Vrije Universiteit Amsterdam · VRIJE UNIVERSITEIT. Attention to Emerging Objects . ACADEMISCH...

VU Research Portal

Attention to Emerging Objects

Schreij, D.B.B.

2012

document versionPublisher's PDF, also known as Version of record

Link to publication in VU Research Portal

citation for published version (APA)Schreij, D. B. B. (2012). Attention to Emerging Objects.

General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.

• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ?

Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.

E-mail address:[email protected]

Download date: 25. Jul. 2021

https://research.vu.nl/en/publications/c6047e01-fca9-408a-8606-7e5b7933f45e

VRIJE UNIVERSITEIT

Attention to Emerging Objects

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad Doctor aan de Vrije Universiteit Amsterdam,

op gezag van de rector magnificus prof.dr. L.M. Bouter,

in het openbaar te verdedigen ten overstaan van de promotiecommissie

van de faculteit der Psychologie en Pedagogiek op vrijdag 13 januari 2012 om 11.45 uur

in de aula van de universiteit, De Boelelaan 1105

door

Daniël Bertus Bernard Schreij

geboren te Amsterdam

promotor: prof.dr. J.L. Theeuwes

copromotor: dr. C.N.L. Olivers

The studies presented in this dissertation were funded by VIDI grant 452‐06‐007 from the Netherlands Organization for Scientific Research (NWO) awarded to dr. Christian Olivers. Beoordelingscommissie Prof.dr. Ed Awh

Prof.dr. Pieter Roelfsema Prof.dr. Werner Schneider Prof.dr. Willem Verwey Dr. Artem Belopolsky Dr. Mark Nieuwenstein

Paranimfen: Paul van Klaveren, MSc Ronald Terpstra, MSc Voorblad: Fotografie: Sam A. Eftegarie, Ir. Handmodellen: Fong Lin, MSc Emma Hameleers, LLM Druk: Off Page, Amsterdam, the Netherlands

Table of contents Chapter 1: Attention and spatiotemporal object representations .................................................. 7

Chapter 2: Object representations maintain attentional control settings across space and time ............................................................................................................... 33

Chapter 3: Object-based attentional control settings depend more on the spatial than the temporal continuity of the object ....................................................... 45

Chapter 4: Object representations maintain attentional control settings for feature information ....................................................................................................... 59

Chapter 5: Abrupt onsets capture attention independent of top-down control settings ........................................................................................................................... 85

Chapter 6: Abrupt onsets capture attention independent of top-down control settings II: Additivity is no evidence for filtering ......................................................... 111

Chapter 7: Abrupt Irrelevant onsets cause inhibition of return regardless of attentional set .............................................................................................................. 137

Summary in Dutch / Nederlandse samenvatting ......................................................................... 149

References .................................................................................................................................... 155

Acknowledgements / Dankwoord ................................................................................................ 165

Curriculum Vitae ........................................................................................................................... 167

Author publications ...................................................................................................................... 168

Chapter 1 Attention and spatiotemporal object

representations

ATTENTION AND SPATIOTEMPORAL OBJECT REPRESENTATIONS

8

Introduction

Around 400 BC, the Greek philosopher Plato proposed his Theory of Forms, which states

that "Forms" (or "Ideas"), and not the material world of change known to us through

sensation, constitute the highest and most fundamental kind of reality. Almost three

millennia have passed since, but many contemporary philosophers and scientists still

agree with Plato’s view that our mind operates on representations of observed objects.

The brain can perform mental operations (e.g. assess an object’s function) on these

representations and uses them to construct a (spatial) model of its direct environment.

Such a model helps the brain to maintain a coherent experience of its surroundings and

also enables it to stay aware of objects of which it (temporarily) has no sensory input.

For instance, imagine that you see a coffee cup in front of you. If you completely turn

your gaze away from the cup, you will still be aware that the cup exists, despite the

absence of its sensory input. Object representations further aid the brain in keeping

track of objects that are temporarily occluded by other objects. For example, when you

witness a cat moving behind a tree, you will probably expect that same cat to reappear a

moment later (assuming it did not come to a halt behind the tree) and at the same time

know that it is not a different cat than the one you saw disappear earlier. In short, the

brain stays aware of objects by maintaining representations of them based on the

assumption that objects are always continuous in both space and time.

The main focus of this thesis lies on how this spatiotemporal continuity of an

object, or the lack thereof, affects the deployment of attention. The first part of the

presented research investigates if knowledge obtained during the first encounter with

an object influences the way it is attended to during subsequent encounters (Chapter 2

to 4). Think of the cup of coffee from before, which was standing on a table in front of

you. Would you expect to find this cup of coffee at the same spot of the table after you

temporarily lost sight of both objects? And what would your expectations be about the

location of the coffee cup when you are presented with a table that looks identical to the

one before, but of which you know it is actually a different table? We investigated if and

how the spatiotemporal continuity of an object affects the preservation of attentional

control settings that one has potentially established for internal properties or locations

of the object. The second part of this thesis addresses whether objects that suddenly

appear in the visual field involuntarily capture attention (Chapter 5 to 7). The sudden

appearance of an object can be seen as an event that violates spatiotemporal continuity

CHAPTER 1

9

and such an event is already known to attract the attention of an observer without his

intention (Jonides & Yantis, 1988; Yantis & Jonides, 1984). We investigated whether this

is also the case when a completely irrelevant newly appearing object has to compete for

attention with a cue that has task-relevant properties. Before discussing the main

research in detail, I first review concepts and background literature that are relevant to

the current work in the next sections of this introduction.

Object representations

Object correspondence through spatiotemporal continuity

For a coherent visual experience, it is important to keep track of objects in the direct

vicinity through space and time. Kahneman, Treisman and Gibbs (1992) were among the

first to provide evidence that episodic representations of objects assist in this process. In

their object preview paradigm, they presented the observer with two boxes located at

opposite sides of the screen. Initially, these boxes would each contain a letter that

disappeared after a short preview period, after which both boxes smoothly moved to

new locations. Once they arrived there, a letter reappeared in one of the boxes and

observers indicated if this letter was also present during the preview period. Responses

were faster when the letter matched one of the previewed ones than when it was a new

letter. More important however was that this repetition benefit was greater when the

matching letter also appeared in the same box (now at a different location), as compared

to the other box. Note that “sameness” here is determined by the motion trajectory of

the box – in other words, its spatiotemporal history – and does not refer to its

appearance (i.e. shape or other features). Kahneman, et al. (1992) proposed that we

create an episodic representation, or ‘object file’, for each object we observe. Object files

contain information about properties of their corresponding physical objects (e.g. color,

shape, or letter identity), and are preserved across space and time. When the

spatiotemporal history of the stimulus suggests that the same object is encountered, its

represented properties are readily available, and if they match the actual visible

properties, responses will be facilitated. In contrast, responses are slowed when the

visible object no longer matches the content of its associated object file.

It has been proposed that spatiotemporal continuity is in fact the most important

contribution to perceiving object constancy (Scholl, 2001, 2007), more so than other

properties such as object identity or surface features. Pylyshyn and colleagues


10

(Pylyshyn, 2000, 2001; Pylyshyn & Storm, 1988) for instance showed that observers are

able to track several identical objects (which thus could not be distinguished by surface

features) on basis of their spatiotemporal properties. Observers were presented with a

search field in which a large number of white dots were continuously moving in random

directions. At the beginning of a trial, one or more of these dots were briefly highlighted

and observers were instructed to track these for a few seconds. After this period, a

single dot was highlighted again and observers had to indicate whether this was one of

the dots they were supposed to track or not. Notably, observers were able to track up to

4 or 5 objects with high accuracy.

Furthermore, Mitroff and Alvarez (2007) used a variant of the object preview

paradigm to demonstrate that continuity in the surface features of an object (e.g. texture,

color or shape) from one instance to the other plays no significant role in same-object

perception, but the spatiotemporal continuity of the object does. When the

spatiotemporal constraints of an object were violated (e.g. when it jumped from one

location to another instead of gradually moving between them), no same-object benefits

were found, even when the object retained the same physical appearance. Vice versa, a

change in features did not affect same object benefits as long as spatiotemporal

consistency was preserved.

Spatiotemporal representations further enable us to keep track of objects that

temporarily disappear from vision through occlusion. This is nicely illustrated by the

tunnel effect (Burke, 1952; Michotte, 1963), which occurs when a moving object

disappears behind one end of an occluder (the ‘‘tunnel’’) and a different moving object

appears at the other end a moment later. When the second object emerges at about the

time and place that the first object should have emerged, assuming it underwent

continuous motion behind the occluder, people tend to perceive both objects as a single

instance. This effect has appeared to be very robust and as long as spatiotemporal

parameters are correct, people can tolerate large changes in color, shape or other

features to the second object (Flombaum & Scholl, 2006). Infants seem to be even less

susceptible to such changes than older children and adults, who will at a point infer that

the second object is different from the first when changes become too large (Bower,

1967; Bower, Broughto.J, & Moore, 1971; F. Xu & Carey, 1996, 2000; Y. D. Xu & Chun,

2006).

CHAPTER 1

11

Contents of object representations

A topic that has been less frequently investigated is which information about an object is

actually maintained with its representation. The object-preview paradigm of Kahneman

et al. (1992) suggests that a representation preserves information about the identity of a

response feature, enabling one to later respond faster to objects that remain consistent

with their object files. This has often been corroborated by other studies using variants

of the object preview paradigm (Kruschke & Fragassi, 1996; Mitroff, Scholl, & Wynn,

2004; Noles, Scholl, & Mitroff, 2005). However, most of these object-reviewing studies

have used displays in which a target object only contained a single response-related

feature. In fact, in many of these studies the previewed and target-defining features

were identical to the response features, such that same object benefits may have been

response-based rather than have a perceptual or attentional basis. Moreover, such

response-based effects have also been found for objects that were merely repeated on

basis of their features and were not spatiotemporally connected. Hommel and

colleagues for instance suggested that one integrates specific object features and

responses that co-occurred in a certain ‘time segment’ (usually a single trial) into an

episodic structure they coined an event file (Hommel, 1998, 2004, 2007; Hommel,

Musseler, Aschersleben, & Prinz, 2001). Keizer, Colzato and Hommel (2008) illustrated

this concept by showing that observers ‘integrate’ their responses to an object with the

direction they see it move. When observers were presented with a same object as in a

trial before that also moved in the same direction, there were response benefits.

However, if either the identity of the object or its moving direction was altered,

responses were slower compared to when both the object’s identity and its moving

direction were new. Keizer et al. therefore reasoned that when the current set of

features match those stored in an event file, previous response information is retrieved

from it and facilitates current responses. Conversely, the information from an event file

can interfere with responses if it only partially corresponds with the current situation.

This study thus shows that response information can be tied to specific objects of which

the correspondence is determined on the basis of feature context rather than

spatiotemporal continuity.

We are aware of only one previous study that looked at pure perceptual effects in

object representations. With a novel paradigm, Yi, Turke-Brown, Flombaum, Kim, Scholl

and Chun (2008) examined the effect of spatiotemporal continuity on the perseverance


12

of complex stimuli, in this case faces. They displayed a pillar on the left and on the right

side of the screen, which each served as an occluder. A trial consisted of two consecutive

events each involving the emergence of a face from behind a pillar. The second face

could either be the same as or different from the first, and it could appear from behind

the same or the other pillar. Using fMRI, Yi et al. found that brain activity in the right

fusiform face-area (FFA) decreased when the face had the same appearance in both

events, which was not that surprising as it is common for neurons to show such signs of

habituation after sustained stimulation. Importantly however, the habituation effect was

stronger when the same face had also re-emerged from the same pillar as it had just

disappeared behind. In other words, the neural coding of the face as one and the same

depended on whether its spatiotemporal history had been violated or not, suggesting

that face information is preserved with representations. This study largely inspired the

work described in the following section of this thesis, as it shows that an object

representation maintains more than simple feature or response information. We

addressed the question whether complex attentional control settings for an object are

also preserved.

Object representations and attentional control settings

The first part of this thesis focuses on the question if attentional selection settings that

have been established for an object can be stored with its spatiotemporal

representation. If we for instance see a platter with snacks and find bread at its top left

corner, do we intuitively expect to find the bread at this same location again the next

time we encounter this same platter? More technically, if a certain part or feature of an

object has been selected before, do these attentional selection settings then persist

across subsequent spatiotemporal changes that the object undergoes and affect

selection again later on?

As illustrated in Figure 1, our main paradigm consisted of two display objects

which were for the largest part hidden behind walls positioned at each edge of the

screen. On a trial, one of these displays would shift to the center of the screen revealing a

visual search array with multiple distractors and one target. This made selection

necessary as there was competition between multiple elements within the object. After

response, the display shifted back behind one of the walls which was not occupied by the

CHAPTER 1

13

other display object. Crucially, in the following trial either the same or the other display

would shift to the center of the screen.

Chapter 2 describes an experiment in which the potential same-object benefit on

selection was measured by repeating the target’s position over trials. As Maljkovic and

Nakayama (1996) demonstrated, observers unintentionally tend to start search at the

location which they previously found the target, leading to response benefits when the

target is indeed found there again the next time. If these selection settings are

furthermore connected to an object representation, observers should be even faster

when this target not only appears at the same location as on the previous trial, but also

on the same object. In other words, intertrial repetitions of the target location should

result in greater performance benefits when the spatiotemporal dynamics suggest that

the search display is the same object as the one which appeared the trial before, as it

would appear from its spatiotemporal trajectory.

The results indeed provided evidence that spatial selection settings for internal

object properties are stored with the object’s representation. Observers were found to

respond faster when the location of the target was repeated, but even more so when it

also appeared in the same object as in the preceding trial. This corroborates earlier

findings that repeating target locations facilitates search over trials (Maljkovic &

Nakayama, 1996) as do entirely repeated display configurations (Chun, 2000; Chun &

Figure 1: Example of the stimulus displays shown in a trial sequence of Chapter 2.

Until response

150 ms

150 ms


14

Jiang, 1998) and extend them by showing that such effects are partly object-bound.

Observers thus are strongly inclined to start search at the same spot as where they

previously found the target, especially when the current display object was

spatiotemporally connected to the previous one.

Chapter 3 looked further into the factor of spatiotemporal continuity itself,

which of course consists of the two separate components space and time. We examined if

same-object perception relies more heavily on only one of the two, or really requires

continuity in both dimensions to occur. This time, there was only one display present

which would shift to the opposite side of the screen on each trial. Centered in the middle

of the screen was a stationary narrow wall, which would temporarily and completely

occlude the display when it passed behind it. Importantly, the display could pass behind

this occluding wall in four possible manners: its motion trajectory was either continuous

(i.e. emerge from behind the occluder at the expected place and moment), temporally

discontinuous (emerge at the expected location, but a different moment), spatially

discontinuous (emerge at the expected moment, but a different location), or

discontinuous in both space and time. The benefits for a repeated target location were

found to be larger when the display object followed a spatially coherent trajectory,

regardless of whether there was a temporal discontinuity. This suggests that persistence

of attentional settings within an object is mostly determined by continuity in the spatial

dimension.

Chapter 4 further investigated if other attentional biases than for the target’s

location are preserved based on spatiotemporal object history. If so, similar object

benefits as for a repetition of the target’s location should be found for the repetition of

other internal object properties. The first experiment was identical to the experiment

described in Chapter 2, except for the addition of an occasional singleton color

distractor. If object representations preserve inhibitory tags for distracting elements in

an object, then one would expect a distractor to interfere less when it reappears in the

same object than in the other one. Distractor interference indeed was lessened when it

had been present the trial before but especially when it reappeared inside the same

object. Repetition of the distractor’s location however did not lead to any further

benefits, suggesting that attentional settings for a distractor are not maintained on the

basis of its spatial location.

CHAPTER 1

15

In a second experiment we examined whether selection settings for the target’s

features also survive occlusion of the object it is displayed on. On any trial, either or both

the target shape and color could be the same or different from the previous trial. A

change of the target’s features had a larger impact on RTs if the display object was

repeated from the previous trial, indicating that object representations can indeed hold

feature-based attentional settings. A mismatch between the observed target features

and those stored in the object representation consequently results in extra response

penalties. Notably, the effect was only apparent for a repetition of shape, but not for

color. As the target was defined by its shape and color was an irrelevant dimension, a

bias might exist toward maintaining only task-relevant information about the target.

In all previous experiments, the two display objects both had the exact same

appearance of a basic black slate. Still, participants were perfectly able to distinguish

them on the basis of their spatiotemporal history and link attentional control settings to

a specific representation. In a third experiment we investigated how much same-object

perception depends on, or can be disrupted by a change of, the exterior appearance of

the objects. The stimuli and task were similar to the first experiment, but this time the

search array was presented inside the display area of a mobile device, which could

either be a white IPod or a black Nokia N95. Between trials, when the display object was

completely occluded by one of the walls, this exterior could change causing the object to

have a completely different appearance when it re-emerged. As the specific object on

which the array was presented could also still switch from trial to trial, this experiment

pitted the spatiotemporal continuity of objects directly against their appearance to

determine which of these two factors forms the more important basis for same-object

perception. According to Flombaum and Scholl (2006) or Mitroff and Alvarez (2007) a

change to an object’s external features should not disrupt same-object effects as objects

are mainly individuated using their spatiotemporal properties. Alternatively, the

findings of Moore et al. (2010) or Moore and Enns (2004) would predict that a drastic

change of the object’s features would shatter same-object perception. We found

attentional selection to be only modulated by the object’s spatiotemporal history and to

remain unaffected by changes to or repetitions of its exterior. Apparently, the sameness

of an object is more predominantly designated by spatiotemporal continuity which thus

also as the only factor determines whether previously established attentional control

settings are retrieved.


16

Taken together, Chapters 2 to 4 show that an observer is able to maintain

attentional selection settings he has established for the internal properties of an object

with its spatiotemporal representation. Information of both the target’s location and its

defining features can survive with the object through occlusion, as long as its

spatiotemporal continuity suggests it to be a single instance. Whether an object is

perceived as the same seems to mostly depend on its continuity in the spatial dimension

and does further not rely on the object’s exterior features. A change to the appearance of

a spatiotemporally continuous object therefore did not have an influence on the reuse of

previously stored attentional control settings.

The above and other studies thus suggest that an object is mainly individuated

and tracked on the basis of its spatiotemporal continuity and not by its appearance.

Moore, Stephens and Hein (2010) reasoned that if features are irrelevant for the

maintenance of object representations, same object effects should still occur when

objects change color during smooth movement in a typical object-preview paradigm.

Instead, they found the opposite to be the case and argued that feature changes interfere

with same object perception, even when an object’s spatiotemporal continuity remains

intact. Moore et al. hence concluded that beside spatiotemporal factors, features also

play an important role in establishing and maintaining object correspondence. Other

studies supporting this notion reported that corrections of misdirected eye movements

to objects that are displaced during saccadic suppression are done on the basis of the

objects’ features (Hollingworth, Richard, & Luck, 2008; Richard, Luck, & Hollingworth,

2008), which suggests that visual working memory also maintains object

representations on the basis of features. Furthermore, a phenomenon known as change-

related persistence (Moore & Enns, 2004) shows that an abrupt change to a moving

stimulus can cause it to be seen as two separate objects: the original object and the

changed object. If the object underwent no changes in the same setting, it was perceived

as a single instance. These studies thus all show that disrupting the features of an object

can disrupt the representation of it as a single object, despite spatiotemporal

consistency, and therefore argue that the role of features in maintaining object

correspondence should not be underestimated.

There however is a possibility that not the changes per sé severed object

correspondence, but rather the abruptness with which they occurred. Abrupt luminance

or polarity changes have been shown to potentially signal the appearance of a new

CHAPTER 1

17

object (Rauschenberger, 2003b) which hence requires a new object representation to be

created (Kahneman, et al., 1992). This process likely requires the object to be evaluated

by attention first, which is hence automatically allocated to it upon its appearance

(Yantis & Jonides, 1984). Attentional capture by the appearance of new objects is the

topic of the second part of my thesis.

Capture of attention by new objects

The sudden appearance of a new object, often signaled by an abrupt onset of its features,

has shown to be an event that attracts the attention of an observer independent of his

goals and intentions (Posner, 1980; Todd & Van Gelder, 1979; Yantis, 1993). This

phenomenon is referred to as attentional capture. Before we continue, it is useful to first

give better description of attention and what is meant with attentional capture.

The world we live in provides such a vast amount of information that the

capacity-limited human brain would quickly become overwhelmed if it had to process

everything that came in through the senses. It therefore needs to make a selection from

its sensory input. This process is referred to as attentional selection. Only the objects or

locations we attend to are processed in more detail and reach our conscious experience

or awareness (Simons & Chabris, 1999). The locus of attentional focus in the

environment frequently changes to obtain a more complete representation of it. When

the properties of the stimulus features in the environment determine what attention is

focused on, orienting is said to be stimulus-driven, or ‘bottom-up’. This exogenous

attention is very fast, crude and not under our voluntary control (Broadbent, 1958;

Treisman & Gelade, 1980; Treisman & Sato, 1990). Top-down (or endogenous) orienting

on the other hand refers to the goal-driven way in which one directs his attention.

Contrary to bottom-up allocation, top-down allocation is “voluntary”, under control of

the observer and led by his goals, beliefs or intentions (Yantis, 1993). Top-down

attention engages and disengages slower from locations than its bottom-up counterpart

(Theeuwes, Kramer, & Atchley, 2000) and operates serially, as opposed to the presumed

parallel nature of bottom-up processing (Egeth & Yantis, 1997).

It is generally agreed that whether or not an object gets represented in visual

cortex depends on the collaborative outcome of both processes (Cave & Wolfe, 1990;

Wolfe, 1994). Brain areas located later in the visual stream are shown to affect the

processing of information by areas earlier in the stream via re-entrant processing (Di


18

Lollo, Enns, & Rensink, 2000), but before these higher areas can do so, they first have to

receive information from the earlier areas. Therefore, the initial evaluation of a scene is

thought to be stimulus-driven, and at this stage only the most salient objects in the

visual field win the competition for representation (Donk & van Zoest, 2008; Theeuwes,

2010), which consequently also results to the suppression of other, less salient, objects.

Endogenous processing kicks in shortly after, during which the goals and intentions, also

called the attentional control settings (ACS), of the observer come into play. Top-down

biases can subsequently increase the strength of relevant, but less salient stimuli, if

salience caused an irrelevant object to win the competition (Desimone & Duncan, 1995;

Reynolds & Desimone, 2003; Tsotsos et al., 1995). In those cases in which an object is so

salient that it is represented at the expense of other stimuli, regardless of the volitional

goals of the observer, one speaks of attentional capture.

The capture of attention is often operationalized as speeded search performance

when an otherwise non-predictive stimulus happens to be the target of a visual search.

In other words, a stimulus is said to capture attention when it is searched with priority,

even when it is irrelevant to the task. Jonides and Yantis (1988; see also Yantis &

Jonides, 1984; Yantis & Jonides, 1990) demonstrated that onsets enjoy such

prioritization with an experiment in which observers were instructed to find a pre-

specified letter among a set of other letters. Some letters were initially masked by figure-

eight placeholders that were present from the start of the trial. These letters, which

constituted the no-onset stimuli, were revealed by removing the placeholders’ line

segments that camouflaged their identity (a method of presentation first introduced by

Todd & Van Gelder, 1979). Simultaneously with the revelation of the no-onset letters,

one other letter appeared at a previously blank location in the visual field and

constituted the onset stimulus. Importantly, the onset stimulus was the target only at

chance level and hence gave the observers no reason to start search at the onsets as they

were not predictive of the target’s location. When the target was one of the no-onset

letters, search times increased linearly with the number of items present in the display

(also called set size). For targets appearing at the onset location however, search times

remained constant regardless of the set size. The search slopes (response time as a

function of number of items present in the display) for onset targets were found to be

shallow, which is considered to be a hallmark for attentional capture. Theeuwes (1994b)

further found that abrupt onsets interfere with search when observers are explicitly

CHAPTER 1

19

instructed to look for a color singleton and thus an onset is not part of their attentional

set. In this same situation, onsets are even shown to capture one’s gaze (also called

oculomotor capture; Theeuwes, Kramer, Hahn, & Irwin, 1998).

Possible explanations for attentional capture by onsets

So what makes an onset so special that it receives attentional priority? It has been

suggested that this tendency is a result of evolutionary development. As onsets signal

the appearance of a new entity that could be a dangerous predator, it is best for

organisms to attend to it as quickly as possible to take appropriate action. In other

words, onsets signal potentially behaviorally urgent events (Franconeri & Simons,

2003).

Others have proposed that it is the luminance increment accompanying an onset

which triggers the shift of attention. The magnocellular visual pathway of the brain is

known to be sensitive to high temporal frequencies. This neurological system is thought

to be very influential in signaling the location to which attention should be directed

(Breitmeyer & Ganz, 1976). The luminance increment of an onset might activate visual

pathways sensitive to high temporal frequencies, which are then responsible for

directing attention to the onset. In support of this notion, Franconeri, Hollingworth and

Simons (2005) demonstrated that removing the luminance increase accompanying an

onset makes it lose capturing power. Likewise, Enns, Austen, Di Lollo, Rauschenberger

and Yantis (2001) showed that certain types of luminance contrast changes to old

objects are already sufficient to capture attention (albeit to a lesser degree).

