the VHF paradigm should
engage in the endeavor to develop and standardize stimuli which can be used for various kinds of
tasks, investigating lateralization of cognitive functions (an example could be developing a
standard set of stimuli for facial emotion recognition, global-local levels of processing etc.).
In the end, I would like to present the VHF paradigm as we have used it for use by the
larger research community beyond our lab, and encourage them to use the task for investigating
the lateralization of cognitive functions.
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References
Biederman, I., & Cooper, E. E. (1991). Priming contour-deleted images: Evidence for
intermediate representations in visual object recognition. Cognitive psychology, 23(3),
393-419.
Brysbaert, M. (1994). Lateral preferences and visual field asymmetries: Appearances may have
been overstated. Cortex, 30, 413–429.
Cai, Q., van der Haegen, L., & Brysbaert, M. (2013). Complementary hemispheric specialization
for language production and visuospatial attention. Proceedings of the National Academy
of Sciences, 110(4), 322–330.
Cattaneo, Z., Mattavelli, G., Papagno, C., Herbert, A., & Silvanto, J. (2011). The role of the
human extrastriate visual cortex in mirror symmetry discrimination: A TMS-adaptation
study. Brain and Cognition, 77, 120–127.
Cho, Y. S., & Proctor, R. W. (2007). When is an odd number not odd? Influence of task rule on
the MARC effect for numeric classification. Journal of Experimental Psychology:
Learning, Memory, and Cognition, 33(5), 832.
Corballis, M. C., & Roldan, C. E. (1974). On the perception of symmetrical and repeated
patterns. Perception and Psychophysics, 16(1), 136–142.
Frey, S. H. (2008). Tool use, communicative gesture and cerebral asymmetries in the modern
human brain. Philosophical Transactions of the Royal Society B: Biological
Sciences, 363(1499), 1951-1957.
Hausmann, M., & Gunturkun, O. (1999). Sex differences in functional cerebral asymmetries in a
repeated measures design. Brain and Cognition, 41(3), 263–275.
Hausmann, M., & Güntürkün, O. (2000). Steroid fluctuations modify functional cerebral
asymmetries: the hypothesis of progesterone-mediated interhemispheric
decoupling. Neuropsychologia, 38(10), 1362-1374.
Chapter 6|General Discussion
P.| 247
Hugdahl, K. (2000). Lateralization of cognitive processes in the brain. Acta
psychologica, 105(2), 211-235.
Hunter, Z. R., & Brysbaert, M. (2008). Visual half-field experiments are a good measure of
cerebral language dominance if used properly: Evidence from
fMRI.Neuropsychologia, 46(1), 316-32.
Knecht, S., Drager, B., Deppe, M., Bobe, L., Lohmann, H., Floel, A., et al.(2000). Handedness
and hemispheric language dominance in healthy humans. Brain, 123, 2512–2518.
Koffka,K.(1935). Principles of Gestalt Psychology. New York: Harcourt, Brace and World.
Lansdell, H. (1969). Verbal and non-verbal factors in right-hemisphere speech: Relation to early
neurological history. Journal of Physiological and Comparative Psychology, 69, 734–
738.
Little, A. C., & Jones, B. C.(2006). Attraction in dependent of detection suggests special
mechanisms for symmetry preferences in human face perception. Proceedings of the
Royal Society B, 273, 3093–3099.
Najt, P., Bayer, U., & Hausmann, M. (2013). Models of hemispheric specialization in facial
emotion perception—a reevaluation. Emotion, 13(1), 159.
Rode, C., Wagner, M., & Gunturkun, O. (1995). Menstrual cycle affects functional cerebral
asymmetries. Neuropsychologia, 33(7), 855–865.
Snodgrass, J. G., & Vanderwart, M. (1980). A Standardized set of 260 pictures: Norms for name
agreement, image agreement, familiarity and visual complexity. Journal of Experimental
Psychology: Human Learning and Memory, 6(2), 174–215.
Teuber, H. L. (1974). Why two brains? In: F. O. Schmidts, & F. G. Worden(Eds.), The
Neurosciences: Third Study Program (pp. 71–74).Cambridge, MA: MIT Press.