A profound alternative explanation was given by Kahneman and Treisman

(1984), who proposed that it is not the physiological properties of an onset which

attract attention, but rather that the onset signals the presence of a novel perceptual

object for which a new ‘object file’ needs to be created. Since this process requires

attention to evaluate the object first (although see Kahneman, Treisman, & Burkell,

1983), attention is automatically allocated to any new object which appears in the visual

field. Yantis and Hillstrom (1994) indeed demonstrated that a new object was still

prioritized if its appearance was not accompanied by luminance transient. The presence

of a new perceptual object seemed enough to produce the flat search slopes typical for

attentional capture when the onset was the target. In addition, Enns, et al. (2001)

showed that search for targets indicated by luminance changes was far less effective


20

than targets signaled by the sudden appearance of the new object. They found that

search slopes were steeper for targets designated by luminance increments, in contrast

to the search slopes of new object targets, which remained zero. Furthermore,

Franconeri, Simons and Junge (2004) showed that a new object still captured attention

when it appeared during a period of saccadic suppression. Even though observers thus

not saw the appearance (and hence a luminance increase) of the object itself, the sudden

presence of the object still elicited an involuntary shift of attention. This was further

corroborated by Brockmole and Henderson (2005) who found that observers also made

significantly more eye-movements to new objects that were inconspicuously added

during presentations of natural scenes.

Are abrupt onsets unique in their ability to capture attention?

Feature singletons also capture attention

Some have argued that involuntary shifts of attention can also be elicited by so-called

feature singletons, which are objects that possess unique properties in relation to the

other objects surrounding them, such as a distinct color or shape. In his famous study,

Theeuwes (1992) demonstrated that the presence of a color singleton interferes with

search when another item is the target. He presented observers with a circular array of

circles within which observers had to locate a unique diamond shape and respond to the

orientation of a line inside it. Whenever one of the circles carried a unique color,

response times were higher than when all items were colored the same. Theeuwes

inferred that the color singleton must have captured attention, thereby delaying

selection of and response to the target. Indeed, the diamond target could also be

regarded as a singleton itself because of its unique shape, but a singleton in the color

dimension is simply regarded as being more salient and therefore demands higher

priority in attentional processing (Theeuwes, 1992). Even after extensive practice and

explicit instructions to ignore the color singleton, search performance remained poor

when the distractor singleton was present, suggesting that observers simply were

unable to ignore a singleton and prevent their attention to be captured by it. This finding

has often been corroborated by many other studies (Kim & Cave, 1999; Kumada, 1999;

Lu & Zhou, 2005; Nothdurft, 1993, 2006; Pashler, 1988; Theeuwes, 1995b, 2010)

CHAPTER 1

21

Only onsets can capture attention independent of attention set

Yantis and Egeth (1999) however argued that in most studies where search was

disrupted by a singleton distractor, it was in one or another way task relevant. Either the

target was a singleton itself, or the locations of the singleton distractor and target

coincided at higher than chance level, giving observers an incentive to initially attend

the distractor because of its predictive ability. Singleton distractors were often, as they

called it, nominally irrelevant. Yantis and Egeth (1999) stated that the many cases in

which a singleton did influence search, one could better speak of a top-down

“attentional misguidance” by the singleton than of stimulus-driven attentional capture.

According to Yantis (1993) one can only speak of true stimulus-driven attentional

capture, when the investigated distractor stimulus property is independent of either the

defining or the reported attribute of the target (notions first introduced by Duncan,

1985). The defining property designates the specific feature that defines the target and

the observer has to look for. For instance, if one has to look for a red letter among

distractors with a different color, the defining attribute is the color red. The reported

attribute of the target forms the basis for response. A reported attribute could for

instance be the identity of a target letter. Yantis and Egeth (1999) henceforth made sure

that these criteria of Yantis (1993) were met in their experiments, in which observers

had to indicate the presence of a vertical among randomly oriented line segments and

one line could have a unique color. The singleton distractor and target only coincided at

chance level and the singleton shared neither a reported nor a defining attribute with

the target, as the target was defined by its orientation and the singleton was defined in

the color dimension. The resulting response times showed no benefits when the target

also was the color singleton, nor did the presence of a singleton distractor inflict a cost.

Yantis and Egeth (1999) hence argued that if a highly salient feature singleton is not part

of the observer's attentional control setting, that singleton does not necessarily control

the deployment of attention. Franconeri and Simons (2003) further demonstrated that

onsets are one of few dynamic events that can produce shallow search slopes, and that

color singleton targets are unable to do so if color is unpredictive in an exact same task

environment. This and other studies thus suggest that new-object onsets are truly

unique in their capability to elicit purely stimulus-driven shifts of attention (Enns, et al.,

2001; Franconeri & Simons, 2003; Jonides & Yantis, 1988).


22

One may then wonder, what top-down set in Theeuwes (1992) paradigm allowed

the singleton distractor to capture attention. Bacon and Egeth (1994) proposed that

observers chose to adopt a singleton detection mode, in which they strategically use the

singleton status of the target to guide search. As a consequence however, any item which

possesses unique features is bound to capture attention, thus also singleton distractors.

Conversely, when the target is more difficult to find because it possesses no salient

properties, observers have to fall back on feature detection mode, in which attention

traverses locations that match the task-relevant visual features (e.g. a red element or a

diagonal bar) in a serial fashion. Indeed, when Bacon and Egeth (1994) increased the

variety of shapes in Theeuwes’ (1992) search task, thereby revoking the target’s

singleton status, a color singleton distractor did not interfere with search anymore (but

see Theeuwes, 2004). It is however safe to assume that in most studies showing capture

by onsets (i.e. Jonides & Yantis, 1988; Yantis & Hillstrom, 1994) observers were always

operating in feature detection mode, as the target was defined by a specific letter

identity which possessed no unique properties compared to the other letters present.

Still, onsets were prioritized in search, providing further evidence that attentional

capture by onsets occurs regardless of observers’ search strategies.

Others have proposed that objects can only capture attention if they fall within

the attentional window (Belopolsky & Theeuwes, 2010; Belopolsky, Zwaan, Theeuwes, &

Kramer, 2007; Theeuwes, 1994a, 2010). When search requires attention to be focused

on a small region, the attention window is said to be narrow and attentional capture is

often precluded because salient distractors are likely to fall outside the window. A small

attentional window is thus in a sense similar to feature detection mode, as both assume

effortful search leaves little resources for salient distractors to capture attention.

Conversely, if the task permits or induces attention to be distributed across the visual

field, the attentional window is said to be wide, granting irrelevant salient elements the

opportunity to capture attention. This distributed state is thus in a way comparable to

singleton detection mode, in which selection is guided by unique features across the

visual field. Contrary to the search modes of Bacon and Egeth (1994) however, it has

been shown that attentional capture by onsets can indeed be prevented when attention

is highly focused on a specific location, albeit an (upcoming) target has to appear there

with high spatial certainty (Theeuwes, 1991b; Yantis & Jonides, 1990). In this sense, the

CHAPTER 1

23

modulation of the attentional window size seems to be the only top-down measure one

has against attentional capture by abrupt onsets (Theeuwes, 2010).

Capture of attention by onsets is always contingent on attention set

Some however argue that any form of attentional capture is always completely

contingent on attentional control settings, even capture by onsets (Folk & Remington,

1998; Folk, Remington, & Johnston, 1992). In this view, attentional allocation is fully

under top-down control and objects or events will never capture attention if the

observer is not actively looking for them or has no intrinsic reasons to attend them. To

this end, Folk et al. (1992) devised a pre-cue paradigm in which observers had to

respond to the identity of a target letter (X or =) which was either designated by a

unique red color or by an onset. The stimulus displays used in this paradigm are

depicted in Figure 2. The target letter could appear in one of four placeholder boxes that

were positioned on the corners of an imaginary diamond shape. In the color singleton

condition, the red target appeared together with three white letters which filled the

remaining boxes (hence giving it a singleton status) and in the onset condition the target

appeared as the only white character. 150 ms before presentation of the target display,

one of the boxes was briefly cued. Importantly, this cue could also be defined either by

Figure 2: Example of a trial sequence and the stimulus displays used in the Folk et al. (1992, 1998) pre-cue paradigm. A target, which could be defined as an onset or color singleton, was preceded by a cue of the same or the other dimension. It was found that a cue only had effect when it was of the same dimension as the target. The cue is hence assumed to only capture attention if it contains a task-relevant property. In reality the background was black, black lines where white and the gray elements were red.


24

an onset, in which case only one of the boxes was surrounded by four white dots, or by a

color singleton, in which case one box was surrounded by four red and the other boxes

by four white dots. The cue and target could equally likely appear at any of the four

possible locations and only coincided at chance level. Participants were informed about

the cue’s uninformativeness and were advised that it would be best to ignore it. The

critical finding was that when the dimensions of the cue and target matched and when

they appeared at the same location, there was a considerable response benefit, which

was absent when their dimensions differed; even when the cue was an onset which

according to most studies should have captured attention. Thus, although participants

knew the cue was uninformative, they were not able to ignore it when it possessed a

property that also defined the target. This led Folk et al. (1992) to conclude that a

stimulus is only able to capture attention when it has properties that are contained in

one’s attention set. They called this phenomenon contingent attentional capture (CAC).

How could it be then, that so many studies did find attentional capture by

irrelevant abrupt onsets even when observers were not looking for them? Folk and

Remington (1998) reasoned that in most studies onsets were always task-relevant, in

the sense that the presentation of the target display as a whole was often accompanied

by an onset (or luminance increase), which thus can be regarded as a signal that search

can start. Henceforth, people likely establish a default attention set for onsets, in the

absence of any other clear top-down control settings. Gibson and Kelsey (1998) made a

similar argument that observers’ attention is prone to be captured by any change in the

display (or display wide features) that might indicate the appearance of the target.

When the appearance of the target display in their study was for instance signaled by an

onset and color change, this latter dimension also captured attention, while it did not do

so if an onset was the only signaling attribute. Gibson and Kelsey (1998) hence warned

that many studies claiming to find pure stimulus-driven attention capture might be

confounded by goal-directed processes. However, there have been studies that

eliminated such transients which warn for the target’s appearance and still found

stimulus-driven attention capture. As discussed before, Franconeri et al. (2004) made

sure an observer never directly saw the display change, by presenting the target display

during a period of saccadic suppression. They instructed participants to briefly make an

eye movement to a point below the screen, and at the peak level of this saccade the

target display appeared. Even though participants thus never witnessed the display

CHAPTER 1

25

change, irrelevant salient items still possessed the power to capture attention. In their

second experiment, Franconeri et al. (2004) presented the target display to participants

without telling them what to search for, so that they could not form an attentional set.

After presenting the whole display, participants were told the target’s identity by means

of a voice prompt (see also Belopolsky, Theeuwes, & Kramer, 2005). The revelation of

the target was thus never signaled by a display change, giving observers no incentive to

adopt a default attention set for dynamic events. Even so, when one item in the array

underwent a large contrast change, it still received attentional priority.

Rather than being the result of the strategies of an observer, it can be argued that

the contradicting findings of contingent capture on the one hand and stimulus-driven

capture on the other are attributable to critical differences in experimental design. For

one, whereas onsets mostly appear simultaneously with the target display in studies

supporting stimulus-driven capture, in a typical contingent capture paradigm the onset

cue precedes the target display with at least 150ms. It has been shown that attention can

quickly disengage from a location to which it made an exogenous shift (Kim & Cave,

1999; Lamy, Tsal, & Egeth, 2003; Theeuwes, et al., 2000). This gives attention ample

opportunity to have disengaged from the cued location once the target appears,

especially when the cue is defined by color, making the onset an irrelevant property. On

the other hand, when the target is also defined by an onset, disengagement from an

onset cue naturally would be more difficult as the onset property has become task

relevant and attention shifts might be partly under control of the slower top-down

component. In this case, attention is thus more likely to linger at the cued location,

resulting in the cue validity effect common to the contingent capture paradigm.

Theeuwes (1991a) indeed showed that interference effects dramatically increase when

distractors and targets changed roles from trial to trial. Due to the large uncertainty this

brings about, substantial top-down processing is needed to determine that a distractor

which captured attention is not the target, causing the disengagement of attention to

take longer.

Filtering costs

Folk and Remington (1998) however warned that the simultaneous presentation of a

target and distractor may lead to a non-spatial filtering operation, of which the effects

can easily be confused with those of attentional capture. The filtering account was first

introduced by Kahneman, et al. (1983), who showed that response times increase


26

linearly with the number of items that are concurrently presented with a target, even

when these do not resemble the target at all (e.g. a random dot pattern when the target

is a letter). Kahneman et al. claimed this happens because the appearance of new objects

necessitates the creation of new object files, which process competes with that of the

reallocation of attention and thereby delays it. According to this line of reasoning,

attention thus goes directly to a target, but when it appears together with other items,

attention takes more time to do so. One might quickly notice that both the filtering and

stimulus-driven capture accounts attribute the RT costs incurred by new objects to the

creation of corresponding object files. The critical difference however is that the filtering

account assumes attention is never allocated to the object in doing so (and hence is a

non-spatial process), while the stimulus-driven capture account assumes that a

representation for an object cannot be created without attention evaluating it first,

which is why the object captures attention in the first place (and hence is a spatial

process). Both accounts thus differ vastly in the assumed underlying processes that are

involved in the processing of new objects, but make similar phenomenal predictions

concerning RTs, making it difficult to dissociate them empirically or determine mutual

falsification. Folk and Remington (1998) stated that attentional capture can only be

dissociated from filtering costs (as these are very fleeting according to them) by

separating the presentation of the distractor and target in time, which is exactly what

they did in their contingent capture paradigm. They claimed that many studies finding

response delays while simultaneously presenting a target and distractor actually

demonstrate the occurrence of filtering costs rather than attentional capture.

As can be seen, controversies still remain regarding the effects on attention

caused by the sudden appearance of new objects and how these effects are modulated

by top-down control. This thesis contributes new insights on this matter by directly

pitting stimulus-driven attention capture by new-object onsets against contingent

capture. Importantly, we did this within the CAC task devised by Folk et al. (1992) so

that any results could not be attributed to the use of different paradigms.

Onsets capture attention independent of control settings

The second part of the research presented in this thesis is dedicated to further explore

the ability of abrupt onsets to capture attention when observers are strongly induced to

adopt an attention set for a different feature dimension. To this end, we utilized the

CHAPTER 1

27

contingent capture pre-cue paradigm (Folk & Remington, 1998; Folk, et al., 1992), but

made some important changes. First, both the cue and target were always presented as a

color singleton. Observers had to find a unique red character (again an “X” or “=”) among

three similar white characters and hence were induced to have a strong attention set for

the color red throughout each experiment, making the onset dimension completely

irrelevant. The cue thus also consisted as one set of four red dots again, among other

sets of white dots surrounding the other boxes. Second, the onset distractor did not

appear as a cue surrounding one of the boxes briefly before the target was presented,

but concurrently and as a new object (a placeholder box containing a character)

occupying a previously empty space. This assured that attention did not have the time to

disengage from the onset’s location before the target appeared, which might have been

the case in the classic contingent capture studies of Folk and colleagues, in which any

capture effects might have been absorbed by the inter-stimulus interval (ISI) between

cue and target. Thus, by combining the specifics of well-established contingent capture

and onset capture paradigms, we investigated how irrelevant onsets affected the

allocation of attention, when it is under strict top-down control.

In the experiments presented in Chapter 5, the onset distractor was always

present on half of the trials. Experiment 1 and 2 both demonstrated that the onset

distractor interfered equally in both invalid and valid cue conditions. Experiment 2

controlled for competition by other display changes that could have lessened the

capture effect by the onset, but its results were no different from Experiment 1. Both

Experiment 1 and 2 however left the possibility that the RT costs inflicted by an onset

distractor were the result of a non-spatial filtering operation rather than attentional

capture. Experiment 3 therefore applied the identity intrusion method (Theeuwes,

1995b) to further dissociate these two options. Basically, this method relies on the

assumption that the information at attended locations always gets processed at a high

(semantic) level. Henceforth, if the onset distractor captured attention, it can be

expected that the identity of its character is processed. One may then assume this

character will interfere more with response to the target, if their identities are

incongruent than when they are the same. Since the filtering account assumes that

attention does not visit the locations at which a new object appears, it would predict that

the identity of the distractor would have no effect on response times. These findings

favored the stimulus-driven capture account: after changing the onset distractor


28

character to carry one of the possible target identities (X or =, instead of just a neutral

“O” as in the first two experiments), we indeed found that RT costs were higher when

target and distractor identity were incongruent than when the distractor congruent.

Finally, Experiment 4 controlled if the onset did not capture attention because

participants were searching in singleton detection mode. When each no-onset distractor

character was given a unique color (instead of all being white) and observers were thus

forced to adopt a feature search mode to find the red target, the onset still captured

attention.

Folk and colleagues (Folk & Remington, 1998; Folk, Remington, & Wu, 2009)

nevertheless proposed an alternative explanation for the identity intrusion effect that

we found, namely that parallel processing of the target and distractor was the source of

interference. Lavie (1995) demonstrated that displays which pose a low perceptual load

leave observers resources to process all items in the visual field in parallel, during which

items whose identities compete with that of the target cause interference which is

reflected in prolonged response times. Importantly, parallel processing is spatially non-

specific, which implies that (spatial) attention does not need to visit the locations of the

items for their identities to be processed. In contrast, if the complexity of a display

increases (e.g. due to the addition of extra distractors) search will claim more resources

which prevents parallel search and thereby eliminates the interference effects.

According to Folk et al. (2009), the displays used in our Experiment 3 posed a low

perceptual load, because the color target and onset distractor both were very salient and

therefore ‘popped out’. Henceforth, they claimed that the onset interfered because it was

processed in parallel with the target and not because it captured spatial attention.

However, this perceptual load account was recently challenged by Tsal and

Benoni (2010a, 2010b, 2010c) who showed that the degree of interference by certain

distractors rather depends on the dilution of the display. Dilution is dissociable from

perceptual load and refers to the mere presence of different neutral letters whose

features are visually similar to those of the distractor. To demonstrate this concept, Tsal

and Benoni (2010c) made participants search for a pre-specified letter in the presence

of a highly conspicuous distractor letter. Low-diluted displays only contained these two

letters and therefore simultaneously posed a low perceptual load. Conversely, in high-

diluted displays more distractor letters were present, which either resembled the target

(causing the perceptual load to be high) or possessed a different color (giving the target

CHAPTER 1

29

a unique color, resulting in a low load). The important finding was that a conspicuous

incongruent distractor letter interfered when the display dilution was low, but did not

do so anymore in highly diluted displays, regardless of perceptual load. From a similar

perspective, one could argue that the displays used in Experiment 3 constituted a low

perceptual load as the target and distractor both were very salient, but were diluted by

the presence of the other no-onset distractors. Since the dilution account would in this

case predict that the identity of the onset distractor does not modulate interference, our

finding favors the assumption that the onset distractor captured spatial attention.

The research described in Chapter 6 was conducted in response to Folk et al.

(2009), who argued that filtering costs were still the best explanation for the effects

elicited by the onset distractor in Chapter 5. If the effects of onset presence and color-

based cuing both originate from a same process of spatial capture, these two factors

would have been expected to show an under-additive relationship (Sternberg, 1969).

After all, if capture by the onset nullified any effects of the cue, attention should always

move directly from onset to target and not be affected by cue validity. Filtering and

contingent capture are more compatible in this sense, because attention is expected to

only go to the item that matches the attentional set for color and not go to the location of

the abrupt onset, which hence causes a delay only because it triggers a non-specific

filtering operation. Because capture and filtering operations are presumed to take place

during independent stages of processing, additive effects of color-based cuing and onset

interference would be expected. As pointed out by Folk et al. (2009), this was exactly

what was found in the experiments described in Chapter 5: The interference caused by

the onset presence was equally strong for trials with valid or invalid color cues.

Therefore, if one accepts that the color cue captures spatial attention, one can only infer

that the onset cannot do so as well.

Experiment 1 of Chapter 6 investigated if such a pattern of under-additivity is a

useful diagnostic to determine if two consecutive events separated shortly in time both

captured attention. Assuming it is, then the underadditive relationship should also be

apparent for two events that capture attention contingent on attention set. We took the

Folk and Remington (1998) paradigm and briefly made one of the distractor boxes red

between presentation of the first color cue and the target. This distractor cue was

always invalid. In other words, the displays contained a red cue (valid or invalid), then

potentially a red distractor (invalid), and finally, the target display with a red target.


30

According to the contingent capture theory, the new red distractor should capture

attention away from the initially cued location, since red is what the observers are

looking for, and capture by red is moreover what explains the original cuing effect. If

such capture by a new distractor did indeed erase or reduce all prior cuing effects, the

red distractor should attenuate the benefits of a valid color cue, resulting in under-

additivity. If, on the other hand, there is still residual activation of the first cue strong

enough to affect the reorienting toward or the identification of the target, we may again

observe additivity between cue validity and the presence of the red distractor. The latter

was found to be the case, showing that even two events which must have captured

attention following the contingent capture hypothesis did not show underadditive

effects. This makes underadditivity an unreliable diagnostic for attentional capture.

Clearly, neither an onset distractor nor a contingent distractor was powerful

enough to erase the effects of the prior cueing effect. Would there exist a process at all

which is able to do so? It was hypothesized that only an event which invokes a process

involving a strong stimulus-driven attention shift, like an onset, and at the same time

possesses a task-relevant feature (making disengagement from its location harder) is

able to hold attention sufficiently long for the earlier cueing effect to dissipate.

Experiment 2 thus reintroduced the onset distractor with the goal to find out if the

‘capturing power’ of this distractor increased if it also carried task-relevant features.

Instead of having its normal white bounding box, the onset possessed a red bounding

box each other block. With such a distractor, underadditivity was indeed found between

the cueing and onset effect, suggesting that some events are able to overcome prior

cueing effects, given that these events possess characteristics that elicit both stimulus-

driven and goal-driven attention shifts.

Experiment 3 finally investigated whether responses would benefit when the

onset occasionally was the target itself. If present, the onset was a distractor the

majority of cases and the target was among the no-onset characters. However,

incidentally the red target letter was located inside the onset, albeit at less than chance

level, giving observers no incentive to purposefully start search at the onset.

Nevertheless, responses to onset targets were of the same magnitude as those for a

validly cued no-onset target, indicating that the onset captured attention.

Finally, Chapter 7 provided further evidence that spatial attention had really

been allocated to the location of the onset target described in the previous chapter. A

CHAPTER 1

31

phenomenon which is often used as a spatial marker for attention is Inhibition of Return

(IOR). IOR is best described as a slowing in the allocation of attention to a previously

visited location when the time between first and subsequent attentional shift exceeds

300 ms, only when the first shift of attention to this location was involuntary or

exogenous (Klein, 2000; Posner & Cohen, 1984). IOR is therefore considered a hallmark

for stimulus-driven capture as it is rarely found after voluntary orientation to a location

(although see Berlucchi, 2006). We thus added a condition in which the ISI between cue

and target display was 1000ms instead of 150ms. In the long ISI condition, the onset, if

present, still appeared after 150 ms, but its identity remained hidden until the revelation

of the target display. If attention was initially captured by the onset but shortly after

disengaged from its location, people should be slower if the target appeared at the onset

location a moment later after all. If the onset on the other hand was suppressed by a

non-spatial filtering process, such signs of IOR are not expected as the filtering account

claims attention did not go to the onset upon its appearance. While the onset target as

before enjoyed a response benefit in the short ISI conditions, responses were indeed

prolonged when the ISI was extended, indicative of IOR. As filtering would not have

predicted such a pattern, the results once again flavored stimulus-driven attention

capture by the onset.

Conclusion

In the first part of this thesis, we showed that an observer maintains attentional

selection settings for the internal properties of an object with its spatiotemporal

representation. These selection settings involve information about the location and

features of a target and influence how attention treats this object the next time it is

encountered, as long as its spatiotemporal continuity indicates that it is a single

instance. Whether an object is perceived as the same, seems to depend more on its

continuity in the spatial than the temporal dimension. It does furthermore not rely on

the object’s exterior features, as a change to the appearance of a spatiotemporally

continuous object did not eliminate the reuse of previously stored attentional control

settings.

The second part of this thesis provided evidence that suddenly appearing objects

enjoy a special status for attentional allocation as their spatiotemporally discontinuous

nature demands priority, even when observers are not set to look for them, or are


32

actively looking for something else. The only top-down control we thus seem to be able

to exert on attentional capture by onsets is adjusting the size of the attentional window,

as onsets have been shown to only capture attention if they fall within this area of focus.

Chapter 2

Object representations maintain attentional control settings across space

and time

Schreij, D. & Olivers C.N.L (2009) Object representations maintain attentional control settings across space and time

Cognition, 113(1), 111-116

OBJECT-BASED ATTENTIONAL CONTROL SETTINGS

34

Abstract

Previous research has revealed that we create and maintain mental representations for

perceived objects on the basis of their spatiotemporal continuity. An important question

is what type of information can be maintained within these so-called object files. We

provide evidence that object files retain specific attentional control settings for items

presented inside the object, even when it disappears from vision. The objects were

entire visual search displays consisting of multiple items moving into and out of view. It

was demonstrated that search was speeded when the search target position was

repeated from trial to trial, but especially so when spatiotemporal continuity suggested

that the entire display was the same object. We conclude that complete spatial

attentional biases can be stored in an object file.

CHAPTER 2

35

Introduction

Visual attention is the mechanism by which we select relevant information from a rich

visual world. Evidence so far indicates that attention can be directed not only to specific

locations (Posner, Snyder, & Davidson, 1980) or features (e.g. Wolfe, 1994), but also to

entire objects (see Scholl (2005), for a review). In most of the classic studies on object-

based selection, objects were presented abruptly on the screen and, either after a set

time or after a response, disappeared instantly. Researchers then assume that each trial

provides an independent performance measurement of the condition at hand. In the real

world, objects often behave quite differently. Rather than covering a well-defined

instance in time, objects typically appear and disappear gradually (e.g. by occlusion,

moving in and out of the periphery, or looming). In other words, objects have a history

across space and time. The present study investigates the effect of this spatiotemporal

history of an object on the attentional selection settings applied to that object. More

specifically, it addresses the question as to whether an object representation includes

the way in which attention has previously treated that object, and whether this

information is then preserved across space and time, even when an object temporarily

disappears from vision.

Theorists have argued that for an object representation to be preserved across

space and time, some type of indexing or tokenization of objects is necessary (e.g.

Pylyshyn, 2001), A token is an episodic representation that allows the observer to refer

to “that object, then and there” and thus to track it across space and time (Pylyshyn &

Storm, 1988). Kahneman, Treisman and Burkell (1983) referred to such temporary

episodic representations as object files. Evidence for object files comes from the object

reviewing paradigm (Kahneman, et al., 1992), in which observers typically are

presented with a preview of two objects, each containing a letter. The letters disappear

and the objects then move to a new position, after which one of the initial letters re-

emerges in either one of the objects. The task is to identify the letter. Identification is

speeded when the target letter emerges in the same object as it did before, even though

this object has now changed position. This effect was referred to as “the object-specific

preview benefit”, and we refer to it here as the same object benefit.

An important question is what information about an object is maintained across

space and time. In other words, what properties are bound to an object file or index?

Pylyshyn and co-workers (Pylyshyn, 2001) have argued that indexes are primitive and


36

preconceptual, and should thus contain little information on specific object features, as

long as spatiotemporal continuity is preserved (see also Mitroff & Alvarez, 2007).

However, Flombaum and Scholl (2006) demonstrated that, when a moving object is

briefly occluded by another display element, a change to the object’s color or shape is

better detected when the object moves in a spatiotemporally coherent fashion,

suggesting a link between spatiotemporal and object feature representations. In

addition, the same object benefit in the classic object file studies imply that information

about the identity of the response feature (the letter inside the object) must have been

preserved across the object’s translation (Gordon & Irwin, 1996, 2000; Kahneman, et al.,

1992).

In the present study we investigate the possibility that entire attentional

selection settings as applied to a specific object are maintained in its mental

representation. Imagine the case when only a part of an object is relevant to an observer,

for example the door handle when approaching one’s car, or one’s favorite flavor when

presented with a tray of different tea bags. If a certain part or feature of an object has

been selected before, do these selection settings then survive with the object across

subsequent spatiotemporal changes, and affect attention later on? So far, this question

has been largely unexplored. Object reviewing studies have typically used displays with

only a single response-related feature inside the specified target object. This means that

there was no competition for selection in these displays, and hence no way of testing

whether specific selection settings were preserved with the object. In fact, in many

object reviewing studies the previewed and target-defining features were identical to

the response features, such that same object benefits may have been response-based

rather than perceptual in nature (although this was certainly not the case for all object

file studies, see Kruschke & Fragassi, 1996; Noles, et al., 2005).

In our experiment, the objects of interest consisted of entire visual search

displays containing more than one item, but only one target. Thus, there was

competition between multiple elements within the object, and hence the need for

selection (of the search target). Figure 3 illustrates the procedure. Within a trial, one of

two search displays gradually emerged from behind one of four walls on each side of the

screen, and, after response, moved back to a random unoccupied location behind one of

the walls. Crucially, the search display could emerge from the same side as it

disappeared to on the previous trial and would thus constitute the same object in terms

CHAPTER 2

37

of spatiotemporal continuity, or it could come from a different side and would thus

constitute a different object. A potential same object benefit on selection was then

measured through repeating the target position. Following the object reviewing logic, if

observers selected a certain location within a search display on trial n, they may be

inclined to select the same location again on trial n+1, especially so if the search display

is perceived as being the same object as before. If so, intertrial repetitions of the target

location should result in greater performance benefits when the spatiotemporal

dynamics suggest that the search display is the same object as that appeared the trial

before.

The rationale for this manipulation was inspired by Yi, Turk-Browne, Flombaum,

Scholl and Chun (2008). They asked participants to respond to particular faces while

measuring fMRI activity in the fusiform face area (FFA). The faces appeared from pillars

on either side of the screen. They found that if the same face was repeated from one trial

to the next, FFA activity was reduced, in line with general habituation effects. The

Until Response

Figure 3: Example of stimulus display for a typical trial in Experiment 1. For printing purposes, these images were converted to black and white, but the walls were brick-colored and the search elements were green or red. A typical trial started with a screen with both search displays hidden behind the walls for 1000 ms. Then, over a time course of 150 ms, one of the search displays slid to the center of the screen, and with this exposed the search array. Participants were to report the identity of the letter in the diamond shape. When the participant had given a response, the search display shifted back behind one of the unoccupied walls (within another 150 ms).

150 ms

150 ms


38

important finding was that this reduction was greater when the repeated face appeared

from behind the pillar where it had disappeared on the previous trial. In other words,

FFA activity was modulated by the spatiotemporal history of the face, in addition to its

identity. Whereas that study looked at identity processing as a function of

spatiotemporal object history, here we looked at spatial selection as a function of such

object history.

Experiment

Participants searched for a green diamond inside an array of green circles (as in

Theeuwes, 1992) and responded to the identity of the letter inside it (N or M). By

independently varying the response feature from the target-defining feature, we could

decouple potential response-based benefits from spatial selection-based benefits. The

two main manipulations involved the repetition of the target location, and the

spatiotemporal dynamics of the entire visual search display, both from trial to trial. We

expected that repeating the target location would result in faster response times relative

to a location change, but especially so when the dynamics of the display suggested that

observers were dealing with the same object. For this purpose, after each trial, the

display moved behind one of four walls. On the next trial, the display could then emerge

from behind the same wall (same object) or a different wall (different object).

Previous studies have found evidence for the binding of object features to a

specific motion direction (Keizer, et al., 2008). However, these experiments did not

assess the effects of object binding on selection settings. Furthermore, we were not

interested in the binding of such settings to motion direction per se (which could be

regarded as just another object feature), but to a pure object-type representation that is

maintained across space and time. Thus, in our experiment, whether or not a display

constituted the same object (in spatiotemporal terms) was uncorrelated with whether it

moved in the same direction as it did on the previous trial, by not making objects

consistently return to their starting location. If benefits occur independently of an

object’s motion direction, they can unambiguously be ascribed to the object’s

spatiotemporal characteristics.

CHAPTER 2

39

METHOD

Participants

Sixteen students from the Vrije Universiteit of Amsterdam participated and received

course credit or money in return. They were between 18 and 29 years of age (average

22), reported normal or corrected-to-normal vision and no color blindness.

Stimuli and apparatus

The experiment was run in a dimly lit cubicle, on a PC with a 19” CRT screen (1024 x 768

resolution, 120 Hz), viewed from 75 cm. Stimulus presentation and response recording

were done in E-prime 1.2 (Psychological Software Tools, 2003). Images of a wall were

positioned on each side of the display (covering 7.4 deg visual angle on the left and right

sides, 2.5 deg at the top and bottom), revealing a central square grey background area

(CIE(.289,.316), 4.9 Cd/m2). Each of two square panels (11.0 deg visual angle, black

background, white border, 39.0 Cd/m2) containing the search arrays was initially placed

behind one of the walls, revealing only a single edge. To enhance the “objectness” of the

panels, a thin grey shadow was drawn behind it at the right and bottom sides, 3.2 Cd/m2.

The search elements were positioned on an imaginary circle with a radius of 14.2 deg

visual angle, with at the center a white fixation cross. The distractors were green

(CIE(.280,.623), 7.2 Cd/m2) circles with a diameter of 3.1 deg. The target was a green

diamond with a diameter of 3.7 deg to equate for area. All shapes contained a grey “M”

or “N”.

Design and Procedure

The main factors were: 1) Display Identity (3 levels: the search array appeared on the

same object, which had the same motion direction before search as on the previous trial;

the search array appeared on the same object, which had a different motion direction

than on the previous trial, or it appeared on a different object altogether). 2) Target

Location (target position was the same as or different from the previous trial). 3)

Response (again same as or different from previous trial). All factors were randomly

mixed within blocks. Participants were instructed to look for the diamond and to

respond as fast as possible to the letter inside it by pressing N or M on the keyboard,

while making as few errors and eye movements as possible. They practiced 96 trials, and

then completed 10 blocks of 96 trials each. After each block, the participant received RT


40

and accuracy scores, followed by a break. The experiment lasted approximately 45

minutes.

On each trial, one of the two search displays slid to the middle of the screen from

behind a wall within 150 ms. To prevent possible benefits from previewing the target

location while the display was moving, the display only contained distractor shapes until

it reached the center of the screen. One of the distractors then changed into a target and

RT measurements started. Given the speed of the motion and the abruptness of the halt,

these changes were not consciously noticeable. Participants reported whether the

diamond shape contained an “M” or an “N” character by pressing the corresponding key

on the keyboard. The display stayed on until response and then slid back behind any of

the three unoccupied walls, again within 150 ms. This could be the wall it had emerged

from, or a different wall. Correct and incorrect responses were followed by a high and a

low sound respectively. A new trial then started after 1000 ms.

Results

Trials of which RTs deviated more than 2.5 SDs from the mean (3% of the total) were

removed. Erroneous responses (5%) were analyzed separately. The means of the

remaining RTs were subjected to a 3-way repeated-measures ANOVA with Display

Identity (same object from same side; same object from different side or different

object), Target Location (same or different) and Response (same or different) compared

to previous trial as factors.

Participants were significantly slower when the location of the target had

changed, Target Location, F(1,15) = 106.48, p < .001. They were also slower when the

required response changed, Response, F(1,15) = 7.97, p < .01. There was no main effect

of Display Identity (F < 1, p = .348).

Important for the present investigation, the interaction between Display Identity

and Target Location was significant, F(1,15) = 5.13, p < .05. As shown by Figure 4a,

observers benefited from a repeated target location, but especially so when the search

array appeared on the same object. Figure 4d shows the same object benefits underlying

this interaction. For repeated displays, there was a significant same object benefit when

the same object had the same motion direction [t(15) = 2.10, p < .05] and when it had a

different motion direction [t(15) = 2.28, p < .05] as on the previous trial (with no

difference between these conditions, t(15) = 0.80, p = .434). Thus, there was a clear

CHAPTER 2

41

object-based benefit, regardless of the object’s departure side and motion direction.

When the search display configuration changed over trials, there were no significant

same object costs or benefits.

D)

A) B) C)

620

640

660

680

700

720

740

760

780

Mea

n C

orre

ct R

T (m

s)

same display, same sidesame display, different sidedifferent display

0%

4%

8%

12%

same differentTarget Location

Erro

r

620

640

660

680

700

720

740

760

780

Mea

n C

orre

ct R

T (m

s)

same display, same sidesame display, different sidedifferent display

0%

4%

8%

12%

same different

Response

Erro

r

620

640

660

680

700

720

740

760

780

Mea

n C

orre

ct R

T (m

s)

Same responseDifferent Response

0%

4%

8%

12%

same different

Target Location

Erro

r

-15

-10

-5

0

5

10

15

20

25

30

same different Target location

Sam

e O

bjec

t Ben

efit

(ms)

same sidedifferent side

Figure 4: Results of the Experiment. Mean response times and error rates for A) same and different target locations, as a function of display identity: the search display could have the same start side as in a previous trial, or a different start side, or be a different object altogether. B) same and different responses, as a function of target location (same or different as previous trial). C) display identity as a function of response (same or different as on previous trial). Panel D) shows the same object benefits underlying the interaction of panel A, i.e. the RT differences between same (with both types of start side) and different search display, for the different feature changes in display configurations. The error bars display the standard errors of the mean same object benefit.


42

There also was an interaction between Target Location and Response, F(1,12) =

40.92, p < .001 (Figure 4b). Participants were particularly fast when both the display

configuration and the response feature repeated, as compared to when only one or none

of these properties repeated. There was no interaction between Display Identity and

Response Feature, F(1,15) = 2.30, p = .123 (Figure 4c).

The error pattern followed that of the RTs and there was no evidence for a

speed/accuracy trade-off. The only significant effect was the interaction of Target

Location and Response, F(1,15) = 32,73, p < .001. Relatively more errors were made

when the location changed but the response stayed the same.

Discussion

The results support the hypothesis that spatial selection settings for internal object

properties are stored in the object’s mental representation. Repeating the target location

led to greater benefits when these repetitions occurred within the same object, than

when they occurred within different objects – as defined by the spatiotemporal

trajectory of moving back and forth from behind an occluder. This indicates that

observers have a stronger tendency to look at the same spot as where they previously

found the target, when the current display object was spatiotemporally linked to the

previous object.

The results also indicate that the repetition benefits are object-specific (i.e. tied to

the spatiotemporal history of the display object) rather than feature-specific (i.e. tied to

a single motion direction). Same object benefits occurred both for displays that had

returned to their old position (and hence came from the same direction) and for displays

that had not returned to their old position (and thus re-emerged from a new direction).

The fact that we retain location-specific control settings for an object is

consistent with findings of Kristjansson, Mackeben and Nakayama (2001). They asked

observers to search for a target, which was positioned within a cue consisting of two

horizontal lines. Participants were slower when the position of the target within the cue

changed between trials. If we regard the cue as an object within which the target could

appear, these findings corroborate ours, in that search performance deteriorated when

the new spatial relationship between the target and cue object was inconsistent with the

one participants had learned on the previous trial.

CHAPTER 2

43

Studies by Tipper and colleagues also suggest the linking of attentional control

settings to object files (Tipper, Brehaut, & Driver, 1990; Tipper, Grison, & Kessler, 2003;

Tipper, Weaver, Jerreat, & Burak, 1994). These studies showed that inhibition of

distractor objects (as measured through negative priming and inhibition of return)

survives across spatiotemporal changes of these objects. This at least suggests that

object files can include an inhibitory tag. However, note that in the Tipper studies only a

single, response-related feature was used inside the target object, and hence it may have

been the response associated with the object that may have been inhibited, and not

selection settings per se, as applied to information contained within the object file.

It has been demonstrated before that target location repetitions facilitate search

from one trial to the next (Maljkovic & Nakayama, 1996). In addition, repetition of the

entire spatial configuration of a display also facilitates search (Chun, 2000; Chun & Jiang,

1998). In the current study we extend these findings by showing that such repetition

effects are partly object-bound. Search was speeded when target location was repeated,

but more so when presented on an object that could be spatiotemporally linked to the

search display of the previous trial. The interaction between target location and

response repetition we found here is also found more often in the intertrial priming

literature (Hommel, et al., 2001; Huang, Holcombe, & Pashler, 2004). A repetition of both

factors typically yields fastest performance, whereas a repetition of either property may

lead to even slower performance than when both change. In any case, none of the

response effects here interacted with display identity suggesting that the specific

responses are not linked to the object. Our results show that the attentional selection

settings prior to response selection, in contrast, are linked to the object representation.

Thus, using the objects’ spatiotemporal consistency, we can keep its mental

representation active when it disappears from vision and retrieve useful selection

information from this representation when it reappears.

Acknowledgments

This work was supported by VIDI grant 452-06-007 from the Netherlands Organization

for Scientific Research (NWO) awarded to CNLO. We thank the reviewers for their very

helpful comments and suggestions.

Chapter 3 3: Object-based attentional control settings

depend more on the spatial than the temporal continuity of the object

Schreij, D. & Olivers C.N.L (submitted) Object-based attentional control settings depend more on the spatial than the temporal continuity of

the object

OBACS DEPEND MORE ON SPATIAL THAN TEMPORAL CONTINUITY

46

Abstract

It has been shown that specific attentional control settings for an object are preserved

by binding them to the object’s spatiotemporal history. The current study investigates if

the persistence of these attentional control settings is more constrained by spatial or by

temporal factors. Observers searched a display for a target shape among multiple

distractors. The target location could repeat or alternate from trial to trial. This visual

search display was integrated in a moving object that would then pass behind a

stationary occluder before the next visual search display appeared. The occluded motion

trajectory was either continuous (i.e. emerge from behind the occluder at the expected

location and moment), temporally discontinuous (emerge at the expected location, but a

different moment), spatially discontinuous (emerge at the expected moment, but a

different location), or discontinuous in both space and time. Search target repetition

benefits were larger when the display object followed a spatially coherent trajectory,

regardless of whether there was a temporal discontinuity. We conclude that persistence

of attentional settings within an object is mostly determined by continuity in the spatial

dimension.

CHAPTER 3

47

Introduction

For a coherent visual experience, it is important to keep track of objects through space

and time. Kahneman, Treisman and Gibbs (1992) provided evidence that episodic

representations of objects assist in this process. In their classic object preview paradigm

they presented participants with two boxes, each containing a unique letter. They

allowed participants to preview the display for about a second, after which the letters

disappeared and both boxes started to move to new locations. Once both objects had

arrived at their destination, a single letter reappeared in one of them, and participants

had to respond to its identity. Responses were found to be faster when the target letter

matched one of the previewed ones than when it was a new letter. Importantly, this

repetition benefit was greater when the matching letter appeared in the same box (now

at a different location), as compared to the other box. Note that “sameness” here is

determined by the motion trajectory of the box – in other words, its spatiotemporal

history. Kahneman, et al. (1992) proposed that we create an episodic representation, or

‘object file’, for an object we observe. Object files contain information about properties

of their corresponding physical objects (e.g. color, shape, or letter identity), and are

preserved across space and time. When the spatiotemporal history of the stimulus

suggests that the same object is reencountered, its represented properties are readily

available, and if they match the actual visible properties, responses are facilitated. In

contrast, responses are slowed when the visible object no longer matches the content of

its associated object file.

Later work has indicated that the information that can be tied to an object file

ranges from simple features, such as color and shape, to more complex representations

such as faces and abstract concepts (Flombaum & Scholl, 2006; Gordon & Irwin, 1996,

2000; Kruschke & Fragassi, 1996; Noles, et al., 2005; Yi, et al., 2008). Recently, Schreij

and Olivers (2009; submitted) have provided evidence that attentional control settings

are also preserved across spatiotemporally coherent instances of objects. They devised a

paradigm in which two visual search displays were hidden behind walls flanking the

screen. On each trial, one of the displays would move to the middle of the screen.

Participants were instructed to find a diamond-shaped target among circle-shaped

distractors, and respond to the letter printed inside (cf. Theeuwes, 1992). After

response, the display would move back behind one of the walls. There were two

important manipulations: First, from one trial to the next, either the same display object


48

would re-emerge again from behind the wall it had just disappeared behind, or the other

display object would now slide to the middle of the screen. Second, within the emerged

display object, the target was either positioned at the same location as on the previous

trial, or at a different location. Previous work has shown that observers show a

preference for the location where they previously found the target (Maljkovic &

Nakayama, 1996). The hypothesis was that if such spatial selection biases are at least

partially stored with a representation of the entire display object, then this information

may subsequently be retrieved when the spatiotemporal dynamics of the object suggest

that the same search display has re-appeared (i.e. by emerging from the wall the

previous display had disappeared behind), and thus lead to further benefits. This was

indeed found: Search on repeated target trials was especially fast when the display re-

emerged from its last-known position. This provides evidence that relevant target

location information is stored with the spatiotemporal representation of an object.

Follow-up work has indicated that not only target location, but also target feature

information is stored with the object (Schreij & Olivers, submitted).

The present study investigates which aspect of the stimulus is the most important

for the preservation of attentional control settings. In earlier work, Mitroff and Alvarez

(2007) had already demonstrated that continuity in surface features of the object (e.g.

texture, color or shape) from one instance to the other does not necessarily result in a

same object benefit. Instead, the perception of an object as one and the same appears to

depend primarily on its spatiotemporal continuity, as the same object benefit

disappeared whenever the displacement of an object violated natural spatiotemporal

constraints. Likewise, Schreij and Olivers (submitted) found visual search benefits for

spatiotemporally coherent displays regardless of a change in identity of the display

objects – that is, whether they were part of a black phone or a white music player from

instance to instance. The importance of spatiotemporal continuity is also nicely

illustrated by the tunnel illusion (Burke, 1952), which occurs when a moving object

disappears behind an occluder (the ‘‘tunnel’’), followed by the appearance of a different

moving object at the other end. When the second object emerges at about the time and

place that the first object would be expected to emerge, people tend to perceive both

objects as a single instance that underwent continuous motion behind the occluder, in

some cases even when the object changes its appearance. This effect has previously been

used to show that both spatial and temporal continuity play a role in the preservation of

CHAPTER 3

49

object features such as shape and color (Flombaum, Kundey, Santos, & Scholl, 2004;

Flombaum & Scholl, 2006; we will return to this in the discussion). Here we use a variant

of the tunnel paradigm to investigate if spatial continuity, temporal continuity, or both

are necessary for the preservation of attentional control settings across two instances of

an object.

Examples of the stimulus displays are shown in Figure 5. In a visual search

display, participants had to locate a diamond shaped target among circle distractors and

identify the letter (M or N) inside it. The display was positioned at one of four quadrants

of the screen, in the center of which there was a brick wall serving as an occluder. After a

response (i.e. between trials) the entire search display object moved to the other side of

the screen, passing behind the brick wall in the process. When the search display re-

emerged from the other side of the wall, the target could have the same or a different

location than before the object disappeared. Target location repetitions were expected

to result in faster response times (Maljkovic & Nakayama, 1996). The crucial

manipulation was that the displacement of the display object to the other side of the

occluding object was not always spatiotemporally coherent and could breach spatial and

temporal constraints. Concretely, the search display could 1) move to its destination

smoothly and uninterrupted (continuous), 2) pause its movement for a full second while

occluded by the wall (temporally discontinuous), 3) re-emerge from a different vertical

position than when it disappeared (spatially discontinuous), 4) or be subject to both

these disruptions concurrently (spatiotemporally discontinuous).

On the basis of our previous findings (Schreij & Olivers, 2009), we expected to

find a same object benefit for the continuous condition, when both spatial and temporal

continuity are preserved, relative to the spatiotemporal discontinuous condition. That is,

search target repetition effects were expected to be larger when the display object was

seen as one and the same as the previous search display, then when it was seen as

different. Our interest lies in which conditions of discontinuity are able to eliminate this

benefit. If an object only needs to be continuous over time, a spatial discontinuity should

not eliminate same object benefits. Alternatively, if the object only needs to be spatially

continuous, a temporal discontinuity should not eliminate the same object benefit. The

final possibility is that the maintenance of an object representation requires continuity

in both space and time, in which case neither the spatial or temporal discontinuity

conditions should show benefits for a repeated target location. The results suggest that


50

1000 ms

Temporally discontinuous

Spatially discontinuous

Spatiotemporally discontinuous

Figure 5: Illustration of the stimulus displays in a typical trial. In the Continuous condition, the search display moved behind the wall to the other side of the screen in one smooth movement. In the Temporally discontinuous condition, the display stopped moving for 1 second when completely occluded by the wall. In the Spatially discontinuous condition, the display moved smoothly to the other side of the screen again, but had swapped its position along the vertical axis (from bottom to top of the screen or vice versa) once it re-emerged from the other side of the occluder. In the Spatiotemporally discontinuous condition, it paused for a second while occluded, and had swapped vertical position once re-emerged. In the real stimulus displays, the walls had a slight red hue and the background was gray.

1000 ms

Continuous

CHAPTER 3

51

object spatial continuity is in principle sufficient to generate a same object benefit for

attentional control settings.

Experiment

METHOD

Participants

Fourteen students (7 male) from the VU University of Amsterdam participated in

exchange for money or course credits. All were between 17 and 25 years of age and

reported having normal or corrected-to-normal vision and no color blindness.

Apparatus

The experiment was run on a HP Compaq with a 2.6 GHz Pentium 4 processor and 512

MB of RAM. The stimuli were presented on a 19” Iiyama Vision Master Pro 454 CRT

screen with loudspeakers, with a refresh rate of 120 Hz and with a resolution of 1024 x

768 pixels. The “M” and “N” keys on a normal keyboard were used to register the

responses. Stimulus presentation and response recording were done in E-prime 1.2

(Psychological Software Tools, 2003). The experiment was executed in a dimly lit and

soundproof room, in which participants were seated at a distance of approximately 75

cm from the screen.