Tyler, C.W., Baseler, H. A., Kontsevich, L. L., Likova, L. T., Wade, A.R., & Wandell, B. A.
(2005). Predominantly extra-retinotopic cortical response to pattern symmetry.
NeuroImage, 24, 306–314.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 248
Van der Haegen, L., Cai, Q., Seurinck, R., & Brysbaert, M. (2011). Further fMRI validation of
the visual half field technique as an indicator of language laterality: A large-group
analysis. Neuropsychologia, 49, 2879–2888.
van Diepen, P. M. J., & De Graef, P. (1994). Line-drawing library and software toolbox (Psych.
Rep. No. 165). In Laboratory of experimental psychology. Belgium: University of
Leuven.
Whitehouse, A. J., Badcock, N., Groen, M. A., & Bishop, D. V. (2009). Reliability of a novel
paradigm for determining hemispheric lateralization of visuospatial function. Journal of
the International Neuropsychological Society,15(06), 1028-1032.
Wilkinson, D. T., & Halligan, P. W. (2002). The effects of stimulus symmetry on landmark
judgments in left and right visual fields. Neuropsychologia, 1045–1058.
Willmes, K., & Iversen, W. (1995 April). On the Internal Representation of Number Parity.
Paper presented at the Spring Annual Meeting of the British Neuropsychological Society,
London.
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Nederlandse Samenvatting
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Nederlandse samenvatting
Lateralisatie van cognitieve functies: Verder onderzoek met de
visuele halfveldtaak
Het belangrijkste doel van deze verhandeling was om de validiteit van het visuele halfveld
paradigma, zoals voorgesteld door Hunter en Brysbaert (2008), uit te testen voor onderzoek naar
de lateralisatie van cognitieve functies, in het bijzonder voor de lateralisatie van functies in de
niet-dominante hersenhemisfeer. Hiertoe werden de volgende taken gebruikt:
werktuigherkenning (linkse hersenhelft), symmetriedetectie, figuurvergelijking en detectie van
emoties op gezichten (alle drie rechterhemisfeertaken). Ik ben er verder in geslaagd om een
gestandaardiseerde stimulusset te ontwikkelen die beter onderzoek mogelijk maakt over de
lateralisatie van werktuigherkenning en objectherkenning. Hier toe werden gematchte sets van
werktuigen, andere voorwerpen en niet-objecten ontwikkeld. Een andere interessant aspect aan
mijn thesis is dat ik symmetriedetectie heb kunnen onderzoeken bij een groep van proefpersonen
met atypische taaldominantie. In deze groep vond ik aanwijzingen voor een omgekeerde
lateralisatie van symmetriedetectie in de linkerhemisfeer.
Hieronder bespreek ik de verschillende hoofdstukken wat meer in detail.
Hoofdstuk 1
Hoofdstuk 1 bevat een literatuurstudie over lateralisatie-onderzoek, met bijzondere aandacht
voor de functies die in de volgende hoofdstukken aan bod komen. Er wordt ook een overzicht
gegeven van de verschillende technieken die gebruikt worden bij lateralisatie-onderzoek. Hierbij
valt, zoals in veel andere gebieden van de neuropsychologie, een toenemend belang van
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hersenscanstudies op. Toch blijft gedragsmatig onderzoek belangrijk, omdat dit veel goedkoper
en flexibeler is. Hierbij is het wel belangrijk dat het onderzoek degelijk uitgevoerd wordt. Hunter
en Brysbaert (2008) wezen op de tekortkomingen van veel studies met de visuele halfveld (VHF;
visual halffield) taak en stelden een reeks van aanbevelingen op, waaraan VHF studies moeten
beantwoorden. De huidige verhandeling gaat na in hoeverre het toepassen van deze
aanbevelingen leidt tot duidelijkere resultaten met betrekking tot linkerhemisfeer en – vooral –
rechterhemisfeertaken.