Stimuli

An image of a wall (7.4o visual angle wide) was positioned in the middle of the display,

stretching from the top to the bottom of the screen. The wall was drawn on an evenly

colored grey background (CIE(.289,.316), 4.9 Cd/m2). A square area containing the

search array was placed next to the wall, in one of four quadrants of the display. This

search display had a black background and a white border, CIE(.282,.310), 39.0 Cd/m2,

with 0.07o width. The diagonal of the square search display was 5.2o. To generate an

impression of depth in the display and to enhance the perception of the search display

as a real object, a thin shadow was drawn behind it at the right and bottom sides,

CIE(.0272,.330), 3.2 Cd/m2. The search elements were positioned on an imaginary circle

with a radius of 2.3o visual angle. A white fixation cross was located at the center of this

circle. The individual search elements consisted of circles and diamonds, with a visual

angle of 0.5o and 0.6o respectively. The difference in visual angle between a circle and a


52

diamond shape was necessary, because this adjustment equalized the surface sizes of

these two shapes. The shapes were all colored green, CIE(.280,.623), 7.2 Cd/m2, except

for the distractor, if present, which was colored red, CIE(.619,.355), 9.0 Cd/m2. The

shapes contained either an “M” or “N” character, of a grey color identical to that of the

main background. The display moved from its starting position to the center of the

screen (behind the wall) in 300 ms, and another 300 ms to move from behind the wall to

its new position. A continuous displacement from origin to destination would thus take

600 ms.

Design and Procedure The main factors of interest were: 1) Target Location (the target position was the same

as, or different from, the previous trial). 2) Response (again same as, or different from,

previous trial). 3) Spatiotemporal continuity. The display would either a) move behind

the wall with constant speed and vector (continuous), b) stop for a second when behind

the wall (temporally discontinuous), c) reappear from behind the wall on the opposite

vertical half of the screen than it disappeared behind (spatially discontinuous), or d) be

subject to both latter events at the same time (spatiotemporally discontinuous).

Together, this resulted in a 2x2x4 design.

Participants were tested in a one hour session. Before the experiment started,

oral and written instructions were given to familiarize them with the task. They were

asked to look for the diamond target, while ignoring all other items, and to respond as

fast as possible while making as few errors and eye movements as possible (they did not

have to keep fixation at a central point). Participants were to report whether the

diamond shape contained an “M” or a “N” character by pressing the corresponding key

on the keyboard. Correct and incorrect responses were followed by a short high

frequency tone and a slightly longer low frequency tone respectively. Participants were

first presented with a practice block containing 80 trials. After completion, participants

were requested to call the experimenter to check their scores. The main experiment

consisted of 8 blocks of 112 trials each. In each block there were an equal number of

combinations for each of the factors. After each block, the participant received RT and

accuracy scores followed by a short break.

At the beginning of a trial, the search display was located at one of the four

possible locations next to the wall. After response, the display would move behind the

wall to a new location at the other side of the wall. When moving, the search display only

CHAPTER 3

53

contained green circles (with N or M inside each of them), as to not give away the

display arrangement during the motion. It deserves mentioning that given the speed of

the motion, and the abruptness of the halt, these changes were not consciously

noticeable if one was not instructed about their occurrence beforehand. As soon as the

display came to a halt on the opposite side of the wall, one of the items changed into the

diamond target again and response time measurements were started for a next trial.

Results The analyses focused on response times (RTs). Erroneous responses (4.6% of the trials)

and trials on which RTs were deviating more than 2.5 SD from the mean for each cell

(another 2.1%) were removed from the dataset. The means of the remaining RT data

were submitted to an ANOVA with Target Location (same, different), Response (same,

different) and Spatiotemporal Continuity (continuous, temporally discontinuous,

spatially discontinuous, spatiotemporally discontinuous) as factors.

There was a significant main effect of Target Location, F(1,13) = 77.88, p < .001.

As expected, responses were faster when the target location was repeated between

trials. There also was a significant main effect of Response, F(1,13) = 6.69, p < .05,

reflecting faster responses when the response feature (M or N) was repeated.

Figure 6: Results of the experiment. A) Mean correct RTs for the various Spatiotemporal Continuity conditions as a function of repeated or alternated target locations. B) Same object effects for a continuously moving display and displays that suffered a temporal or spatial discontinuity in their displacement. The spatiotemporal discontinuous condition was taken as a baseline and was substracted from RTs in the other conditions to obtained the depicted values. Error bars depict one standard error of the mean effect.

B)

A)


54

Importantly, the Target Location x Spatiotemporal Continuity interaction was

significant, F(3,39) = 5.97, p < .01. This interaction is depicted Figure 6a. The effects of

target location repetition were larger for displays that had followed either a fully

continuous or a spatially continuous trajectory, than those that had followed a spatially

disrupted or both temporally and spatially disrupted trajectory. Figure 6b depicts this

same interaction, but now as “same object effects” (SOE) relative to the spatiotemporally

discontinuous condition, which was taken as a baseline. Thus, the SOE is the additional

location repetition benefit found for spatially and/or temporally coherent objects. As

can be seen, continuous objects resulted in a same object effect of 22 ms, which was

significant at F(1,13) = 17.62, p < .001. The temporal discontinuity did not destroy this

effect, still resulting in a significant 17 ms same object effect, F(1,13) = 6.27, p < .05,

which did not differ significantly from the continuous condition, F<1, p> .5. However, the

spatial discontinuity reduced the same object effect to nil, F < 1, p > .5, a reduction that

was significant when compared to the continuous and temporally discontinuous

conditions, F(1,13) = 17.62, p < .001, and F(1,13) = 10.51, p < .01 respectively. Thus,

when the display was subject to a spatial or spatiotemporal discontinuity, the effect

elicited by the repetition or alternation of the target’s location was attenuated compared

to the continuous and temporal discontinuous conditions. Finally, the Target Location x

Response interaction was significant, F(1,13) = 19.86, p < .001. Responses were speeded

when both the target location and the response feature were repeated. No other

interactions reached significance (Fs < 1.29, ps > .29).

An ANOVA on the error rates with the same factors revealed no significant effects.

Table 1 shows the error rates as a function of target location and spatiotemporal

continuity.

Average error rates SearchField GapEvent different same

None 5% 4% Spatial 5% 5% Spatiotemporal 5% 4% Temporal 4% 5%

Table 1: The error rates as a function of target location and spatiotemporal continuity.

CHAPTER 3

55

Discussion

Schreij and Olivers (2009; submitted) have shown that observers maintain attentional

control settings for relevant locations or features inside an object. When the same object

is later reencountered (for instance after disocclusion) these attentional control settings

are more readily available to guide attention. The current study shows that the retrieval

of these attentional control settings is hampered when a display object has been subject

to a spatial or spatiotemporal discontinuity while moving behind an occluder. If the

display object reappeared from behind a different part of the wall than its previous

trajectory would lead to expect (spatial discontinuity) or additionally paused for a

moment when entirely occluded by the wall (i.e. spatiotemporal discontinuity), the

beneficial effect of a repeated target location was attenuated compared to when the

display moved in a spatiotemporally continuous fashion. A temporal discontinuity in the

object’s movement also did not disrupt the maintenance of attentional control settings.

When the display stopped behind the occluder for a moment but continued along the

same trajectory as before it disappeared, the additional beneficial effects of target

repetition were preserved. In other words, there was a same object benefit. The

persistence of attentional control settings for an object thus appears to be more

constrained by the spatial than by the temporal characteristics of the object’s dynamics.

Response selection itself (i.e. whether an N or M had to be pressed) was not

affected by the spatiotemporal continuity of the display object, corroborating the

findings of Schreij and Olivers (2009). This indicates that only spatial selection settings

are maintained with an object representation, and response selection is not. However,

response repetition effects did in turn interact with location repetition effects, which

suggests a cascade of stages. First, the target is spatially selected within the object with

help of information stored in the spatiotemporal object representation, and then the

response is selected, which is in turn influenced by the spatial selection process.

Our findings are largely in line with an earlier study of Flombaum and Scholl

(2006), who deployed a change detection task to demonstrate that when the occlusion

and disocclusion of an object occurs in a spatiotemporally incoherent fashion, the

disoccluding object tends to be perceived as a different instance. Flombaum and Scholl

presented participants with various oscillating shapes that were temporarily occluded

by other, stationary, objects along their trajectory. During occlusion a moving object

could change shape or color and participants had to detect this change once the object


56

reappeared. Detection rates were higher when an object moved behind an occluder in a

spatiotemporal coherent way, than when it paused for a moment behind the occluder, or

reappeared from an unexpected part of the occluder. Consistent with object-file theory,

Flombaum and Scholl reasoned that in order to efficiently compare the current state of

an object with its previous state, it has to be perceived as the same object in terms of its

spatiotemporal history. However, their finding that a temporal discontinuity also breaks

the object file is at odds with our present findings showing that attentional settings are

preserved across such discontinuities. This is not just a fluke of the present study. Note

that in our previous study (Schreij & Olivers, 2009), there was also a temporal

discontinuity between trials: There a search display would disappear behind a wall on

one trial, and after a pause of one second the next trial would start and a display would

appear from either the same wall or a different wall. This suggests that observers can

bridge a temporal gap as long as there is sufficient other evidence (in this case spatial)

that one is dealing with the same object.

Why then did Flombaum and Scholl (2006) find that temporal discontinuities

affected object persistence? One possible explanation is that in their study the temporal

consistency of the objects was not the only thing that changed. As the task was a change

detection task, the objects regularly changed features form one appearance to the next.

It could be that object persistence is mediated by featural consistency of the object when

it is subject to a temporal discontinuity. That is, briefly pausing objects will be regarded

as one and the same, unless they also change feature, in which case there is sufficient

evidence for a new object. This notion is supported by a study of Flombaum, Kundey,

Santos and Scholl (2004), who used a foraging task to explore the tunnel effect in rhesus

monkeys. The monkeys watched as a lemon rolled down a ramp containing two occluder

screens. When the lemon came to rest behind the first occluder (located halfway across

the ramp), a kiwi started rolling from the other end of the screen and eventually became

occluded behind the second screen at the bottom of the ramp. If the kiwi emerged at the

moment the lemon should have, had it rolled on, then the monkeys only searched for

food behind the second screen – as if the lemon had just transformed into a kiwi. In

contrast, when the disappearance of the lemon and the emergence of the kiwi was

interrupted by a brief pause (i.e. a temporal discontinuity), most monkeys searched for

food behind both occluders, apparently perceiving two distinct objects. In other words,

they must have inferred (on the basis of the featural difference in combination with the

CHAPTER 3

57

temporal gap) that the lemon must have remained behind the first occluder. Importantly

however, when a lemon disappeared behind the first occluder, but a lemon also re-

appeared at the other end, a temporal gap had no such effect: The monkeys then only

searched for the lemon behind the last occluder the majority of times. This demonstrates

that a temporal gap does not need to disrupt object persistence, given that the occluding

and disoccluding objects are featurally consistent. In the current study, the features of

the search display object also did not change during occlusion, possibly explaining why

its representation survived a temporal discontinuity.

In conclusion, the current study shows that attentional control settings are best

preserved when an object passes behind an occluder in a spatiotemporal coherent

fashion. Whether one perceives an object as the same or different, and hence whether

one is able to efficiently retrieve previously established attentional control settings from

the object’s representation or not, seems to largely depend on the object’s spatial

continuity and to a lesser degree on its continuity in the temporal dimension.

Acknowledgments

This work was supported by VIDI grant 452-06-007 from the Netherlands Organization

for Scientific Research (NWO) awarded to CNLO. We thank the reviewers for their very

helpful comments and suggestions.

Chapter 4 Object representations maintain

attentional control settings for feature information

Schreij, D. & Olivers C.N.L (under revision). Object representations maintain attentional control settings for feature information.

OBACS FOR FEATURE INFORMATION

60

Abstract

For stable perception, we maintain mental representations of objects across space and

time. An important question remains what information is stored in or linked to such a

representation. Recently, we reported evidence for the preservation of spatial

attentional control settings across instances of the same object, as defined by

spatiotemporal history. Here we further investigate which attentional settings are

stored with a spatiotemporal object representation. Observers conducted visual search

for a target among multiple distractors on a search display, in which the target location

or feature (here shape) could repeat from trial to trial. Importantly, the entire visual

search display was part of an object that could move in and out of view. Responses were

speeded when the target property repeated, but especially when the motion suggested

that the same object had emerged. We show that this same object benefit is tied to task-

relevant target information, and not to irrelevant target or distractor information.

Additionally, we show that the maintenance of these attentional control settings is not

affected by a change in object identity, but is specific to an object’s spatiotemporal

history.

CHAPTER 4

61

Introduction

To help keep a stable percept of the world, it is proposed that the visual system

maintains mental representations of objects across space and time. Classical empirical

support for this idea was provided by Kahneman, Treisman and Gibbs (1992; see also

Treisman & Kahneman, 1983) with their object preview paradigm. Participants were

initially shown two boxes each containing a unique letter. Participants previewed the

display for about a second, after which the letters disappeared. Both boxes then moved

to new locations. Once both objects had arrived at their destination, a single letter

reappeared in one of them, and participants had to respond to its identity. As would be

expected, responses were considerably faster when the target letter matched one of the

previewed ones than when it was a whole new letter. The important result was that this

benefit was greater when the matching letter appeared in the same box (now at a

different location), as compared to the other box. This same object benefit led

Kahneman, et al. (1992) to propose that we create an episodic representation, which

they termed an ‘object file’, for each object we observe. Object files contain information

about the properties of the corresponding physical objects (e.g. location, color, shape, or

letter identity). When the same object is then encountered again, its represented

properties are readily available, and when they match the actual visible properties, a

rapid response is achieved. In contrast, responses are slowed when there is a mismatch

between the visible object and its object file.

It has been proposed that it is especially spatiotemporal continuity which

determined whether an object is experienced as one and the same (Scholl, 2001).

Consistent with this, Mitroff and Alvarez (2007) used a variant of the object preview

paradigm, and demonstrated that continuity in the surface features of the object (e.g.

texture, color or shape) from one instance to the other plays no significant role in the

same object benefit, but the spatiotemporal continuity of the object does. When

spatiotemporal constraints of an object were violated (e.g. when it jumped from one

location to another instead of gradually moving between them), no same object benefits

were found, even when the object retained the same physical appearance. Vice versa, a

change in features did not alter the same object benefit as long as spatiotemporal

consistency was preserved. Spatiotemporal continuity enables us to keep track of an

object even when it temporarily disappears from vision (for instance through occlusion;

Flombaum, Scholl, & Pylyshyn, 2008; Pratt & Sekuler, 2001). In other words, an object


62

does not cease to exist in our experience if we cannot see it for a moment and we will be

aware that the object is ‘there’ as long as it moves behind an occluder in

spatiotemporally coherent way. Flombaum and Scholl (2006) illustrated this with a

study in which participants were presented with various shapes that were moving back

and forth across the screen, during which these shapes were temporarily occluded by

other, stationary, objects. During occlusion a moving object could change shape or color

and participants had to detect this change once the object reappeared. Detection rates

were higher when an object moved behind an occluder in a spatiotemporal coherent

way, than when it paused for a moment behind the occluder (temporal gap), or

reappeared from an unexpected part of the occluder (spatial gap). Consistent with

object-file theory, Flombaum and Scholl reasoned that, in order to efficiently compare

the current state of an object with its previous state, it has to be perceived as the same

object in terms of its spatiotemporal history.

In a comparable study, Yi, Turk-Browne, Flombaum, Kim, Scholl and Chun (2008)

used fMRI to investigate the effect of spatiotemporal history on physically identical or

distinct faces. They displayed two pillars, one on the left, and one on the right. These

served as occluders for the faces. Each trial consisted of a sequence of two events, each

involving the emergence of a face from behind a pillar. The second face could be the

same as the first or different, and it could appear from behind the same or a different

pillar. Yi et al. found that brain activity in the right fusiform face-area (FFA) was reduced

when the identity of the face was the same from one event to the next. This is expected

on the basis of habituation of neurons in response to sustained stimulation. Importantly,

this habituation was stronger when the same face had also re-emerged from the same

pillar as where it had just disappeared. In other words, the neural coding the face as one

and the same depended on whether its spatiotemporal history had been violated or not.

Many studies have thus attempted to assess how object representations are

referenced and maintained, but few have examined what kind of information is actually

stored within, or bound to, the representation. With this purpose, Schreij and Olivers

(2009) investigated if attentional control settings are maintained with object

representations. They devised a paradigm in which two visual search displays were

hidden behind walls flanking the screen on all sides. On each trial, one of the displays

would move to the middle of the screen. Participants were instructed to find a diamond-

shaped target among circle-shaped distractors, and respond to the letter printed inside

CHAPTER 4

63

(cf. Theeuwes, 1992). After response, the display would move back behind one of the

unoccupied walls. There were two important manipulations: First, from one trial to the

next, either the same display object would re-emerge again from behind the wall it had

just disappeared behind, or the other display object would now slide to the middle of the

screen. Second, within the emerged display object, the target was either positioned at

the same location as on the previous trial, or at a different location. Previous work has

shown that when observers have selected the location of a target, they are likely to

select that location again on the next trial (Maljkovic & Nakayama, 1996). The

hypothesis was that if such spatial selection biases are at least partially stored with the

spatiotemporal representation of the entire display object, then this information is

subsequently retrieved when the same display object appears again from behind the

same wall, leading to further benefits. This was indeed found: Search on repeated target

trials was especially fast when the display re-emerged from its last-known position.

Thus, the display object’s spatiotemporal history affected the way in which locations

within the object were selected. The study of Schreij and Olivers (2009) shows that

relevant target location information is stored with the spatiotemporal representation of

an object. One of the goals of the current study was to investigate if information less

relevant to the task is also stored within a representation, such as the presence of an

irrelevant salient object. To this end, we replicate Schreij and Olivers (2009) in

Experiment 1 but in one condition added a color-defined singleton distractor to the

search array.

Second, we ask if besides the target location, relevant target feature information

is also stored with an object’s spatiotemporal representation. In Experiment 2, the target

shape, the target color, or both could repeat from trial to trial, but only target shape was

relevant. The target location was never repeated. As with spatial biases, the question

was whether the bias for target features would depend on the display object being

spatiotemporally the same or different.

Third, we investigated if the attentional control settings which are maintained for

target locations are affected by a change in the physical appearance of the display object,

especially when the spatiotemporal continuity of the object defines it as one and the

same. Instead of having two simple square displays as objects, in Experiment 3, we

presented the search arrays in the display area of either a cell phone or a digital music


64

player. The type of device could change from trial to trial, independent of the

spatiotemporal trajectory.

Experiment 1

This experiment sought to replicate Schreij and Olivers (2009) in showing an object-

based bias towards the target location. Figure 7 shows an example display. As in Schreij

and Olivers (2009), participants searched for a diamond shape and responded to the

letter N or M inside it. From trial to trial, the target location could be repeated, or it

could change. In addition, the search display appeared from behind either one of two

walls positioned at the left or right side of the screen. Schreij and Olivers (2009) actually

used walls at all four sides of the screen in order to dissociate movement direction and

object history. Since this made no difference, and to simplify the experimental design,

we used only two walls in this and subsequent experiments. As in our previous study,

we predicted a same object benefit for target location repetitions. Response times

should be speeded when the target location repeats, but especially so when it appears to

150 ms

150 ms

Figure 7: Example of stimulus display for a typical distractor present trial in Experiment 1. For printing purposes, these images were converted to black and white, but the walls were brick-colored and the search elements were green or red. A typical trial started with a screen with both search search displays hidden behind the walls for 1000 ms. Then, over a time course of 150 ms, one of the search displays slid to the center of the screen, and with this exposed the search array. Participants were to report the identity of the letter in the diamond shape. When the participant had given a response, the search display shifted back behind the wall it departed from (within another 150 ms).

Until response

CHAPTER 4

65

be the same display object, as when it re-emerges from the side on which it disappeared

on the previous trial.

The novel addition was that on certain trials one of the circles would carry a

salient deviating color, and thus form a singleton distractor. Theeuwes (1992) has

shown that such a color distractor interferes with search, resulting in increased RTs.

Here we assessed if this distractor interference effect is also modulated by the

spatiotemporal history of the search display object. Just like biases towards the target

location are bound to the display object, biases away from the distractor may also be

bound to it. If so, distractor interference should be reduced for search array repetitions

when the same spatiotemporal object is reencountered. If on the other hand only

(relevant) target information is saved, and (irrelevant) distractor information is not, the

effect of a distractor should be unaffected by the spatiotemporal continuity of the object

on which it is presented.

METHOD

Participants

Twelve students from the VU University Amsterdam participated and received course

credit or money in return. All of them were between 19 and 29 years of age (average

21), reported normal or corrected-to-normal vision and no color blindness.

Apparatus




768 pixels. The “M” and “N” keys on a normal keyboard were used to register the

responses of the participants. Stimulus presentation and response recording were done

in E-prime 1.2 (Psychological Software Tools, 2003). The experiment was executed in a

dimly lit and soundproof room, in which participants were seated at a distance of

approximately 75 cm from the screen.

Stimuli

Images of a wall (7.36o visual angle wide) were positioned on the left and the right side

of the display, stretching from the top to the bottom of the screen. Behind these walls

there was an evenly colored grey background (CIE(.289,.316), 4.9 Cd/m2). Two square


66

areas containing the search arrays were placed behind the walls on either side. The

contents of these search displays would be occluded by the walls and thus not visible to

the participant, until one of them would slide to the middle of the screen. The search

displays had a black background and a white border, CIE(.282,.310), 39.0 Cd/m2, with

0.07o width. The size of the search display was 512x384 pixels. To generate an

impression of depth in the display and to enhance the perception of the search display

as a real object, a thin shadow was drawn behind it at the right and bottom sides,

CIE(.0272,.330), 3.2 Cd/m2. The search elements were positioned on an imaginary circle

with a radius of 14.24o visual angle. A white fixation cross was located at the center of

this circle. The individual search elements consisted of circles and diamonds, with a

visual angle of 3.07o and 3.68o respectively. The difference in visual angle between a

circle and a diamond shape was necessary, because this adjustment equalized the

surface sizes of these two shapes. The shapes were all colored green, CIE(.280,.623), 7.2

Cd/m2, except for the distractor, if present, which was colored red, CIE(.619,.355), 9.0

Cd/m2. The shapes contained either an “M” of “N” character, of a grey color identical to

that of the main background.


The main factors of interest were: 1) Spatiotemporal Object (the search array appeared

on the same object as the previous trial, or on a different object). 2) Target Location

(target and distractor positions were the same as, or different from, the previous trial).

3) Response (again same as, or different from, previous trial). 4) Distractor: An

irrelevant color singleton could be absent or present in the display (replacing one of the

standard distractors). Together, this resulted in a 2x2x2x2 design. So for example, on

trial n, the search display could come from the other side of the display than on trial n-1

(and therefore constitute a different object), but the target could be in the same location

as on trial n-1 and have the same response feature as on trial n-1 or any other

combination of these factors. Distractor: All factors were randomly mixed within blocks,

except distractor presence, which was blocked.

Participants were tested in a half hour session. Before the experiment started,

oral and written instructions were given to familiarize them with the task. They were

asked to look for the diamond target, while ignoring all other items, and to respond as

fast as possible while making as few errors and eye movements as possible. To keep

CHAPTER 4

67

them motivated, participants were asked to write down their average response time and

accuracy score after each block. They were first presented with one singleton distractor

absent and one singleton distractor present practice block (with the order

counterbalanced across participants), each containing 80 trials. After completion of the

practice blocks participants were requested to call the experimenter to check their

scores. Practice was repeated until scores were reasonable (no less than 85% correct

and average RT < 1000 ms). The main experiment consisted of 10 blocks of 80 trials

each, with distractor present and distractor absent blocks alternating in

counterbalanced order (across participants). In each block there were an equal number

of combinations of same and different conditions for each of the remaining factors. After

each block the participant received RT and accuracy scores, followed by a short break.

At the beginning of a trial only the two walls were visible, each having a search display

hidden behind them of which only the left- or right-most edge was visible (for right- and

left-sided displays respectively). After 1000 ms, one of the search displays would take

150 ms to slide to the middle of the screen from behind a wall, revealing the search

display. Until it arrived at the center of the display, the search display only contained

green circles (with N or M inside each of them), as to not give away the display

arrangement during the motion. As soon as it came to a halt, one of the items then

changed into a diamond target, another into a red singleton distractor (in the distractor

present condition). It deserves mentioning that given the speed of the motion, and the

abruptness of the halt, these changes were not consciously noticeable if one was not

instructed about their occurrence beforehand. It still looked like a smoothly entering

display.

When the search display arrived at the middle of the screen, response time

measurements started and participants were to report whether the diamond shape

contained an “M” or an “N” character by pressing the corresponding key on the

keyboard. The display stayed on until response and then slid back behind the wall that it

came from (again within 150 ms). Correct and incorrect responses were followed by a

short high frequency tone and a slightly longer low frequency tone respectively.

Results

Figure 8 depicts the results of Experiment 1. The RT data were trimmed from 2.5 SD

from the mean (2.6% of trials) and erroneous responses were removed (another 4.8%).


68

The means of the remaining RTs were subjected to a 4-way repeated-measures ANOVA

with Spatiotemporal Object (same or different compared to previous trial), Target

Location (same or different), Response (same or different), and Distractor (absent,

present) as factors. When a new display object was presented, responses were overall

slower (717 ms) than when the old one appeared again (707 ms); Spatiotemporal

Figure 8: Results of Experiment 1. Mean response times and error rates for A) same and different search displays, as a function of object type (same or different as on previous trial). B) same and different search displays, as a function of response feature (same or different as on previous trial). C) same and different responses, as a function of object type (same ore different as previous trial). Panel D) shows the same object benefits underlying the interaction of panel A, i.e. the RT differences between ‘different object’ and ‘same object’ conditions, for the different feature changes in display configurations. The error bars show the standard error.

B) C)

D)

A)

CHAPTER 4

69

Object, F(1,11) = 11.07, p = .007. Participants were also significantly slower when the

target location differed from the previous trial, compared to same previous target

locations (761 vs. 662 ms); Target Location, F(1,11) = 31.92, p < .001. A change in

Response caused no significant difference. The main effect of Distractor was significant

F(1,11) = 5.57, p = .038. Responses took longer when there was a color distractor

present (721 ms) than when it was absent (702 ms).

As shown in Figure 8a, repeated display configurations led to improved

performance, but especially so when they appeared on the same object. This was

confirmed by a significant Spatiotemporal Object by Target Location interaction, F(1,11)

= 13.83, p = .003. Figure 8d depicts this same object benefit in terms of the difference in

RT between the same and different object conditions. Separate t-tests showed a reliable

same object benefit for repeated display configurations, t(11) = 4.43, p < .001, and no

such benefits for changing configurations.

The interaction between Target Location and Response was also significant,

F(1,11) = 28.762, p < .001 (Figure 8b). When both factors repeated, participants were

faster than when either one or none repeated. There also was a trend towards an

interaction between Distractor and Target Location, F(1,11) = 4.01, p = .070. The

presence of a distractor resulted in greater RT costs when the display configuration

changed, than when it repeated. There was no interaction between Spatiotemporal

Object and Response (F< 0.5, p > .5), nor between Spatiotemporal Object and Distractor,

or Spatiotemporal Object, Target Location, and Distractor (F<0.5, p >.5 and F<0.9, p > .3

respectively).

The only significant effect on the errors was an interaction between Target

Location and Response, F(1,11) = 23.09, p = .001. Participants made more errors when

either the response feature or the display configuration changed, than when both

remained the same or when both changed together.

Discussion

A clear same object benefit occurred for selecting target locations, confirming the results

of Schreij and Olivers (2009). Observers benefitted when the target location repeated

from one trial to the next, but especially so when the display object re-appeared from

the side it had just disappeared to. The presence of a color distractor slowed down

search overall, in line with previous findings in the literature (Theeuwes, 1992).


70

However, this cost did not interact with the spatiotemporal properties of the display

object. Such an interaction would be expected if selection settings pertaining to the

distractor were stored with the object representation. For example, if the distractor

becomes subject to location-based or feature-based inhibition, such inhibitory settings

may then be expected to carry over to the next search display when it appears on the

same object. Apparently the control settings for the target were bound to the

spatiotemporal object representation but the settings for the distractor were not.

Apparently, the object file stores what is relevant and not what is irrelevant to the task.

Experiment 2

Experiment 1 suggests that objects carry an attentional bias that affects selection when

the same object emerges again. This bias was spatial in nature, as the same object

benefit was measured through the repetition of the target location. The main goal of the

present experiment was to see if similar object benefits would also occur for the

repetition of target features instead of location. The second goal was to see if such

object-based biases are again limited to relevant features, or could also include

irrelevant features.

Participants searched for a unique shape, which could be a diamond among

circles, or vice versa. Furthermore, the color of the search elements could also change

between red and green. So on any trial, either or both the target shape and color could

be the same or different from the previous trial (and the same would go for the singleton

distractor). This allowed for feature-based priming effects to occur. Importantly, the

target and distractor locations always changed from trial to trial, so there were no

opportunities for location-based effects. If object representations can also carry feature-

based attentional settings, we would expect a same object benefit for repeated target

features. For example, if observers found a diamond-shaped target on trial n, they would

be biased towards a diamond-shaped target again on trial n + 1 if the search display is

the same object in terms of spatiotemporal history.

As the target is defined by its shape and not by its color, information about the

target color is not relevant to the task. If, as the results of Experiment 1 suggest, task-

irrelevant information is not stored with the object, then the effect of a color change on

search would not be modulated by the spatiotemporal continuity of the display object.

Furthermore, we again introduced an irrelevant, color-defined distractor. On the basis of

CHAPTER 4

71

previous experiments with feature changes between trials (Hickey, Olivers, Meeter, &

Theeuwes, 2011; Pinto, Olivers, & Theeuwes, 2005), we expected this distractor to

strongly interfere with search. However, since it was again irrelevant, it may not stick

with the spatiotemporal representation of the display object.

METHOD

Participants

Fifteen students from the VU University Amsterdam (aged 18-21 years) participated for

course credits or money. They reported normal or corrected-to-normal vision and no

color blindness.

Apparatus, Stimuli, Design, and Procedure

The method was the same as in Experiment 1, except for the following changes.

Participants were instructed to look for the unique shape, which could be a diamond

among circles, or the other way around. Items could also change color from trial to trial,

between red and green. If the target was red, the singleton distractor (if present) would

be green, and vice versa. The location of the target and distractor never remained the

same and changed on every trial. Thus, instead of Target Location, we manipulated a

new factor, Target Feature, with four levels: “no change”, “color change”, “shape change”,

and “both change”, as considered relative to the previous trial. This factor was presented

randomly mixed with the previous factors Spatiotemporal Object (same, different), and

Response (same, different) in 14 counterbalanced distractor present and distractor

absent blocks of 96 trials each, resulting in a 2x2x2x4 design.

Results

The RT data were trimmed, removing 2.6% of the total number of trials, and erroneous

responses were omitted, removing another 9.7%. The remaining RTs are depicted in

Figure 9 and were submitted to an ANOVA with Target Feature (no change, color change,

shape change, both change), Spatiotemporal Object (same, different), Distractor (absent,

present) and Response (same, different) as factors. Overall, participants were faster

when there was a switch of object (791 vs. 802 ms), Spatiotemporal Object, F(1,14) =

9.82, p = .007. They were slower when the target-defining feature changed (834 vs. 796

ms), Target Feature, F(3,42) = 42.43, p < .001. They were also slower in responding

when a distractor was present (853 ms, vs. 740 ms when absent), Distractor, F(1,14) =


72

Figure 9: Results of Experiment 2. Mean response times and error rates for A) same and different search displays, as a function of object type (same or different as on previous trial). B) same and different search displays, as a function of response feature (same or different as on previous trial). C) same and different responses, as a function of object type (same ore different as previous trial). Panel D) shows the same object benefits underlying the interaction of panel A, i.e. the RT differences between ‘different object’ and ‘same object’ conditions, for the different feature changes in display configurations. The error bars show the standard error, for each individual “same vs. different object” contrast.

C)

B)

D)

A)

CHAPTER 4

73

57.65, p < .001. The interaction of most importance here, between Spatiotemporal

Object and Target Feature, was significant, F(3,42) = 3.88, p = .021. This interaction is

shown in Figure 9a, and further clarified in Figure 9d, which shows the relative same

object benefits (i.e. the difference in RT between same object and different object trials).

Note that rather than there being a same object benefit with repeated feature

configurations, there was now a marked same object cost when the feature

configuration changed over trials. Planned comparisons confirmed that when the target

shape changed, or shape and color changed together, there were significant same object

costs, t(14) = 3.06, p < .05 and t(14) = 3.33, p < .05 respectively. There were no costs or

benefits in the condition in which the target changed color only, or did not change at all

(ts < 1.2, ps > .2).

There also was a significant interaction between Distractor and Target Feature,

F(3,42) = 7.03, p = .001. The distractor was more disruptive when the target shape, or

the target shape and the color changed. The interaction between Response and Target

Feature was also significant, F(3,42) = 15.95, p < .001. When the target changed shape,

or both shape and color, participants were faster when the response feature changed

too. When the target did not change, or changed only color, same responses were faster.

The presence of a distractor even enlarged this effect, resulting in a three-way

interaction, F(3,42) = 4.08, p = .019. There was no Response x Spatiotemporal Object (p

> .3 ), nor a Spatiotemporal Object x Distractor (p > .1) or a Spatiotemporal Object x

Target Feature x Distractor interaction (p > .4). As shown in Figure 9c, RTs remained

similar for each combination of Response and Spatiotemporal Object.

An ANOVA on the error rates with the same factors revealed that participants

made significantly more errors when a distractor was present than when it was absent,

F(1,14) = 57.65, p < .001. Participants also made more errors when the object changed

over trials, Spatiotemporal Object, F(1,14) = 8.50, p = .011, when the Target Feature

changed, F(3,42) = 19.51, p < .001, or when Response changed, F(1,14) = 10.57, p = .006.

The interaction between Response and Target Feature was significant, F(3,42) = 15.90, p

< .001. More erroneous responses were made when the display configuration changed

but the response feature was repeated. None of these findings jeopardizes the

conclusions based on the RT data.


74

Discussion

The results provide evidence for the idea that feature-based attentional control settings

can be stored in an object file. The change of search display features between trials had a

differential effect on RTs depending on the spatiotemporal history of the entire display

object. However, where Experiment 1 found a same object benefit for repeated

configurations, here the object-based effect was expressed as a same object cost when

the feature configuration changed from one trial to the next. Participants performed

worse when the spatiotemporal trajectory suggested that they were looking at the same

display as on the previous trial, but in fact the feature configuration had changed.

Apparently, the reappearance of an object (in spatiotemporal terms) creates the

expectation of a certain target definition (here shape). When this expectation is violated,

attentional settings need to be reconfigured, resulting in a selection delay. A possible

reason for finding same object costs with changing configurations rather than same

object benefits with same configurations is that although the features of the search

elements did not necessarily change over trials, the locations of the target and distractor

did (on every trial). Any location-based expectations (such as found in Experiment 1)

may thus have worked against the feature-based benefit.

When merely the color changed, there were no particular same object effects.

This finding once again supports that it is mainly a bias towards task-relevant features

which is stored with the object representation. Because the target was defined by its

shape and not by its color, information about the target’s color was irrelevant for the

task and henceforth apparently not kept with the representation. This conclusion is

further corroborated by the lack of any object-based modulations of the singleton

distractor effect. Even though the distractor by itself caused considerable slowing, this

did not depend on object history.

Finally, a change of response interacted with a change of target feature, indicating

that participants linked specific responses to specific features of the target. Such feature-

response bindings have been found before (Hommel, et al., 2001) and will be discussed

further in the General Discussion.

Experiment 3

Experiments 1 and 2 demonstrated that selection settings for relevant properties of the

search array, like target features and locations, are linked to an object representation.

CHAPTER 4

75

The current experiment investigates if a change in the physical appearance of this object

weakens or severs this link. Will attentional control settings for the target still be

retrieved for an object that is the same in terms of spatiotemporal continuity, but has

changed physical appearance during occlusion? For this purpose, we presented the

Figure 10: Illustration of a stimulus display in Experiment 3. The search arrays were now presented inside the screen area of a portable device, which was either a white Apple Ipod, or black Nokia N95.


76

search array inside the display area of two distinct mobile devices, as illustrated in

Figure 10. When one of these mobile devices moved to the center of the screen, it could

change its appearance when it was temporarily occluded by the wall. This manipulation

allows us to determine if attentional control settings are linked more strongly to

spatiotemporal continuity, continuity in terms of object identity, or both. Earlier work

by Mitroff and Alvarez (2007) has indicated that the persistence of an object

representation depends on the spatiotemporal continuity rather than on the physical

appearance of the object. We may therefore expect the same to happen for the


In order to keep the number of experimental manipulations within limits, we

chose to leave out the singleton distractor in this experiment, since its presence did not

interact with the spatiotemporal representation of an object in both previous

experiments.

METHOD

Participants

Eleven students from the VU University Amsterdam (aged 18-24 years, 3 male)

participated for course credits or money. They reported normal or corrected-to-normal

vision and no color blindness. One participant reported suffering from severe fatigue

during the experiment. As this was confirmed by her data (large standard errors and

mean RT beyond 3 SD from the mean of the remainder of the group), she was removed

from the dataset.

Apparatus

The apparatus remained unchanged from the previous experiments.

Stimuli

The search display was now presented as the display of a mobile device (see Figure 10),

which could either be a white Apple iPod or a black Nokia N95. To make these devices fit

on the screen, the location of the search display had to be slightly shifted upwards

compared to the central position used in Experiments 1 and 2. A further small change

was that whereas in the previous experiments the objects stuck out a little from the

inner side of the occluding wall, in the present experiment they stuck out from the outer

CHAPTER 4

77

side. This way, an object could change appearance while it moved behind the wall before

re-emerging on its path towards the middle of the screen.

Design, and Procedure

The experiment was similar to Experiment 1. The factor Singleton Distractor was

dropped. No singleton distractor was present in the display. Instead, Object Identity was

introduced as a factor, with the object identity either being the same or different as

compared to the previous trial. The factors of this experiment thus consisted of Object

Identity, Spatiotemporal Object, Response and Target Location, all with the levels same

and different as on the previous trial.

Results

Erroneous trials (6%) and trials deviating more than 2.5 SD from the mean (another

2.3%) were removed from the dataset. The results are shown in Figure 11 and Figure

12. An ANOVA was performed with Spatiotemporal Object (same, different), Object

Identity (same, different), Target Location (same, different) and Response (same,

different) as factors. The main effects of Target Location and Response were found to be

significant, F(1,9) = 67.47, p < .001 and F(1,9) = 10.20, p < .05 respectively. Participants

were faster when the target location or response feature repeated from trial to trial.

Importantly, the Target Location x Spatiotemporal Object interaction was significant

again, F(1,9) = 9.20, p < .05. Participants responded faster to a target location repetition

when the spatiotemporal object was repeated too. The Target Location x Response

interaction was also significant, F(1,9) = 8.88, p < .05. Participants responded faster

when both Target Location and Response were unaltered from the previous trial. There

was no interaction between Spatiotemporal Object and Object Identity, F(1,9) < 0.3, p >

.5, nor between Target Location and Object Identity, F(1,9) < 0.02, p > .88, nor between

Object Identity, Spatiotemporal Object, and Target Location, F(1,9) < 0.26, p > .62.

However, there was a significant three-way interaction between Spatiotemporal Object,

Object Identity and Response, F(1,9) = 5.57, p < .05 (see Figure 12). Response

repetitions led to faster RTs than a response change, but only if both object history and

object identity were consistent with the display being the same object. If either of these

factors indicated a different object, no such response repetition benefits were found. If

anything, RTs were then faster to response changes.


78

A) B)

C)

Figure 11: Results of Experiment 3 concerning the effects of Target Location on Response and Object. Mean response times and error rates for a repeated or changed target location that is A) presented on the same or a different spatiotemporal object and B) contains a same or different response feature. Panel C) displays the same object benefits for repeated or different target locations. Error bars depict the standard error.

CHAPTER 4

79

A)

C

Different object

B) Same object

Figure 12: Results of Experiment 3 concerning the effects of object appearance. Mean response times and error rates for a repeated or changed response that is presented on the same or a different object when A) the object retains the same physical appearance or B) the object changes appearance in between trials. Panel C) displays the same object benefits for repeated or different responses, depending on a repetition or change in object appearance. Error bars depict the standard error.


80

A similar analysis on the error rates only revealed main effects of Object Identity and

Response, F(1,9) = 5,32, p < .05 and F(1,9) = 7.47, p < .05 respectively. Participants made

more errors when the object appearance or the response was different from the

previous trial.

Discussion

The current results corroborate the findings of Experiment 1. There was once again a

clear same object benefit on target selection. The important new result is that this

benefit was not affected by a change in object appearance, suggesting that the object

representation that is used to store selection settings is predominantly determined by

spatiotemporal continuity rather than by identity. This is consistent with earlier work

showing that the persistence of an object’s perceptual representation is dependent on

the spatiotemporal continuity rather than the surface features of the object (cf. Mitroff &

Alvarez, 2007).

This is not to say that object identity had no effect at all. The three-way

interaction with the spatiotemporal object history and response shows that object

identity information is bound to response information. This is consistent with earlier

work showing episodic binding of object features and responses (Hommel, 1998; Keizer,

et al., 2008). We add that this response selection is not only modulated by object

identity, but also by the spatiotemporal history of the object, as we found earlier in

Experiment 1. In conclusion, although object appearance does not appear to guide our

spatial attention, it appears to affect the way in which we respond to it, consistent with

separate perceptual and response selection mechanisms.

General Discussion

To make sense of the outside world, the visual system carves it up into separate objects.

An important carrier of object representations appears to be spatiotemporal continuity.

This makes sense, since objects tend to be stable across space and time. This has been

confirmed by previous studies showing same object benefits (or different object costs)

when objects were defined in terms of spatiotemporal history (Egly, Driver, & Rafal,

1994; Flombaum & Scholl, 2006; Kahneman, et al., 1992; Mitroff, Scholl, & Noles, 2007;

Muller & Kleinschmidt, 2003; Scholl, 2001). Where these previous studies focused on the

link between the spatiotemporal history of an object and the responses that should be

made to that object, the current study explored the link between the spatiotemporal

CHAPTER 4

81

history of an object and the attentional selection of perceptual properties of that object.

To this end, objects consisted of entire visual search displays, with the target location or

target-defining feature being decoupled from the response feature. We report evidence

for the following:

1) Experiments 1 and 3 showed that seeing the same object (in terms of

spatiotemporal history) retrieves spatial selection settings for that object.

Repeating the target location in the visual search task was especially beneficial

when the search array was presented on the same display object that had just

disappeared behind a wall. This replicates Schreij and Olivers (2009), and

confirms the conclusion that target location settings are stored with an object.

2) Experiment 2 showed an important new finding: Seeing the same object retrieves

selection settings for target features, in this case shape. When the target was

presented on the same object but had a different shape than in the previous trial,

responses were slowed. This indicates that relevant information on feature

selection is stored with the object representation, as a mismatch of the observed

target feature and the one stored in the representation causes interference.

3) Both Experiment 1 and 2 showed that although target information is stored with

an object, distractor information is not. A salient singleton distractor was

introduced in the displays, and although it interfered overall with search, such

interference effects did not vary with the spatiotemporal history of the object.

This was the case regardless of whether same object benefits were spatial

(Experiment 1) or feature-based (Experiment 2) in nature, and regardless of

whether distractor interference was weaker (Experiment 1) or stronger

(Experiment 2). This suggests that relevant information is stored with an object,

but irrelevant information is not.

4) The same conclusion can be reached on the basis of the fact that, in Experiment 2,

only the target-defining feature (shape) was linked with the object history,

whereas an irrelevant feature (color) was not. This is unlikely due to color being

a weaker feature than shape: If anything, previous studies using the same visual

search displays have shown that color is a stronger selection property than shape

(Theeuwes, 1992). Additionally, in the present experiments a color-defined

singleton distractor was sufficiently powerful to interfere with search for a shape.


82

5) Finally, Experiment 3 showed that the preference for previous target locations is

tied to the spatiotemporal history of an object, but not to its identity. Location

repetition effects were not modulated by object identity, nor were the effects of

spatiotemporal history weakened by a discordant change in object identity. The

dissociation between object definitions based on spatiotemporal continuity and

object identity is consistent with a number of other studies (Kahneman, et al.,

1992; Mitroff & Alvarez, 2007; Mitroff, et al., 2007; Scholl, 2001) which show that

it is mainly spatiotemporal consistency that determines what is and what is not

the same object, and not its visual appearance.

In all, the results show that both location-based and feature-based selection settings are

stored with an object, that the most important definition of an object here is one in

terms of spatiotemporal continuity rather than identity, and that what is stored is

relevant target information instead of information about irrelevant features or

distractors.

Effects on response selection

The main result in Experiment 1 and 3 was that spatiotemporal history affected spatial

selection within the object, as measured by target location repetition. In turn, the target

location repetition interacted with response, such that a repeated target location further

facilitated a repeated response. Response selection per se did not interact with

spatiotemporal history, although in Experiment 3 response selection depended on

overall object appearance, both in terms of identity and spatiotemporal history. In all,

this suggests a cascade of processes first retrieving target location information on the

basis of object history, followed by response selection on the basis of the target location.

Such interactions with response selection fit well within the theory of event

coding (Hommel, 1998; Hommel, et al., 2001). This theory states that task-relevant

stimulus and response features are integrated into an episodic structure called an event

file (comparable to Logan’s instance theory (Logan, 1988) . These event files are nicely

illustrated by Experiment 4 of Keizer, Colzato and Hommel (2008). They presented

participants with two sequential images of faces or houses (S1 and S2), which moved in

a certain diagonal direction. Regardless of its content, S1 had to be responded to with a

pre-defined left or right response (as indicated by an arrow prior to the image).

CHAPTER 4

83

However, S2 had to be responded to on the basis of its motion direction, again with a left

or right key press. On each trial, S2 could be the same as or different from S1 in terms of

content (house or face) and motion direction (and thus also the required response) It

was found that response times were longer when one feature was repeated while the

other was alternated, compared to complete repetition or alternation of both features.

Keizer et al. reasoned that we integrate the given response with the observed

combination of features into an event file. When both movement direction and

face/house features were then repeated, the previous response could quickly be

retrieved and executed from the event file. However, when one feature was repeated

and the other was alternated, the stimulus was partly In conflict with its event file,

resulting in response penalties. In the last case, in which both features were alternated,

there was neither a match nor conflict with an event file and thus no effect on responses.

In the present study too, the spatiotemporal properties as well as identity of the display

object may be integrated with the given response, thus facilitating the same response on

the next trial, when the same combination appears again.

The Keizer et al. (2008) study also provides an alternative explanation for our

object-based effects. So far we have suggested that selection settings are bound to

objects, as defined by their spatiotemporal continuity. Alternatively, these settings may

be tied to motion direction per se (regardless of it being the same object or not). Note

that in the present set up, the re-appearance of a previous object meant that it came

from the same side as on the previous trial, and thus had the same motion direction.

However, using very similar displays as in the current study, Schreij and Olivers (2009)

have dissociated movement direction from spatiotemporal object continuity by enabling

an object to move to and from four different sides of the screen. Therefore, an object did

not need to move back to where it had just come from and could thus re-emerge from a

different direction on the next trial. Schreij and Olivers found a similar same object

benefit regardless of whether the direction of movement was the same, suggesting that

it is not motion direction, but object representation that drives the effect. A further

argument against binding at the level of motion direction is that Keizer et al. found a link

between object identity and motion direction, whereas in Experiment 3 we failed to find

such a link, suggesting a potential dissociation between motion binding and object

binding.


84

In conclusion, task-relevant selection settings, like for target locations and

features are maintained in the spatiotemporal representation that we create for an

object. Information that is not directly relevant for the task, like the presence of a

distractor, or a task-irrelevant target feature, is most likely not stored in this

representation. Although an object’s physical appearance does not affect spatial

selection of target information inside that object, it does influence response selection

given that the object is spatiotemporally continuous. This suggests that we possibly

store information inside an object representation at different levels, which each

influence different stages of attention and response selection the next time we

encounter and interact with the same object.

Chapter 5 Abrupt onsets capture attention

independent of top-down control settings

Schreij, D., Owens, C. & Theeuwes J. (2008) Abrupt onsets capture attention independent of top-down control settings

Perception & Psychophysics, 70 (2), 208-218

ATTENTIONAL CAPTURE BY ABRUPT ONSETS INDEPENDENT OF ACS

86

Abstract

Previous research using a spatial cueing paradigm in which a distractor cue preceded

the target has shown that new objects presented with abrupt onset only capture

attention when observers are set to look for them (Folk, et al., 1992). In the present

study we used the same spatial cueing paradigm and demonstrated that even when

observers have an attentional set for a color singleton or a specific color feature, an

irrelevant new object presented with abrupt onset interfered with search. We also show

that the identity of the abrupt onset distractor affects responses to the target, indicating

that at some point spatial attention was allocated to the abrupt onset. We conclude that

abrupt onsets or new objects over-ride top-down set for color. Abrupt onsets or new

objects appear to capture attention independently of top-down control settings.

CHAPTER 5

87

Introduction

One of the most fundamental questions is whether we are able to control what we select

from our environment. Overt or covert selection may either be controlled by the

properties of the stimulus field, or by intentions, goals and beliefs of the observer (see

recent reviews, e.g. Burnham, 2007; Rauschenberger, 2003a; Ruz & Lupianez, 2002;

Theeuwes & Godijn, 2001). When we intentionally select only those objects and events

needed for our current tasks, selection is said to occur in a voluntary, goal-directed

manner. When, irrespective of our goals and beliefs, specific properties present in the

visual field determine what we select, this selection is said to occur in an involuntary,

stimulus-driven manner. These two mechanisms of selection have been referred to as

bottom-up and top-down attentional control (Eriksen & Hoffman, 1972; Hoffman, 1979;

Posner, 1980; Theeuwes, 1991a; Yantis & Jonides, 1984). When objects or events receive

priority of processing, independent of the observer's goals and beliefs, one refers to this

as attentional capture when such events or objects only capture our attention (e.g.