Hoofdstuk 2
Een functie waarvan recent is komen vast te staan dat die gelateraliseerd is in de taaldominante
hemisfeer betreft het herkennen van werktuigen. Deze taak hebben we dan ook als eerste
gebruikt. De proefpersonen moesten beslissen of een aangeduide tekening naar een werktuig
(hamer, schroevendraaier, vork, …) verwees of niet. In navolging van Hunter en Brysbaert
(2008) werd tegelijk links en rechts een tekening aangeboden (bilaterale presentatie) en moest de
proefperson reageren op de tekening waar een centraal aangeboden pijl naar verwees. De
responsen waren bimanueel (met de wijsvingers of de mindervingers van beide handen), om een
effect van stimulus-responscompatibiliteit te vermijden. Deze proef leverde een duidelijk
voordeel van het rechtse visuele veld op bij rechtshandigen, zoals voorspeld op basis van de
linkerhemisfeerdominantie. De proefpersonen konden sneller aangeven of een tekening
aangeboden rechts van het fixatiepunt naar een voorwerp verwees dan een tekening aangeboden
links van het fixatiepunt. Om zeker te zijn dat het effect te wijten was aan lateralisatie van
werktuigherkenning en niet aan oninteressante neveneffecten, zoals de aandachtsverdeling, werd
een tweede proef afgenomen, waarin de proefpersonen moesten aanduiden of de figuur waarnaar
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verwezen werden een bestaand object voorstelde dan wel een verzonnen niet-object. Zoals
verwacht, leverde deze proef geen voordeel van het rechtergezichtsveld op.
Hoofdstuk 3
Een ongemak bij het onderzoek uit hoofdstuk 2 was dat we moesten werken met verschillende
sets van voorwerpen in de studie over werktuigherkenning en voorwerpherkenning. De
werktuigen en bijbehorende voorwerpen kwamen uit de database van Snodgrass en Vanderwart,
1980). Deze database bevat enkel tekeningen van bestaande voorwerpen. Om tekeningen van
niet-voorwerpen te vinden, moesten we gebruik maken van een database uitgewerkt door van
Diepen en De Graaf (1994). Deze database bevat voorwerpen en gematchte niet-voorwerpen,
maar geen werktuigen. Jammer genoeg was de tekenstijl volledig verschillend, zodat we de twee
sets niet konden combineren. Omdat we de VHF-taak voor het herkennen van werktuigen op
punt wilden hebben voor verder onderzoek, hebben we een set van gematchte tekeningen van
werktuigen, andere voorwerpen en niet-voorwerpen laten ontwerpen, geïnspireerd op het
onderzoek in Hoofdstuk 2. Bovendien hebben we stimuli gevalideerd op basis van twee
beoordelingstaken (in hoeverre is dit een tekening van een werktuig, en in hoeverre is dit een
tekening van een bestaand voorwerp?). Toen we deze stimuli gebruikten, stelden we inderdaad
vast dat de data nog mooier werden. Vooreerst steeg het rechterveldvoordeel van 17 ms naar 26
ms. Bovendien waren de tijden in de voorwerpherkenningstaak en de werktuigherkenningstaak
nu aan elkaar gelijk (in Hoofdstuk 2 ging de voorwerpherkenningstaak sneller dan de
werktuigherkenningstaak). De nieuwe stimulusset, samen met de validatiestudies, worden
gepubliceerd en zullen beschikbaar zijn voor andere onderzoekers die rond werktuigherkenning
willen werken.
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Hoofdstuk 4
In Hoofdstuk 4 onderzocht ik een taak van de niet-dominante rechterhemisfeer. Uit een overzicht
van Hugdahl (2000) was gebleken dat het onderscheid tussen taalgerelateerde vs. visuospatiale
functies nog altijd het best de taakverdeling tussen de dominante en de niet-dominante
hersenhelft weergeeft. Daarom besloot ik gebruik te maken van een minder onderzochte
visuospatiale functie, namelijk symmetriedetectie. In een eerste proef werd aan rechtshandigen
gevraagd om aan te geven of de figuur waarnaar de centrale pijl verwees, symmetrisch was of
niet (volgens het paradigma van Hunter & Brysbaert, 2008). Dit leverde inderdaad een
significant voordeel in het linkse gezichtsveld op bij 80% van de proefpersonen. Nadien werd de
proef herhaald bij linkshandigen van wie op basis van voorgaand hersenscanonderzoek (Van der
haegen, et al., 2011) geweten was dat ze ofwel linksdominant waren voor spraakproductie ofwel
rechtsdominant. Bij de linksdominanten werd het voordeel van het linkse gezichtsveld herhaald,
maar het was iets kleiner dan bij de rechtshandigen. Bij de rechtsdominante linkshandigen was er
een duidelijke trend in de richting van een voordeel voor de rechtergezichtshelft, maar was er
ook evidentie voor veel meer individuele variabiliteit bij de proefpersonen. Dit lijkt erop te
wijzen dat atypische lateralisatie voor taalproductie tot op zekere hoogte gepaard gaat met
atypische lateralisatie van symmetriedetectie (zie ook Cai et al., 2013, voor een gelijksoortige
bevindingen met een andere visuospatiale taak).