Yantis, 1996). When such events trigger an exogenous saccade to the location of the

object or event, one refers to this as oculomotor capture (Theeuwes, et al., 1998).

Even though the controversy whether salient, static singletons capture attention

in a purely bottom-up way continues (for recent discussions see Leber & Egeth, 2006;

Theeuwes, 2004; Theeuwes & van der Burg, 2008), there appears to be less controversy

about attentional capture by suddenly appearing new objects or abrupt onsets. The

finding that abrupt onsets might capture our attention dates back to the early research

of Eriksen and Hoffman (1972) and Jonides (1981), which showed that participants’

attention was automatically drawn to an exogenous cue. Subsequent research by Todd

and Van Gelder (1979) showed that onset stimuli were detected faster than their no-

onset counterparts in tasks requiring rapid eye movement responses. As the task

demands were made more complex, Todd and van Gelder (1979) observed that the

advantage for onset stimuli increased with the complexity of decisions that had to be

made by participants. Yantis and Jonides (1984) demonstrated that peripheral cues

captured attention because of their abrupt onset. In their experiments, participants had

to search for a specific target letter embedded in an array of two or four non-target

letters. While participants searched for the target letter, a new letter suddenly appeared

in an empty location.


88

Following these demonstrations of the special status of onsets on attentional

capture, Theeuwes and colleagues (Theeuwes, et al., 1998; Theeuwes, Kramer, Hahn,

Irwin, & Zelinsky, 1999) showed that abrupt onsets also have the ability to capture the

eyes. In this so called oculomotor capture paradigm, participants were instructed to

make a saccadic eye movement towards the only gray element in the display. On some

trials, an irrelevant new object presented with abrupt onset was added to the display.

Participants knew the onset was irrelevant and also knew that they had to ignore it. The

condition in which a to-be-ignored onset was presented somewhere in the visual field

was compared to a control condition in which no sudden-onsets were added to the

display. The results showed that when no new object was added to the display,

observers made saccades that generally went directly to the uniquely colored circle.

However, in those trials in which a new object was added to the display, in about 30 to

40% of the trials the eye went in the direction of the abrupt onset. Moreover, in a

subsequent eye movement study Theeuwes and colleagues (Theeuwes, De Vries, &

Godjin, 2003) showed that under the very same circumstances irrelevant salient static

singletons (such as a uniquely color element) only captured attention but not the eyes.

Therefore transient singletons seem to have a different effect than static singleton

confirming the special role of abrupt onsets.

All these studies demonstrate the special status of abrupt onsets in capturing

attention. The reason for this special status in capturing attention may be because

onsets are accompanied by luminance transient (e.g. Jonides & Yantis, 1988; Theeuwes,

1990, 1994b, 1995a; Yantis & Jonides, 1984) or because they represent a new object

(Abrams, Davoli, & Suszko, 2007; Yantis & Hillstrom, 1994). Regardless of the

underlying mechanism, it is generally agreed that onsets have the ability to capture

attention in an exogenous way.

Whether attentional capture by onsets is truly exogenous has been challenged by

the Involuntary Contingent Orienting Hypothesis of Folk, Remington and Johnston (1992).

According to this hypothesis whether or not an object captures attention is completely

dependent on attentional control settings. Participants are able to compose a certain

attentional set, which contains the dimensions or features of the target the participant

has to look for in a task (also called task set). Only elements in the visual field that

possess the properties that match the information in the attentional set, will capture

attention. This holds for static stimuli, as well as dynamic events like onsets or motion.

CHAPTER 5

89

To provide evidence for this hypothesis, Folk et al. (1992) conducted an experiment in

which participants were induced to adopt an attention set for a certain stimulus

property, like an onset or a color. In their paradigm, the presentation of a search display,

which contained a stimulus dimension participants had to look for, was preceded by a

cue which gave an incorrect or correct (henceforth called valid or invalid) indication of

the location where the target would appear. This cue could be the same or a different

dimension as the target element. For example, a color search display could either be

preceded by an onset cue or by a color cue. The critical finding here was that only when

the cue was of the same dimension as the target element, a considerable validity effect of

the cue was found. When the cue was from a different dimension as the target, it did not

affect the response times to the target, regardless of its validity.

The contingent capture hypothesis of Folk et al. (1992) is consistent with notions

put forward by Bacon and Egeth (1994) regarding top-down set for specific search

modes (i.e., feature search vs. singleton detection mode) and with notions suggested by

Yantis and Egeth (1999) regarding an top-down attentional set for singletons. In this

respect, the contingent capture hypothesis of Folk et al. (1992) may account for findings

of attentional capture by static singletons (Hickey, McDonald, & Theeuwes, 2006;

Theeuwes, 1991b, 1992; Theeuwes, et al., 2000). However, the predictions of the

involuntary contingent orienting hypothesis regarding abrupt onsets seem to be

inconsistent with earlier findings which have shown that abrupt onsets are unique in the

ability to capture attention without an attentional set (Jonides & Yantis, 1988; Yantis &

Egeth, 1999).

The discussion whether it is transient luminance or the appearance of a new

object that causes abrupt onsets to capture attention (e.g. Yantis & Hillstrom, 1994) led

to discussions regarding the original Folk et al. (1992) studies. The onset in Folk et al.’s

experiments consisted of the appearance of a character inside a boundary box, instead of

the presentation of an object a previously empty location. This could be a violation of the

requirement that the onset has to be a new perceptual object to capture attention.

Instead of being regarded as the appearance of a new perceptual object, these onsets

could just be perceived as a property change of a previous present object (the bounding

box), which by itself does not always capture attention (Jonides & Yantis, 1988). To

address this issue, Folk and Remington (1999) conducted a series of new experiments

using new perceptual objects in combination with their usual pre-cueing paradigm.


90

Consistent with earlier findings, they found that onsets presented in empty locations

(i.e., so called new objects) only captured attention when participants were set for

onsets but not for color. In line with their hypothesis, capture was fully contingent on

the attentional control settings.

However, there is one important difference between the experimental paradigms

favoring capture by abrupt onsets and salient singletons (Theeuwes, 1992, 1994b;

Yantis & Jonides, 1984) and the pre-cueing paradigm of Folk and colleagues supporting

the contingent orienting hypothesis. Experiments using the first paradigm, presented

the target and distracting element simultaneously exactly at the moment participants

needed to start searching. However, in the classic pre-cueing paradigm of Folk et al.

(1992) the distracting element (the cue) preceded the search display by 150 ms. In other

words; participants had to ignore a “cue” that preceded the search display. As argued by

Theeuwes et al. (2000) it is possible that the delay between cue and search display was

long enough to overcome attentional capture by the irrelevant cue (see also Theeuwes,

1994b). In other words, disengagement of attention from the cue may have been

relatively fast when the cue and target did not share the same defining properties (e.g.,

the cue was red and the target was an onset), while disengagement from the cue may

have been relatively slow in cases where the cue and target share the same defining

properties (e.g., both were red). Such a mechanism could explain why there are RT costs

when the cue and target have the same defining characteristics and no costs when cue

and target are different. In this view, the contingent capture hypothesis can explain why

it may be easier to disengage attention from a particular location when an element

presented at that location is not in line with the top-down control settings. However, this

does not imply that there is no capture of attention by the irrelevant cue singleton; it

simply indicates that after a certain time participants are able to exert top-down control

over the erroneous capture of attention by the irrelevant singleton.

In line with this explanation, Theeuwes and colleagues (2000) provided strong

evidence for the claim that once attention is captured by an irrelevant singleton it only

takes a very brief time to disengage attention from that location. Theeuwes et al. (2000)

used a visual search task similar to that of Theeuwes (1992) in which participants

searched for a shape singleton (a single gray diamond among 8 gray circles). Prior to the

presentation of the target display a color singleton was presented at different SOAs (50,

100, 150, 200, 250 and 300 ms). Theeuwes et al. showed that for conditions in which

CHAPTER 5

91

target and distractor were presented in close temporal proximity (< 100 ms), the

distractor interfered with search, suggesting that there was not enough time to

overcome attentional capture. However, when the singleton distractor was presented a

considerable time (SOAs 150 to 300 ms) before the presentation of the singleton target,

the distractor no longer interfered with search suggesting that participants were able to

overcome capture by the irrelevant singleton

The current research was intended to further explore the ability of abrupt onsets

to capture attention, while using the classic pre-cueing paradigm of Folk et al. (Folk &

Remington, 1999; Folk, et al., 1992; Folk, Remington, & Wright, 1994). A search display

was preceded by a cue display of the same dimension as the target. Participants were set

for color, since they had to search for a color singleton throughout the whole

experiment. In some trials an abrupt onset (i.e., a new perceptual object) was presented

at a random and empty location. However, unlike Folk and Remington (1999) we

presented the abrupt onset not during the cue display but simultaneously with the

search display, as is typically done in traditional visual search experiments investigating

the role irrelevant distractors (e.g. S. E. Christ & Abrams, 2006; Theeuwes, 1994b,

1995a; Yantis & Johnson, 1990; Yantis & Jonides, 1990). As noted, by presenting the

target and the onset distractor simultaneously, the data will reveal any potential capture

effect of the onset distractor because unlike in the spatial cueing paradigms of Folk and

Remington (1998, 1999) there is no time to recover from capture (see Theeuwes, et al.,

2000).

Experiment 1

The current experiment used the Folk et al. (1992) pre-cuing paradigm. We created two

experimental conditions. One condition was regarded as the “no-onset” condition and

was the same as the color cue, color target condition of Folk et al. (1992). The

participant’s goal was to find a red character among white characters which appeared

inside placeholder boxes at four possible locations in the visual field. Before the search

display appeared, a pre-cue that had the same color as the target was presented at any of

the four potential target locations. Since the cue was a color singleton and participants

were set for color, it was expected that the cue would capture attention and result in a

significant difference in response times depending on the validity of the cue, just as in

Folk et al. (1992).


92

In the other condition, the “onset” condition, a boundary box containing a white

character appeared at a random empty location between two of the already present

boundary boxes. This extra character could be regarded as an abrupt onset of a new

perceptual object. The Contingent Involuntary Orienting Hypothesis of Folk et al. (Folk &

Remington, 1999; Folk, et al., 1992; Folk, et al., 1994) would predict that when

participants are set to search for color, the sudden appearance of an abrupt onset should

have no effect on performance.

To ensure that difference in response times could be attributed to attentional

capture and not by “attentional misguidance”, it was made sure that the appearance of

the new object would meet the criteria set by Yantis (1993) for stimulus-driven

attentional capture. This means that the distracting element should not share a defining

or reporting property (Duncan, 1985) with the target character. In this case, the defining

property was the red color of the target character, which the onset did not share since it

was white. The reporting property in this task was character identity, so it was made

sure that the identity of the onset distractor never had the identity of a target character.

Since in the current task the onset character would always be an ‘O’ and the target

character would either be an ‘X’ or an ‘=’, one can argue that this demand was met as

Cue display Fixation display Fixation display

Search display

1000-1400 ms 50ms 100 ms

Until response (or 2000ms)

No Onset

Onset

Figure 13: The sequence of events for a typical trial. First a fixation display was shown for 500ms, after which the central fixation cross was turned off for 50 ms. Then the fixation display was shown again for a random period of 1000, 1100, 1200, 1300 or 1400 ms. The cue display was presented for 50 ms. After an ISI of 100ms, the search display was presented for 2000 ms or until the participant responds. This is an example of an invalid trial, since the location of the red dots in the cue display and the location of the red character in the search display differ.

CHAPTER 5

93

well, since the distractor identity was not among the target identities the participants

were to respond to.

METHOD

Participants

Fourteen first-year students from the University of Sydney, School of Psychology

participated in the study, in exchange for course credit. The participants ranged in age

from 18 to 25 and all reported normal or corrected-to-normal visual acuity and color

vision.

Apparatus

The stimuli were presented on a 15” TFT screen with a Dell OptiPlex GX520, containing

an Intel Pentium IV 3 GHz and 512 MB of internal memory. The experiment was created

and run with E-prime 1.1 (SP3). The slides consisted of BMP images and had a resolution

of 640x480 pixels.

Stimuli

There were three basic types of displays: a fixation display, a cue display and a search

display, all of which had a black background. The fixation display consisted of a light

white fixation cross at the center of the screen, surrounded by four light gray,

RGB(167,169,172), placeholder boxes measuring a width of 2.6o visual angle, using an

approximate distance to the screen of 40 cm. The four boxes were positioned above,

below, to the left and to the right of the fixation cross, along a virtual circle with a

diameter of 20o visual angle, with the fixation cross as the center.

The cue display consisted of the same elements as the fixation display, with the

addition of four dots, with a diameter of 1.4o visual angle, positioned along the outside of

the center of each rib of all the placeholder boxes. One set of these dots surrounding one

of the placeholder boxes had a red color, (RGB (236,43,39); luminance 62.2 cd/m2) and

indicated the cued location. All the dots surrounding the other boxes had a bright white

color, RGB (255,255,255). In the search display an “X” (Myriad Roman, 21pt) or “=”

(Myriad Roman bold, 22pt) were placed in each of the boxes. There were always two ‘X’s

and two ‘=’ present.


94

Three of the characters inside the boxes were bright white and one was red,

which designated the target character. The search display could contain all possible

combinations of characters in the four boxes of which one character always was red.

In the onset condition one extra character “O” with a bright white color and

placed inside a light grey bounding box, would appear in the search display, located

between two other boxes on the virtual circle on which all other boxes were placed.

Examples of these display types, along with their order of appearance are presented in

Figure 13.

Design

There were two within-subject conditions. In the onset condition an additional object

(an abrupt onset) was added to the display. In the no-onset condition, everything was

the same except that no new object was added to the display. In both conditions, the cue

display could give a correct or incorrect indication of the location where the target

character might appear, but was correct at chance level. In 25% of the trials the red dots

surrounded the box where the target character would appear, which was considered a

valid cue, and in the other 75% of the trials it was invalid and the red dots surrounded a

box other that the target.

In the onset condition an extra distractor character was presented

simultaneously with the search display. This character appeared inside a bounding box,

identical to the other four boxes present on the display, in a previously empty location.

The extra onset character could appear between any of two other already present

placeholder boxes and appeared equally often in each of the four possible locations,

throughout the experiment.

The onset and no-onset condition were presented in 6 mixed blocks of 80 trials

each. 50% of the trials had no-onset search displays and the other 50% consisted of

onset search displays. These two types of search displays were randomly mixed within a

block.

Procedure

Participants were tested in a one hour session. Before the experiment started, oral

instructions were given to familiarize them with the task to be performed. It was

stressed that they keep using both hands for pressing the two different buttons on the

keyboard and to not move their eyes away from fixation during a trial, because this

CHAPTER 5

95

could impair their performance. The experiment commenced with the presentation of

general instruction slides that explained the main course of the experiment.

Participants were told that the abrupt onset was irrelevant to the task and would

never contain a target character. Finally, the participants were stressed to react as fast

as possible without making too many mistakes. After these general instruction slides,

the participant began with a block of 40 practice trials. They were prompted to press the

space bar when they were ready to begin with the real trials, after which they were

presented with 6 blocks of 80 trials. At the end of each block, participants were advised

to take a rest and were forced to wait for 30 seconds, before they could press a key to

begin with the next block of trials.

Trials began with the presentation of the fixation display for 500 ms. Then, the

fixation cross blinked off and on for 50 ms, to notify the participant of the start of a trial.

The fixation display remained on screen for a period randomly chosen from a set of

1,000, 1,100, 1,200, 1,300 or 1,400 ms, to eliminate any effects of expectancy. After this

fore period, a cue display was presented for 50 ms, after which the fixation display was

shown again for 100 ms. This served as an inter-stimulus interval (ISI) after which the

search display was presented until the participant responded or, when no response was

detected, for 2,000 ms. When no response was detected the trial was counted as an

error. Throughout a trial, the four place holder boxes were constantly visible.

After a response was given, a distinctive sound was played for a correct or

incorrect response. If the response was incorrect, the experiment paused for 10 seconds,

showing a counter counting from 10 to 0 seconds, to let the participants regain their

focus. If a response was not made before 2000 ms, it was registered as an error and the

participant had to wait 10 seconds before the trial procedure continued. Following the

response of a participant, there was an intertrial interval of 500ms, before the fixation

cross blinked again to indicate the start of the next trial.

Results

All response times (RTs) above 1000 ms (which is approximately 4 SD from the mean)

were regarded as errors and removed from the data set, as were incorrect responses.

This led to a loss of only 5.2% of the trials. Figure 14 shows the participants’ mean RT

and error percentages in the SOA and cue validity conditions. The individual mean RTs


96

were submitted to a repeated measures analysis of variance (ANOVA) with onset

presence (onset or no onset) and cue validity (valid or invalid) as factors.

There was a significant main effect of the presence of the sudden-onset, F(1,13) =

7.915, p<.05, such that participants were slower in their response to the target when an

onset was present. In addition, cue validity was highly significant F(1,13) = 276.852, p <

.001, replicating the traditional Folk et al (1992) effect demonstrating that a cue that

shares the feature properties of the target captures spatial attention. It is important to

note that there was no significant interaction between the validity of the cue and the

presence of an onset F(1,13) = 1.329, p = .270.Error rates for each condition were well

below 10%. Participants made significantly more errors in the invalid than in the valid

cue condition, F(1,13) = 15.443, p=.002, indicating that an invalid cue not only made

participants respond slower, but also less accurate. There were no differences in error

rates between the onset and no onset conditions, F(1,13) =.240.

Figure 14: Experiment 1: Mean Response time for validly and invalidly cued positions with and without the presence of an abrupt onset. Error bars represent the standard error of the mean difference scores between onset vs. no-onset for each validity condition.

CHAPTER 5

97

Discussion

The present results replicate the one of main findings of Folk et al. (1992): when

participants have an attentional set for a color, a “to-be-ignored” cue that has the same

color as the target captures attention. Even though the cue was not informative about

the location of the upcoming target singleton, participants were not able to ignore it.

This is a replication of the classic finding of Folk et al. (1992) and signifies the notion

that attentional capture is (or at least can be) contingent on top-down settings which are

established ‘off-line’ on the basis of current attentional goals. According to the

‘contingent capture’ model, only stimuli that match the top-down control settings will

capture attention; stimuli that do not match the top-down settings should be ignored.

Even though it is clear that participants were set for a color singleton, the

presence of an abrupt onset slowed responding. Indeed, regardless of whether the color

cue was valid or invalid, in the onset present condition RT was slowed by about 10 ms.

One way to explain this slowing is that attention was captured by the abrupt onset, an

interpretation that is consistent with findings from many previous studies and various

paradigms showing the ability of onsets in capturing spatial attention (see e.g.

Belopolsky, et al., 2005; S.E. Christ & Abrams, 2008; Donk & van Zoest, 2008; Gellatly,

Cole, & Blurton, 1999; R. W. Remington, Johnston, & Yantis, 1992; Theeuwes, 1990,

1994b; Yantis & Jonides, 1984). If the distraction effect caused by the abrupt onset is

indeed due to attentional capture, then one has to conclude that this finding is

inconsistent with the contingent capture hypothesis of Folk et al. (1992) because, as we

show in this experiment participants were set for color and therefore onsets should not

capture attention.

Experiment 2

The first experiment showed that even when the classic Folk et al. (1992) spatial cueing

paradigm is used, there is an effect of the appearance of an onset distractor when

presented at an empty location in the search display. This finding is consistent with

other studies using different types of paradigms demonstrating the extent to which

abrupt onsets can capture attention (S.E. Christ & Abrams, 2008; R. W. Remington, et al.,

1992; Theeuwes, 1994b, 1995a).

Even though the present study confirms the notion that onsets capture attention

in a purely exogenous way, one could argue that in the present experiment participants


98

were set to look for onsets. Indeed, the onset was presented simultaneously with the

target elements (the “X” and “=”) inside the placeholder boxes, making it possible that

the abrupt onset captured attention because participants were set to look for it. For

example, Gibson and Kelsey (1998) argued that the onset of a new object (an abrupt

onset) may capture attention because observers are prepared for the abrupt onset of the

entire display (see also Burnham, 2007). Participants may adopt such a set for display-

wide features, because the abrupt onset of the search display typically signals the

presence of the target in a very general sense. In other words, it is feasible that in

addition to an attentional set for color, participants also adapted a default set for abrupt

onsets because the abrupt onset of the elements inside the placeholder boxes signalled

the presence of the target.

In order to address this concern, in Experiment 2 the pre-masking elements were

placed inside the placeholder boxes. They consisted of an overlapping ‘X’ and ‘=’ and ‘|’

to hide the identities of the characters to appear. When the identities of the elements to

search needed to be revealed, the irrelevant line segments were removed in analogy to

figure-eight pre-masking characters as used in Yantis & Jonides (1984).

METHOD

Participants

Thirteen first year students from the University of Sydney participated in this

experiment in exchange for course credit. The participants ranged in age from 18 to 24

and all reported normal or corrected-to-normal visual acuity and color vision. None of

the participants had participated in the previous experiment of this study.

Experiment 1 Experiment 2

Figure 15: Examples of the fixation displays used in Experiment 1 and Experiment 2

CHAPTER 5

99

Apparatus and Stimuli

The apparatus and stimuli were similar to Experiment 1, with the exception of white

pre-masking characters (62.2 cd/m2), which are placed inside the boundary boxes.

Figure 15 provides an example. When the search display was presented, the extra line

segments hiding the characters on the search display were removed, making the

characters to search visible.


The design and procedure was identical to those of experiment 1. Instead of appearing

at the empty location inside a placeholder box, the target character was now revealed by

changing the color of one of the pre-masking characters and, at the same time, removing

the line segments that hide it.

Results

Erroneous responses were removed, as were responses above 1000 ms which led to a

loss of 5.2 % of the trials. Figure 16 shows the participants’ mean RT and error

percentages in the SOA and cue validity conditions. As in Experiment 1, there was a

main effect of onset presence, F(1,12) = 28.410, p < .001, indicating that the presence of

an onset slowed search for the color singleton. Also, the main effect of cue was highly

significant, F(1,12) = 78.470, p < .001. Consistent with Experiment 1, the interaction

between cue validity and onset presence was not reliable F(1,12) = 0.170, p = .687.

Error rates were well below 10%. Again, participants made significantly more

errors in the invalid relative to the valid cue condition, F(1,12) = 21.429, p=.001. There

were no differences in error rates for the onset and no-onset condition, F(1,12) =.302.

Discussion

The current results are basically identical to those of Experiment 1. The presence of an

onset distractor resulted in longer response latencies relative to a condition in which

there was no onset present. The results indicate that whether or not the search elements

placed inside the placeholder boxes were presented with onsets (as in Experiment 1) or

with offsets (as in Experiment 2) had no effect on the impact of the abrupt onsets. It

appears that in the current experiments, in addition to an attentional set for color,

participants did not adopt a general default set for onsets as is advocated by the display-

wide visual feature notion of Gibson and Kelsey (1998).


100

Experiment 3

Experiment 1 and 2 clearly show that the presence of an abrupt onset slows responding

to target. Even though participants were set for color, the onset had an effect on their

performance. Even as previous studies (Belopolsky, et al., 2005; S.E. Christ & Abrams,

2008; Enns, et al., 2001; Gellatly, et al., 1999; Theeuwes, 1990, 1994b; Yantis & Jonides,

1984) suggested that onsets capture attention, one still could argue that the 15 to 25 ms

cost caused by the onsets has nothing to with attentional capture. Indeed, Folk and

Remington (1998) offered an alternative explanation for increases in response times in

conditions in which a distractor was present. They suggested that the increase in search

time caused by the irrelevant singleton is due to what they call "filtering costs" a notion

first introduced by Kahneman, Treisman and Burkell (1983). In the current experiments

the presence of the abrupt onset may have slowed the deployment of attention to the

target item by requiring an effortful and time-consuming filtering operation. According

to this line of reasoning, attention goes directly to the uniquely colored item; and simply

Figure 16: Experiment 2: Mean Response time for validly and invalidly cued positions with and without the presence of an abrupt onset. Error bars represent the standard error of the mean difference scores between onset vs. no-onset for each validity condition.

CHAPTER 5

101

because the onset is present, directing attention to the uniquely colored item takes more

time than when no onset is present. The filtering cost explanation is compatible with the

contingent capture hypothesis because spatial attention only goes to the item (the

uniquely color item) that matches the attentional set for color; it assumes that spatial

attention does not go the location of the abrupt onset.

To determine whether the performance costs due to the onset are the result of

erroneous attentional capture or filtering costs, we employed the so-called “identity

intrusion technique” first introduced by Theeuwes (1995b) and Theeuwes and Burger

(1998). Instead of presenting a neutral character “O” inside the abrupt onsets, in

Experiment 3, the element inside the abrupt onset was either compatible or

incompatible to the response to the target. The underlying notion is that if attention is

allocated to the location of the abrupt onset distractor, its identity will be processed (e.g.

Kramer & Jacobson, 1991). Given this assumption, if attention is captured by the abrupt

onset, then a compatibility effect should be found, with longer RTs when the element

inside the distractor is incompatible with the target than when it is compatible. If the

abrupt onset does not capture attention and spatial attention is never allocated to the

location of the onset, then one does not expect a compatibility effect whatsoever.