Hoofdstuk 5
In Hoofdstuk 5 onderzocht ik de bruikbaarheid van het paradigma van Hunter en Brysbaert
(2008) voor twee andere taken van de rechterhemisfeer, die gewoonlijk geen al te duidelijke
resultaten geven in VHF studies: het vergelijken van moeilijk te benoemen veelhoeken en het
herkennen van emoties in gezichten. Bij het herkennen van moeilijk te benoemen veelhoeken
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
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wordt een voordeel van het linkse visuele veld verwacht, want deze taak kan niet (of moeilijk) op
basis van taal verwezenlijkt worden. Hoewel de verschillen meestal in de verwachte richting
gaan, is het verschil tussen de linkse en de rechtse helft van het gezichtsveld echter altijd klein.
Ik ging na of het groter zou worden met ons paradigma. Jammer genoeg bleek dit niet het geval
te zijn: we vonden geen verschil in reactietijden, enkel een klein verschil bij procent herkend.
Een soortgelijke bevinding werd gedaan bij het herkennen van emoties op gezichten. Ook hier
was er enige evidentie voor een voordeel van de linkse gezichtshelft (de rechterhemisfeer), maar
het verschil was opnieuw niet meer overtuigend dan de bestaande bevindingen. Als dusdanig ben
ik dus op de grenzen van het paradigma gestoten: het maakt consistente verschillen duidelijker,
maar heeft weinig effect bij zeer kleine verschillen (misschien omdat de functies niet sterk
gelateraliseerd zijn).
Een onverwachte bevinding was dat sneller geantwoord werd op gelukkige gezichten wanneer
men met de wijsvingers op deze gezichten moest reageren dan wanneer men met de
middelvingers op deze gezichten moest reageren. Een heranalyse van alle studies in deze
verhandeling bevestigde dat responsen met de wijsvingers in elke proef tot de snelste reacties
leidden en ook tot de duidelijkste VHF verschillen. We brengen deze bevinding in verband met
het markedness effect, aangetoond bij binaire responsen. Het laat ons toe om de resultaten van
het paradigma van Hunter en Brysbaert (2008) beter te begrijpen.
Hoofdstuk 6
In Hoofdstuk 6 wordt een samenvatting gegeven van de bevindingen en de conclusies die uit
deze verhandeling kunnen getrokken worden. Dit hoofdstuk was de leidraad voor de huidige
Nederlandse samenvatting.
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P.| 255
Referentie
Hugdahl, K. (2000). Lateralization of cognitive processes in the brain. Acta
psychologica, 105(2), 211-235.
Hunter, Z. R., & Brysbaert, M. (2008). Visual half-field experiments are a good measure of
cerebral language dominance if used properly: Evidence from
fMRI.Neuropsychologia, 46(1), 316-32.
Snodgrass, J. G., & Vanderwart, M. (1980). A Standardized set of 260 pictures: Norms for name
agreement, image agreement, familiarity and visual complexity. Journal of Experimental
Psychology: Human Learning and Memory, 6(2), 174–215.
Van der Haegen, L., Cai, Q., Seurinck, R., & Brysbaert, M. (2011). Further fMRI validation of
the visual half field technique as an indicator of language laterality: A large-group
analysis. Neuropsychologia, 49, 2879–2888.
van Diepen, P. M. J., & De Graef, P. (1994). Line-drawing library and software toolbox (Psych.
Rep. No. 165). In Laboratory of experimental psychology. Belgium: University of
Leuven.
Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited
P. | 256