METHOD

Participants

Twenty-one first-year students from the University of Sydney, School of Psychology

participated in the study, in exchange for course credit. The participants ranged in age

from 18 to 25 and all reported normal or corrected-to-normal visual acuity and color

vision. None of the participants had participated in any of the previous experiments.


The apparatus and stimuli were identical to Experiment 2 with the exception of the

onsetting element. Instead of an “O” character inside the onset placeholder, an “X” or “=”

would appear with the same font and color properties as all the other characters.


The design and procedure were basically the same as in the previous experiments

except that the compatibility of the element inside the onset distractor was manipulated.

When an onset distractor was present, in half of the trials the item inside the onset


102

distractor was compatible with the response to the target; in the other half it was

incompatible. There were 6 blocks of 80 trials.

Results

Erroneous trials and trials with responses above 1000 ms were removed from the data,

which resulted in a total loss of 6.7% of the trials. Figure 17 presents the results. To

investigate whether the overall presence of a distractor had an effect, the individual

mean RTs were submitted to an analysis of variance, with distractor presence (onset vs.

no onset), cue validity (valid vs. invalid) as factors. The main effect of distractor

presence was significant, F(1,20) = 22.977, p < .001, indicating the presence of the onset

Figure 17: Experiment 3: Mean Response time for validly and invalidly cued positions with and without an abrupt onset. In the compatible condition the character inside the abrupt onset is compatible with the response to the target; in the incompatible condition it is incompatible with the response to the target. Error bars represent the standard error as recommended by Masson and Loftus (2003).

CHAPTER 5

103

slowed search. Again, the cue validity was significant, F(1,20) = 75.774, p < .001. As in

the previous experiments, there was no significant interaction between the cue

condition and presence of the onset distractor, F(2,40) = 0.321, p =.649,

Another ANOVA was performed on the individual mean RTs for the distractor

conditions, with compatibility (compatible vs. incompatible) and cue condition (valid vs.

invalid) as factors. The main effect of compatibility was significant, F(1,20) = 5.222, p <

0.05, indicating the identity of the element inside the onset distractor affected the speed

with which participants responded to the target. When the element inside the onset

distractor was compatible participant responded faster (729 ms) then when it was

incompatible (759 ms). The interaction between cue validity and compatibility failed to

reach significance, F(1,20) = 0.929, p = .347.

All error rates were well below 10%. Again error rates were higher in the invalid

condition than in the valid condition F(1,20) = 15.977, p<.001. The presence of the onset

had no significant effect on errors, F(1,20) = .186 nor did the compatibility of the onset

distractor with the target F(1,20) = 1.463.

Discussion

The current experiment shows a small but clear compatibility effect, suggesting that

attention was allocated to the location of the onset distractor. The effect size of

compatibility is comparable to that reported by Theeuwes (1995b). On the basis of this

finding, one has to conclude that even when participants are set to look for a color

singleton, irrelevant abrupt onsets can capture attention. Note that the effect of the

onset is not modulated by the validity of the cue suggesting that even when attention is

directed towards the location where the target item is going to appear, the onset may

pull attention away towards the location of the onset. The observed compatibility effect

indicates that the onset does not merely cause some type of non-spatial filtering costs

but shows that the onset truly pulls attention to its location.

Experiment 4

The results of Exp. 1-3 show that when participants have a clear attentional set for color,

an irrelevant abrupt onset captures attention. Even though this clearly suggests that

onsets capture attention independent of a top-down set for color, one still may rescue

the contingent capture hypothesis of Folk et al. (1992) by assuming that in our

Experiment 1-3, participants engaged in what has been called singleton detection mode


104

(Bacon & Egeth, 1994; see also Lamy & Egeth, 2003). The idea behind this is that

participants can choose to search in a particular search mode. When participants engage

the singleton detection mode, they choose to direct attention to the location having the

largest feature contrast. In this mode, the most salient singleton will capture attention

regardless of whether it is the target or not. If, however, participants engage what is

called a feature detection mode they choose to direct their attention to a particular

feature (e.g., the color red) instead of to any singleton. According to Bacon and Egeth

(1994) in this mode "goal directed selection of a specific known featural singleton identity

may override stimulus-driven capture by salient singletons" (p.493). Bacon and Egeth

(1994) suggested that when observers 'choose' a feature search mode, attentional

capture by irrelevant singletons is eliminated. The notion that choosing a search

strategy allows attentional control suggests that attentional capture is under top-down

control (but see Theeuwes, 2004 who criticized the circularity of these search concept).

If we apply this type of reasoning to the current experiments, it is possible that

participants searched in singleton detection mode, allowing the onset singleton to

capture attention. Because participants were always looking for a singleton (the only red

element among gray elements), it is possible that the other singleton (i.e., the onset)

captured attention. To test whether the onset captures attention even when participants

were engaged in a feature search mode, we changed the display such that participants

no longer could search for a singleton. Instead of a red target among gray non-target

elements, participants had to search for one particular color (e.g., red) among elements

which each had a different color (e.g., green, yellow and blue). This way, participants

were forced to use the feature search mode. The question was whether if even in this

set-up the onset would capture attention.

METHOD

Participants

Eight students from the Vrije University Amsterdam were paid for participation. They

ranged in age from 18 to 24 and all reported normal or corrected-to-normal visual

acuity and color vision.

CHAPTER 5

105


The apparatus and stimuli were similar to Experiment 2, with the exception that the

non-target characters were colored instead of white. The colors red, green, yellow and

blue (all matched for luminance at 29 cd/m2) were randomly assigned to each of the

four characters.


Participants were instructed to look for one particular color throughout the whole

experiment. Participants were balanced across the four different colors such that two

participants consistently searched for red, two for green, two for yellow and two for

Figure 18: Experiment 4: Mean Response time for validly and invalidly cued positions with and without the presence of an abrupt onset in a task in which participants search for a particular color feature. Error bars represent the standard error of the mean difference scores between onset vs. no-onset for each validity condition.


106

blue. The color of the cue in the cue display matched that of the color a particular

participant was looking for.

Results

Erroneous trials and trials with response above the 1000 ms were removed from the

data set, which resulted in a loss of 8% of the total trials. Figure 18 displays the

participants’ mean RT and error percentages in the onset presence and cue validity

conditions. There was a main effect of onset presence, F(1,7) = 6.575, p = .037, indicating

that the presence of an onset slowed search for the color singleton. Also, the main effect

of cue was significant, F(1,7) = 11.731, p = .011. The interaction between cue validity

and onset presence was not reliable, F(1,7) = 2.121, p = .189.

Error rates were well below 10%. Participants made significantly more errors in

the invalid than in the valid cue condition, F(1,7) = 7.881, p=.026. There were no

differences in error rates for the onset and no-onset condition, F(1,7) =.127, p=.732.

Discussion

The current results are basically identical to those of the previous three experiments.

Even when participants are forced to search for a particular color feature, the irrelevant

abrupt onset captured attention. The present findings suggest that regardless whether

participants are set to search for a unique color singleton (the singleton detection mode

as in our Exp. 2) or a specific color feature (the feature search mode as in our Exp. 4), an

abrupt onset captures attention and interferes with search.

General Discussion

The present results are clear. In conditions in which participants have a clear attentional

set for color regardless whether they are looking for a singleton or for a specific color,

they cannot prevent attentional capture by an irrelevant abrupt onset. The results are

consistent with the Contingent Capture Hypothesis in showing that an attentional set for

color results in strong capture by a color cue. However, according to Contingent Capture

hypothesis of Folk et al. (Folk & Annett, 1994; Folk & Remington, 1999; Folk, et al., 1992)

an attentional set for color should have prevented attentional capture by abrupt onsets

because Contingent Capture hypothesis assumes that capture is fully dependent on


CHAPTER 5

107

The pattern of results obtained in the present study indicates that the effect of

the attentional set on capture is very strong, generating cueing effects of about 40 ms.

The distracting effect of the onset is relatively small (about 8 to 10 ms) and appears to

be additive with the cueing effects. This pattern of results implies that the distracting

effect of the onset rides on top of the contingent capture effect of the color cue,

suggesting that independent of whether attention is allocated to a valid or an invalid

condition, the onset captures spatial attention for a very brief time before a response to

the target can be emitted.

The current findings are inconsistent with those of Folk and Remington (1999)

who conducted an experiment very similar to the current one. In their experiment they

also had conditions in which participants were set for a unique color and they showed

that a new object presented with abrupt onset had no effect when participants were set

for color. Indeed, the conclusion of this study was that the appearance of a new object

could not override a top-down set of color. Even though on the face of it, these studies

are very similar, there is one important difference between the current study and that of

Folk and Remington (1999). In the current study the irrelevant onset was presented

simultaneously with the search display, while in Folk and Remington (1999) the onset

was presented during the cue display, i.e., the onsetting new object was presented

before the presentation of the search display. In Folk and Remington’s Experiments 1

and 2 the SOA between cue and search display was 150 ms, a SOA identical to those used

in the original Folk et al. (1992) study. As argued, recovery from attentional capture can

be relatively fast (see Theeuwes, et al., 2000). Therefore, it is possible that in Folk and

Remington’s experiments participants had their attention captured by the abrupt onset

but were able to quickly disengage attention when they realized that the new object was

not a uniquely colored item. Data show that 150 ms SOA between cue and search display

certainly provides enough time to recover from capture (see Kim & Cave, 1999;

Theeuwes, et al., 2000). To address this issue, in Folk and Remington’s Experiment 3, the

SOA was reduced to 50ms. The reasoning was that if the abrupt onsets captures

attention then this should become visible when the search and cue display are presented

relatively close in time (i.e., within 50 ms). Even though this manipulation did not

change the overall pattern of results, Folk and Remington (1999) indicate that there was

a small distracting effect of the onset when participants were set for color. Indeed,

Figure 4 of Folk and Remington (1999) seems to suggest that the onset caused a


108

distraction effect of about 8 ms. As noted by Folk and Remington this effect could very

well indicate the “tail effect” of the recovery from capture. In our experiments the SOA

was basically “zero” because the cue and search display were presented simultaneously.

Obviously, in those conditions, the distracting effect of the onset (effect size of 10 to 20

ms) does become reliable as we demonstrated in all four experiments.

Folk and Remington (1999) also employed the identity intrusion technique (as

we used in our Experiment 3) to show in another way that the onset did not capture

attention. In their Experiment 4, they placed a character inside the abrupt onset that was

either compatible or incompatible with the response to the target. The abrupt onset with

the character was presented for 50 ms during the cue display, immediately masked for

50 ms followed by the search display after another 50 ms. In the critical condition, in

which participants were set for color, Folk and Remington did not find a compatibility

effect suggesting that the onset did not capture spatial attention. Note that we used the

very same technique in our Experiment 3 and showed that there was a small, yet reliable

compatibility effect. It is not immediately clear why we found a compatibility effect and

Folk and Remington (1998) did not, but it is feasible that when the onset is not relevant,

a very brief presentation of the interfering character (i.e., 50 ms) inside the onset

followed by a mask as was employed by Folk and Remington (1999) may not be long

enough to allow enough processing to cause a compatibility effect.

Alternatively, Folk and Remington (1998) argued that compatibility effects as

reported in previous studies (Theeuwes, 1995b; Theeuwes & Burger, 1998) may not

reflect the allocation of spatial attention but maybe the result of parallel processing of

target and distractor information. Even though this is a possibility, it still would imply

that at some point, either in serial or in parallel, attentional resources were allocated to

the location of the abrupt onset. Indeed, it seems to be unlikely that Folk and

Remington’s criticism of the identity intrusion technique implies that identity

information at the location of the distractor is processed without attention. Moreover,

Folk and Remington (1999) used this very same identity intrusion technique to argue

that the absence of a compatibility effect indicates that spatial attention did not go to the

abrupt onset or new object.

Even though the present study shows that abrupt onset capture attention even

when participants have a top-down set for color, this does not imply that onset capture

is never under top-down control. For example, Theeuwes (1991a) showed that when

CHAPTER 5

109

the upcoming target position was cued in advance by a 100% valid cue, an abrupt onset

presented elsewhere in the visual field ceased to capture attention (see also Juola,

Koshino, & Warner, 1995; Yantis & Jonides, 1990). In addition, Martin-Emerson and

Kramer (1997) showed that the capture effect of the abrupt onset is reduced with an

increasing number of no-onset elements in the display (see also Miller, 1989; von

Muhlenen, Rempel, & Enns, 2005). Also, Boot, Brockmole and Simons (2005) showed

that capture by onsets is eliminated when participants have to execute a concurrent

auditory task, suggesting that onset capture may dependent on the resources available.

The present study shows that onsets capture attention regardless whether

participants look for a color singleton (i.e., the singleton detection mode) or look for a

specific color (i.e., the feature search mode). Irrespective of these search modes and

consistent with the contingent capture hypothesis, the matching color cue captured

attention resulting in a large spatial cueing effect. At the same time, regardless of the

top-down search modes, the irrelevant onset captured attention. The discovery that the

search modes had no significant effect in our study adds to the growing number of

studies that supports the notion that these search modes may not be a very useful

distinction (Lamy & Egeth, 2003; Theeuwes, 2004; Theeuwes & van der Burg, 2008).

In conclusion, the present study demonstrates that even when participants have

a clear attentional set for color, an irrelevant abrupt onset or new object captures

attention. In other words, the appearance of the new object overrides a top-down set for

color regardless whether participants are engaged in a feature search or a singleton

detection mode. Since the abrupt onset or new object was always irrelevant for the task

and was presented at an empty location that never contained a target we argue that this

attentional capture is genuinely exogenous.

Author Note

This work was based on the master’s thesis of D.S. We thank Jim Brockmole, Angus

Gellatly, and Michael Proulx for excellent comments on an early version of the

manuscript.

Chapter 6 Abrupt onsets capture attention

independent of top-down control settings II: Additivity is no evidence for filtering

Schreij, D., Theeuwes, J. & Olivers C.N.L (2010). Abrupt onsets capture attention independent of top-down control settings II:

Additivity is no evidence for filtering. Attention, Perception & Psychophysics 72(3), 672-682

ATTENTIONAL CAPTURE BY ABRUPT ONSETS INDEPENDENT OF ACS II

112

Abstract

Is attentional capture contingent on top-down control settings or involuntarily driven by

salient stimuli? Supporting the stimulus-driven attentional capture view, Schreij, Owens

and Theeuwes (2008) found that an onset distractor caused a response delay in spite of

participants having adopted an attentional set for a color feature. However, Folk,

Remington and Wu (2009) claimed that this delay reflects separate, non-spatial filtering

costs instead, because the onset effects were additive with color-based capture effects,

and capture should have caused underadditivity. The current Experiment 1 shows that

contingent capture caused by additional color cues is also additive, just like the onset

effect. This makes additivity a dubious diagnostic with regard to spatial capture.

Experiment 2 demonstrates that it is possible to obtain underadditivity when attention-

demanding distractors have sufficient capturing power. Experiment 3 shows that the

abrupt onset interference turns into benefits when the locations of the onset and the

target coincide. Together, these results argue in favor of stimulus-driven attentional

capture by abrupt onsets.

CHAPTER 6

113

Introduction

A frequently debated issue in attention research is which underlying cognitive

mechanisms are fundamental for the ability of objects to capture attention. Can

attentional capture be driven by bottom-up, stimulus-related factors, or is capture

always contingent on what the observer is looking for (i.e. his or her top-down

attentional set)? The latter stance has been advocated by Folk and Remington and

colleagues on the basis of spatial cueing studies in which observers looked, for example,

for a red target among white distractors (Folk & Remington, 1998; Folk, et al., 1992).

Prior to the target display, a cue appeared which unpredictably indicated the target

position (valid cue), or one of the distractor positions (invalid cue). Even though the

cues were uninformative, valid cues resulted in faster response times (RTs), but only

when the cue matched the target-defining property – that is, when it was also red. When

the cue was instead defined by a single abrupt onset, there was no cueing effect. This

suggests that the cue captures attention in a spatial manner, but only when it carries a

feature that is relevant to the goals of the observer. In other words, attentional capture

is contingent on the top-down attentional set (for a different account of contingent

capture results see Belopolsky, Schreij, & Theeuwes, 2010).

Recently, Schreij, Owens and Theeuwes (2008) reported evidence that appears to

be inconsistent with the contingent capture hypothesis. In a task that was very similar to

the spatial cueing paradigm of Folk et al. (1992), Schreij et al. (2008) found that even

when observers had an attentional set for color, the presence of an irrelevant abrupt

onset nevertheless slowed participants in finding the target. As in the Folk et al.

paradigm, participants searched for a red target, and an attentional set for redness was

indeed demonstrated by a strong validity effect of the matching red pre-cue. At the same

time, the presence of an abrupt onset in the target display interfered with responding,

regardless of whether the red cue was valid or invalid. Consistent with earlier claims

suggesting that onsets capture attention in a stimulus-driven manner (Belopolsky, et al.,

2005; S.E. Christ & Abrams, 2008; Enns, et al., 2001; Gellatly, 1999; R. Remington,

Johnston, & Yantis, 1986; Theeuwes, 1990, 1994b; Yantis & Jonides, 1984), Schreij et al.

(2008) concluded that even when observers adopt a clear top down set for color, they

cannot prevent attentional capture by the onset. According to the contingent capture

hypothesis, the presence of the onset should have had no effect on responding because it

was completely irrelevant to the task.


114

However, Folk, Remington, and Wu (2009) have questioned whether the

interference caused by the abrupt onset distractor was due to a bottom-up shift of

attention to the location of the onset. In line with earlier claims of Folk and Remington

(1998), they argued that the interference was due to non-spatial filtering costs, a notion

first introduced by Kahneman, Treisman and Burkell (1983). According to the filtering

explanation, irrelevant new objects that appear simultaneously with the target compete

for attention and need to be filtered out. This filtering operation slows RTs to the target.

In other words, an irrelevant object can cause a delay in the deployment of attention to a

relevant object, without itself invoking a shift of attention. Specifically, in the Schreij et

al. (2008) study, the onset would be competing with the target, thus causing filtering

costs. The filtering explanation is compatible with the contingent capture hypothesis

because attention only goes to the item that matches the attentional set for color; it

assumes that attention does not go to the location of the abrupt onset, which only causes

a non-specific filtering cost. Because capture and filtering operations are presumed to

take place during independent stages of processing, additive effects of color-based

cueing and onset interference would be expected (Sternberg, 1969) As pointed out by

Folk et al. (2009), this was exactly what was found by Schreij et al. (2008): the

interference caused by the onset presence was equally strong for trials with valid as for

trials with invalid color cues. Therefore, if one accepts that the color cue captures spatial

attention, then the onset cannot do so too. According to Folk et al. (2009), if the onset

presence and color-based cueing would both operate on the same process of spatial

capture, one would expect these two factors to show an underadditive relationship

instead. After all, if one assumes that capture by the onset made the cue obsolete, then

attention should move directly from onset to target, regardless of cue validity. Thus,

according to Folk et al. (2009), the elimination of attentional capture is rather

instantaneous, in that the subsequent appearance of another salient object “should

effectively eliminate the [earlier] effects” (p. 309).

We however assume that the local activation of an object does not have to be

instantaneous. Activity takes some time to build up, and may take even more time to

dissipate. Especially when a distractor object looks like a target object, resource

allocation may be more sustained, making it difficult to disengage from this object (see

Theeuwes, et al., 2000). If one accepts that an object’s capturing power can be sustained

for a while (especially when it looks task-relevant) then the additivity of color-based

CHAPTER 6

115

cueing and onset interference is not so strange from an attentional capture perspective:

The abrupt onset may briefly capture attention away from the red cue, but because the

onset is not relevant, whereas the red cue was, attention rapidly returns to the latter. An

alternative solution is that attention first lingers for quite some time at the cued location

even after the cue has disappeared and the target display is already present. Thus

attention can already gather some evidence about whatever object is present at that

location (which may be a target). This process is then disrupted (but not re-set) because

attention is captured away by the abrupt onset. When attention in turn disengages from

the abrupt onset, the color cues may indeed already be forgotten, as Folk et al. suggest,

and attention moves directly back to the target. However, in the case of a valid cue, a

large part of the evidence on which response to make might have already been

accumulated by then, resulting in a speeded response (in other words a cueing effect

that is additive with an onset effect).

This paper investigates the claim that two objects that subsequently capture

attention should always show an underadditive relationship. If Folk et al. (2009) are

correct and capture by a subsequent object always nullifies any previous capture effects,

such underadditivity should also be found when both consecutive capturing objects are

contingent upon the observer’s attentional set. However, if additivity is found in this

case as well, the criterion of underadditivity cannot be regarded as a suitable diagnostic

for or against the occurrence of attentional capture.

Using further adaptations of the Folk et al. (1992) paradigm, Experiment 1

demonstrates that interference by a distractor is also additive with the cueing effect

when the distractor carries the task-relevant feature and thus, according to the theory of

contingent attention capture, is assumed to capture attention. Experiment 2 shows that

a distractor is actually able to eliminate the effects of a pre-cue completely, resulting in

an underadditive relation, when it both has a strong bottom-up signal and is contingent

on the participant’s attentional set. As these experiments show, the occurrence of

additivity is not a reliable diagnostic for or against attentional capture, but depends on

the relative strength of the distractor. Experiment 3 shows that the additional abrupt

onset yielded considerable RT benefits rather than costs when its location incidentally

coincided with the target. This too indicates that the new abrupt onset element actually

attracted attention to its location rather than resulting in general filtering costs.


116

Figure 19: An illustration of sequence of events for a trial of experiment 1. First a fixation display is shown for 500ms, after which the central fixation cross is turned off for 50ms. After this, the fixation display is shown again for a period of 1000ms. Then a cue display will appear for 50 ms and after an ISI of 150ms in which the fixation display is show again, the target display will be presented for 2000 ms or until the subject responds. When there was a distractor cue, it was presented for 50 ms between the cue and target display and was preceded and succeeded by a 50 ms fixation display. This is an example of a valid trial, since the location of the red balls in the cue display and the location of the red letter in the target display are the same. In reality the background was black, black lines where white and the gray elements were red.

CHAPTER 6

117

Experiment 1

This experiment investigated whether a pattern of additivity can serve as a useful

diagnostic against attentional capture. We took the Schreij et al. (2008) version of the

Folk et al. paradigm, but we left out the onset distractor and instead briefly made one of

the other distractor boxes red. This red distractor was always invalid. Thus, the displays

contained a red cue (valid or invalid), then potentially followed by a red distractor

(invalid) and afterwards the target display. The contingent capture theory states that the

new red distractor should capture attention away from the initially cued location. After

all, red is what the observers are looking for, and capture by red is what explains the

original cueing effect. If such capture by a new distractor would indeed erase or reduce

all prior cueing effects, the red distractor should here attenuate the benefits of a valid

color cue, resulting in underadditivity. If, on the other hand, there is still residual

activation of the first cue, strong enough to affect the reorienting towards, or the

identification of the target, then we may again observe additivity between cue validity

and the presence of the red distractor.

To further support the claim that both cues captured attention, it was

investigated if cued distractor identities interfered with responses to the target,

following the identity intrusion method introduced by Theeuwes (1996; see also

Theeuwes & Burger, 1998). The assumption is that if attention is shifted to the location

of the cue, the identity of the object at that position will be preferentially processed (e.g.

Kramer & Jacobson, 1991). If the distractor identity is compatible with the target

identity, performance may benefit, relative to when distractor and target are

incompatible. This compatibility effect would further strengthen the claim that the

distractor captured spatial attention (See Folk, Leber, & Egeth, 2002 for a similar

argument).

METHOD

Participants

Ten students, between 18 and 27 (average 21) years old, of the Vrije Universiteit of

Amsterdam participated in this experiment in return for money or course credits. All

reported no color blindness and normal or corrected-to-normal vision.

Apparatus & stimuli


118




768 pixels. The “X” and “M” keys on a normal keyboard were used to register the

participants’ responses. Stimulus presentation and response recording were done in E-

prime 1.2 (Psychological Software Tools, 2003). The experiment was executed in a dimly

lit and soundproof room, in which participants were seated at a distance of

approximately 75 cm from the screen. All displays had a uniform black background. The

fixation display consisted of a bright white (CIE(0.286, 0.311), 59,50 cd/m2) fixation

cross at the center of the screen, surrounded by four light gray (CIE(0.285, 0.306),

luminance 28.28 cd/m2) placeholder boxes measuring a width of 3.4o visual angle. The

four boxes were positioned above, below, to the left and to the right of the fixation cross,

along a virtual circle with a radius of 6.6o visual angle, with the fixation cross as the

center. The cue display consisted of the same elements as the fixation display, with the

addition of four dots, with a diameter of 0.5o visual angle, positioned along the outside of

the center of each rib of all the placeholder boxes. One set of these dots surrounding one

of the placeholder boxes had a red color, (CIE(0.621, 0.345), 10.43 cd/m2) and indicated

the cued location. All the dots surrounding the other boxes had a bright white color,

(CIE(0.286, 0.311), 59,50 cd/m2). Until the presentation of the target screen, each of the

boxes contained a bright white figure, which consisted of overlapping “X”,”|” and “=”

symbols. When the target display was presented, the irrelevant line segments were

removed, revealing an “X” (Myriad Roman, 21pt) or an “=” (Myriad Roman bold, 22pt)

inside each of the boxes. At this same moment the color of the target character turned

from white into red. There were always two ‘X’s and two ‘=’s present. To serve as a

distractor cue, one of the placeholder boxes briefly flashed from white to red (CIE(0.621,

0.345), 10.43 cd/m2)

Design & Procedure

There were two important factors. The first was the validity of the first color cue, which

could be valid or invalid. The second was the presence of a red distractor (absent or

present). This resulted into a 2 x 2 factorial design. The red distractor was always invalid

and would never appear on a cued location, while the first color cue was valid in only

25% of the trails and invalid for the rest. The first cue validity was varied within blocks

CHAPTER 6

119

and the presence of the second cue was varied between blocks. There were 9 blocks of

80 trials, of which the first block was a practice block.

Participants were tested in a 30 minute session. Before the experiment started,

oral instructions were given to familiarize them with the task. Participants were told to

keep an index finger on each of the two response buttons and to not move their eyes

away from fixation during a trial, because this would impair their performance. The

target character appeared in one of the present boxes on the display, it was equally often

an X or a =, randomly mixed within blocks. At the end of each block, participants were

advised to take a rest and were forced to wait for at least 30 seconds, before they could

continue.

Trials began with the presentation of the fixation display for 1000 ms, after

which the fixation cross blinked off and on for 100 ms, to notify the participant of the

start of a trial. The fixation display then remained on the screen for another 100 ms after

which a cue display was presented for 50 ms. If a distractor cue was present, it appeared

50 ms after the first cue disappeared, with a duration of 50 ms. Afterwards, the fixation

display was again presented for 50 ms before the target display appeared. If the second

cue was absent, then the first cue would simply be followed up by a fixation display for

150 ms, after which the search display was presented until the participant responded

(with a maximum of 2,000 ms). The participant was instructed to look for the red item,

and press “X” when it was an X, or press ”M” when it was an =. A distinctive sound was

played for a correct or incorrect response. If the response was incorrect, the experiment

paused for 5 seconds to let the participants regain their focus. There was an inter-trial

interval of 500ms.

Results and discussion

Incorrect responses were removed from the dataset, resulting in a loss of 3.3% of the

trials, as were responses with RTs below and above 2.5 SD from the mean (another 2%).

The remaining data is depicted in Figure 20 and was first submitted to an ANOVA with

Red Distractor (absent, present) and Cue Validity (valid, invalid) as factors.

There was a significant main effect of Cue Validity, F(1,9) = 19.77, p < .001.

Participants were slower after an invalid cue than after a valid cue. The presence of the

red distractor slowed the responses by 18 ms, Red Distractor, F(1,9) = 13.76 , p < .001.

There was no interaction between Distractor Cue and Cue Validity, F(1,9) < 0.5, p > .5,


120

indicating additive effects of distractor presence and cue validity. The same analysis of

the error pattern revealed no significant effects, F(1,9) = 0.882, p = .372.

Another analysis investigated possible compatibility effects between the target

character and the characters located at the color cue and the red distractor. When there

was no red distractor present and the cue was invalid, the character at the cued location

showed a reliable compatibility effect with the target, t(9) = 2.61, p < .05. An

incompatible character made participants respond more slowly than a compatible

character (by 14 ms). When a distractor cue was present, this compatibility effect

disappeared, t(9) = 1.59, p = .147. However, in this case there was a significant

compatibility effect with the character at the red distractor location, t(9) = 2.87, p < .05

(by 14 ms). Thus, the identity of the character at the distractor cue interfered with the

response to the target.

500

510

520

530

540

550

Mea

n C

orre

ct R

T (m

s)

Distractor cue absentDistractor cue present

0%

1%

2%

3%

4%

5%

6%

invalid validCue validity

Erro

r

Figure 20: Results of Experiment 1. The RTs and error percentages are shown as a function of cue validity, in the situations where a second red distractor was absent or present.

CHAPTER 6

121

An analysis on the errors with similar factors yielded no surprises. Error rates

were equal among all conditions and levels.

The contingent capture account leaves no other option than assuming that the

red distractor captured attention, since a) its color matched the participant’s attention

set for the task and b) it resulted in increased RTs. If one denies that the red distractor

captures attention, one would run the risk of also having to deny that the red cue

captures attention – something which obviously goes against the claims of contingent

capture. Even so, we find almost perfect additivity between the red cue and the red

distractor. An invalid cue added about 20 ms to response times, and so did the presence

of a red distractor, regardless of cue validity.

The costs inflicted by the red distractor in this experiment were generally of

greater magnitude than the costs inflicted by an onset distractor in Schreij et al. (2008).

Most likely this is because the red distractor contained a task relevant feature, which

may have resulted in more trouble disengaging attention from the distractor. The

observation that the cue induced compatibility effects also corroborate the claim that

the distractor successfully captured attention away from the first cue, since there is only

a compatibility effect of the first cue when the distractor cue is absent and, when

present, the distractor cue yields its own compatibility effect. Yet despite these

somewhat stronger distractor effects, the relationship with the cueing effect remained

additive.

It is also unlikely that the costs generated by the distractor cue are due to

filtering, since according to the filter account, filtering costs generally only accompany

the appearance of a new perceptual object, and the distractor cue was actually formed

by a feature change to an old, already present object. In addition, this change occurred

100 ms before the target appearance, while filtering costs are claimed to be usually only

manifested with simultaneous appearance as the target (Folk & Remington, 1998;

Kahneman, et al., 1983).

To conclude, it appears that the onset effects as found in Schreij et al. (2008) are

very similar to contingent capture effects, in terms of their additivity with earlier

capture effects. It seems that contingent capture is partly a sustained phenomenon of

which lingering effects are not easily terminated by subsequent events. It is possible that

such sustained effects are due to the seemingly task-relevant nature of the capturing

event, which may trigger slower but longer lasting top-down feedback mechanisms. If


122

underadditivity is a strict prerequisite for attentional capture by the onset distractor in

previous experiments, then contingent capture by the red distractor in the present

experiment should not have been additive to the effect of the color cue. In other words, if

we accept that the distractor captured attention in the current experiment, then

additivity per se is not a diagnostic for or against attentional capture. Thus, the

argument that additivity between cue validity and onset presence is better explained by

filtering costs and thus excludes attentional capture is doubtful.

Experiment 2

The important question remains why later distractors (whether color-based or onset-

based) did not obliterate the earlier cueing effect (i.e. cause an underadditive interaction

of cueing and distractor effects). We have already suggested that the attentional priority

induced by the cue may linger, thus even exerting effects after observers have already

visited the next distractor. This would still mean that if there exists a distractor powerful

enough to capture attention away from the location of the contingent pre-cue, plus then

hold attention long enough for the cueing effect to finally dissipate, underadditivity may

be observed. With 10 to 20 ms interference effect the onset distractor in Schreij et al.

(2008) or the attentional set-matching red distractor of Experiment 1 may not have

been strong enough. We expected that if anything, a distractor that was both salient in a

stimulus-driven fashion (i.e. it featured an abrupt onset) and that carried a feature also

possessed by the target at the same time (i.e. its bounding box was red), might do the

job, as it would evoke both contingent top-down and stimulus-driven attentional

resources. It has been argued before that attentional disengagement from items

possessing task-relevant features is more time-consuming than from irrelevant items

(Theeuwes, et al., 2000). We argued that if the onset distractor manages to occupy

attentional resources long enough, any residual effects of the pre-cue will have

dissipated once attention has been able to disengage from the distractor location. The

consequence would be that attention will not return to the previous position of this cue,

eliminating the cueing effects as found in previous experiments, this time resulting in an

underadditive relation between onset presence and cue validity. At the same time, this

would again demonstrate a crucial contribution of the onset to attentional capture.

CHAPTER 6

123

METHOD

Participants

13 students, between 18 and 30 (average 24) years old, of the Vrije Universiteit of

Amsterdam participated in this experiment in return for money or course credits. All

reported no color blindness and normal or corrected-to-normal vision.

Apparatus, stimuli, design and procedure

The apparatus and stimuli were largely similar to Experiment 1, except that there was

no longer a distractor cue and that in a new contingent onset distractor condition the

distractor was a white onset character appearing in a red bounding box positioned

between two old bounding boxes (in addition to the irrelevant onset condition). The

target itself never appeared through an abrupt onset. In addition, the ISI between the

cue and target display was reduced from 150 ms (as in Experiment 1) to 100 ms, as it

was in Folk et al. (1992). Thus, the important factors of this experiment were Cue

Validity (invalid, valid) and Onset Presence (No Onset, Onset), which were varied within

blocks, and Onset Distractor Type (Irrelevant Onset, Contingent Onset), which was

varied between blocks. The experiment consisted of 2 practice blocks and 10

experimental blocks, each consisting of 80 trials, which took participants around 45

minutes in total to complete.


Incorrect responses were removed from the dataset, discarding 3.7% of the trials, as

were responses with RTs below and above 2.5 SD from the mean (another 2.1%). The

remaining data is depicted in Figure 21 and was submitted to an ANOVA with Cue

Validity (valid, invalid) and Onset Presence (no onset, onset) for both conditions of

Onset Distractor Type (contingent vs. irrelevant).

When the onset had an irrelevant white colored bounding box, cue validity and

onset presence were significant as before, F(1,12) = 17.66, p < .001 and F(1,12) = 13.69.

p < .001 respectively, demonstrating that a valid cue yielded considerable response

benefits and the presence of an onset slowed down participants. The interaction

between these two factors was far from significant (p > .6). In the blocks where the onset

had a red colored bounding box, there was no main effect of Cue Validity, F(1,12) = 1.07,

p = .321, indicating that there was no difference between RTs for a valid and invalid cue.


124

B)

450

470

490

510

530

550

570

590

610

Mea

n C

orre

ct R

T (m

s)

No OnsetIrrelevant Onset

0%

4%

8%

invalid validCue Validity

Erro

r

Figure 21: Results of Experiment 2. The RTs and error percentages as a function of cue validity, in situations where there was no onset and where the onset appeared in A) a white box (normal onset) or B) a red box (contingent onset).

A)

0%

4%

8%

invalid validCue Validity

Erro

r450

470

490

510

530

550

570

590

610

Mea

n C

orre

ct R

T (m

s)

No OnsetContingent Onset

The main effect of Onset Presence was significant, F(1,12) = 13.08, p < .001. Participants’

responses were delayed when an onset was present. Importantly, the interaction

between Cue Validity and Onset Presence was significant F(1,12) = 6.59, p < .05. When

present, a contingent red onset annihilated the validity effect of the earlier color cue.

Pair-wise comparisons of the valid and invalid cue conditions revealed that there was an

effect of the cue in the no-onset condition [t(12) = 2.379, p < 0.05], but not when a

contingent onset was present [t(12) = -0.471, p = .646].

Comparing the no-onset trials in the contingent-onset with the irrelevant-onset

blocks, it was found that participants were significantly slower during the contingent

onset blocks, F(1,12) = 5.62, p < .05. Conducting an ANOVA with Onset Distractor Type

(Contingent, Irrelevant) and Cue validity(Invalid, Valid) as factors on all onset-present

trials revealed that participants were significantly slower when a contingent red onset

CHAPTER 6

125

was present, than when a irrelevant onset was present, F(1,12) = 10.21, p < .001. The

interaction between Cue Validity and Onset Presence was significant as well, F(1,12) =

8.52, p < .001, showing that the cueing effect got attenuated by the contingent red onset

distractor.

For completeness, we also investigated if the onset character caused a response

compatibility effect with the target, for both levels of Onset Distractor Type. An ANOVA

with Cue Validity (Invalid, Valid) and Compatibility (Incompatible, Compatible) as

factors revealed a significant main effect for Compatibility in both Irrelevant and

Contingent Onset conditions. F(1,12) = 32.597, p < 0.01 and F(1,12) = 6.708, p < 0.05,

respectively. Participants thus responded slower with an incompatible onset, than with

a compatible one, regardless if it contained task relevant features. In neither Onset

Distractor Type condition was there an interaction of Compatibility and Cue Validity (p >

0.1 for both conditions).

Analysis on the error rates in the irrelevant onset blocks revealed no significant

effects. In the contingent onset blocks, only Onset Presence reached significance, F(1,12)

= 82.94, p < .001. Participants made significantly more errors when a contingent red

onset was present, than when it was absent.

Thus, distractors matching the participants’ attentional set inflicted larger RT

costs and were accompanied by larger error rates than distractors that were not

contingent on the attentional set. This supports the notion that attentional capture

towards, and/or attentional disengagement from task-relevant items is more time

consuming than from items that are deemed irrelevant (Theeuwes, et al., 2000).

Additionally, a contingent red onset distractor managed to completely eliminate the

effect of the pre-cue, as opposed to the onset-only distractor. Apparently, the

combination of bottom-up salience and top-down task-relevance gave the distractor the

necessary boost to completely overrule a lingering cue validity effect.

Another interesting finding is that response times were generally higher in

contingent distractor blocks than in irrelevant distractor blocks, even on no-onset trials.

Participants apparently became more conservative overall in responding when they

knew that the distractor could share critical features with the target. This overall delay

may also have allowed for further decay of lingering cueing effects.

The interaction between cue validity and the contingent red onset as found in the

current experiment exhibits the stronger notion of capture proposed by Folk et al.


126

(2009) in that it meets the criterion of underadditivity. However, it also adds a

constraint in that the capturing item has to be sufficiently strong to overcome the earlier

cueing effects. In the present case, adding a strong bottom-up signal – an abrupt onset –

was sufficient. If the distractor lacks a strong bottom-up signal (as in Experiment 1) or

does not contain a task-relevant feature (as in Schreij et al., 2008), residual activation of

a pre-cue will be able overcome capture by the irrelevant item and draw attention back

to its location, with additivity as a consequence. In any case, the conclusion is that

bottom-up signals strongly contribute to attentional capture.

Experiment 3

If the filtering account is correct, onsets do not capture attention when the observer is

not looking for onsets. If anything, the observer is set against onsets, as they need to be

filtered out from competition in order to prevent interference with target processing.

The prediction then is that occasional targets featuring an abrupt onset should not be

processed any faster than normal targets that feature no abrupt onset. In contrast, if

onsets automatically draw attention, as stated by the capture account, then a target

appearing with an abrupt onset should allow for faster responses than for no-onset

targets.

Earlier work by Yantis and Jonides (1984) has indeed shown that onset targets

are given priority even when on the majority of trials the abrupt onsets are distractors.

In their experiments, observers viewed a display of pre-masks, of which one was likely

to change into a target. Together with the display change, a new object was added to the

display, which only occasionally was the target. Nevertheless, search was faster and

more efficient when the new object indeed turned out to be the target, consistent with

the idea that it captured attention (see also Becker, 2007) . Here we wished to apply

exactly the same logic to the paradigm used by Folk et al (1992). In the current

experiment the onset coincided with a distractor on the vast majority of trials (as in the

previous experiments), but now it could also accidentally coincide with the target

(which was again a red item) Hence, observers had no incentive whatsoever to attend to

the abrupt onset, and would be expected to employ an attentional set only for red (as

indicated once more by a cueing effect). If the filtering account is correct, and the onset

does not capture attention, there should be no benefit for onset over no-onset targets. If

the capture account is correct, and following Yantis and Jonides (1984), response

CHAPTER 6

127

benefits should be observed for onset targets because onsets involuntarily capture

attention.

METHOD

Participants

Eight students aged between 20 and 30 (average 24) from the Vrije Universiteit

Amsterdam participated in a half hour session in exchange for course credit or money.

Apparatus and stimuli

Apparatus and stimuli were largely the same as in Experiment 2, with the exception of

the following adaptations: In the onset distractor condition an extra light grey bounding

box containing a bright white character (either “X” or “=”) suddenly appeared in the

search display at the same moment that the other characters were revealed. In the onset

target condition this character was presented in red.

Design and procedure

The design and procedure were mostly identical to Experiment 2, except for the

following: There were no more contingent distractor blocks. A new factor Onset Type

consisted of the following levels: In the no onset condition, there was no additional onset

present. In the onset distractor condition, the new onset contained a distractor item (‘X’

or ‘=’). In the onset target condition, the new onset contained the target. This implied

that in both onset distractor and onset target condition, the effective set size was 5,

while in the no-onset condition it was 4. Cue Validity was varied as in Experiment 2, but

note that in the onset target condition, the cue was always invalid (since the empty

location in which the onset target appeared could not be cued). There were eight blocks

of 80 trials each, preceded by a practice block of 40 trials. Only 6 of the 80 trials per

block would contain an onset target. The onset was a distractor on 34 trials, and there

was no onset on the remaining 40 trials.


Incorrect responses were removed from the dataset, resulting in a loss of 3% of the

trials, as were responses with RTs below and above 2.5 SD from the mean (another 2%).

The remaining data is depicted in Figure 22 and was first submitted to an ANOVA with

Onset Type (no-onset, onset distractor) and Cue Validity (valid, invalid) as factors. The


128

onset target level was omitted in this analysis, because it could not be fully crossed with

Cue Validity (as onset targets could only be invalidly cued, see Method section). We will

return to onset targets below. There was a significant main effect of Cue Validity, F(1,7)

= 49.48, p < .001. Participants were slower after an invalid cue than after a valid cue. The

presence of an onset distractor also slowed the responses, Onset Type, F(1,7) = 40.80 , p

< .001. There was no interaction between Onset Type and Cue Validity, F(1,7) < 1.9, p >

.2, pointing towards additive effects.

To assess the effect of an onset target, we examined at invalidly cued trials only

for onset target, onset distractor, and no onset trials. A one-way ANOVA revealed a main

effect of Onset Type, F(2,14) = 26.05, p < 0.001. Separate comparisons revealed a

significant benefit for onset target trials relative to no onset trials and onset distractor

430

440

450

460

470

480

490

Mea

n C

orre

ct R

T (m

s)

Onset distractorNo onsetOnset target

0%1%2%3%4%5%

Invalid Valid

Cue Validity

Erro

r

Figure 22: Results of Experiment 3. The RTs and error percentages as a function of cue validity, when the onset was a target, a distractor, or there was no onset at all.

CHAPTER 6

129

trials, t(7) = 4.13, p < .01, t(7) = 5.70, p = 0.001, respectively. RTs on onset distractor

trials were significantly slower than on no onset trials, t(7) = 5.65, p = 0.001.

Analysis for compatibility effects with Cue Validity( Valid, Invalid ) and

Compatibility (Incompatible, Compatible) as factors once more revealed a significant

effect of target-distractor compatibility, F(1,7) = 32.739, p < .001. Participants

responded slower to a target when it was accompanied by an incompatible distractor

than by a compatible distractor. There was no interaction between Cue Validity and

Compatibility (p > .8).

The error pattern largely followed that of the RTs and the same analyses revealed

no significant effects (although Cue Validity approached significance, F(1,7) = 6.156, p =

0.056).

The results clearly demonstrate a performance benefit over no-onset trials when

the target featured an abrupt onset (in the invalid cue condition), as opposed to costs

when the onset coincided with a distractor. This provides direct evidence for an

attentional capture account: Despite its irrelevance to the task, the abrupt onset results

in a local enhancement of processing, leading to benefits when it is a target, and costs

when it is a distractor. No such benefits would be predicted by the filtering account:

According to this account, the onset is irrelevant. As the cue validity effects once more

demonstrate, the observers were set for red, not for onsets. In defense of a filter account,

one might argue that the transient of the onset made the target more salient and hence

easier to orient to. However, if this is the case, it would argue against the primary idea of

contingent capture, namely that the allocation of attention does not depend on salience,

but only on task relevance. The idea that high salience facilitates (or invokes

involuntary) orientation of attention towards objects is usually a claim made by the

attentional capture account. Another possibility is that the onset benefit stems from

differential masking as caused by the pre-masks for old objects. However, we consider

this unlikely. Using the current displays, Schreij et al. (2008; Experiments 1 & 2) directly

compared performance under the presence of premasks vs. no premasks and found no

influence of this on the interference caused by abrupt onsets.

General Discussion

There has been a longstanding discussion on whether irrelevant visual objects demand

spatial attention or demand additional filtering operations (Becker, 2007; Folk &


130

Remington, 1998; Kahneman, et al., 1983; Theeuwes, 1994b; Theeuwes & Burger, 1998).

These two mechanisms are by no means mutually exclusive, and, as pointed out by

Becker (2007) different paradigms may result in different emphasis on one or the other.

This is why here and in Schreij et al (2008) we chose to integrate several attentional

capture paradigms (Folk et al., 1992; Theeuwes, 1992; Yantis & Jonides, 1984) and see if

particular findings generalize. Experiments 1 and 2 investigated the claim made by Folk

et al (2009) that if a distractor captures attention away from the cued location, its effect

should be underadditive with the effect of cue validity. This implies that if the onset

distractor captures attention, there should be little to no response benefits for a valid

preceding cue. Experiment 1 demonstrated that a contingent non-onset distractor was

able to capture attention away from the pre-cued location, but that a target appearing at

this location still enjoyed considerable response benefits. The contingent distractor

effect was additive with the contingent cueing effect, suggesting that a) the effects of

cueing were prolonged well into the target display, and b) additivity per se is not a good

diagnostic for or against attentional capture. Experiment 2 then showed that when an

abrupt onset was added to the contingent distractor, the cueing effects disappeared. We

infer that only a sufficiently strong distractor is capable of eliminating lingering cueing

effects, in this case when it both has a strong bottom-up signal and is contingent on the

participants’ attentional set. In Experiment 3, onset costs turned into benefits when the

onset coincided with the target location, indicating preferential processing of onsets.

According to the useful taxonomy of capture and filter effects outlined by Becker (2007),

especially the latter effect passes the criterion for attentional capture: Prioritized

processing of an item is not expected if the response time costs it generates when it is a

distractor are the result of a filtering operation. Since a filtering operation is assumed to

only suppress elements, a facilitated response to objects that should normally be filtered

out is exactly the opposite of what one would expect and can be better explained by

attentional capture.

Another possible explanation for the priority given to the abrupt onset here and

in Schreij et al. (2008) might be that here and in the previous experiment an onset

distractor was disruptive because participants operated in “singleton detection mode”

(Bacon & Egeth, 1994) in search for the target. Since the target was the only red

character among white distractors, it constituted a color singleton, a property which

participants might have actively used to find it. An onset however may also temporarily

CHAPTER 6

131

obtain a singleton status, due to its strong transient. Therefore the onset and color

singleton might be direct competitors as the only salient elements in the display, when

participants search for any salient object. However, Experiment 4 of Schreij et al. (2008)

precludes this explanation. Even when the color target was not a singleton, the onset

still interfered. In this case, all distractors were heterogeneously colored and

participants were required to actively search for redness, forcing them to use “feature

detection mode” (Bacon & Egeth, 1994). Furthermore, the current set-up closely

matched that of the original Folk et al. (1992) experiments, in which the targets were

also singletons, yet there was no evidence of singleton detection mode there, since

singletons that did not match the attentional set did not result in cueing effects.

While we believe that our findings support the claim that onsets have a special

status of being able to capture attention regardless of one’s attentional set, the results

appear to contradict the findings of Folk et al (1992), showing that an abrupt onset cue

did not cause any validity effect (and hence did not appear to capture attention), when

participants searched for a target defined by color. Theeuwes et al. (2000) explained this

lack of capture in the Folk et al. (1992) paradigm by reasoning that during the short SOA

between cue and target appearance, any capture effect of an irrelevant cue might have

already dissipated, especially since the irrelevant cue contained no task-relevant

features. This made swift disengagement from the distractor location possible. In the

Folk et al. (1992) study the onset cue appeared 150 ms prior to the target, while in most

studies where capture by irrelevant onsets was found, the onset appeared simultaneous

with the target, leaving no time for the capturing power of the onset to diminish. After

all, Schreij et al. (2008) found the costs inflicted by an onset distractor appearing

simultaneously with the target to be only 15 ms on average, which is short enough to

have already fleeted in the SOA between cue and target as used in the experiments of

Folk et al.

However, Lamy and colleagues (Lamy, 2005; Lamy & Egeth, 2003 Exp. 3-4) have

shown that an irrelevant onset cue was actually able to capture attention even when it

appeared before the target, like in Folk et al.’s original experiments. These studies

identified onset salience and the predictability of onset-to-target SOA as important

factors for evoking involuntary capture by irrelevant onsets. An onset cue managed to

capture attention when it was relatively salient and preceded the target at an

unpredictable SOA. These parameters were fixed in the original Folk et al. study, and


132

seemed important for modulating capture by onsets. Because the onset distractor was

presented before the target display, the measured effects were unambiguously spatial.

The fact that Theeuwes et al. (2000) only found capture for short SOAs, in spite of using

an unpredictable distractor to target SOA, could possibly be attributed to the fact that

they used a less salient, static (color-based) distractor, instead of an onset distractor.

Related to the idea that the onset has to be sufficiently salient, previous research

has shown that the capturing power of an onset is the largest when it also makes up a

new perceptual object (Enns, et al., 2001; Yantis & Hillstrom, 1994). The onset of a

complete box including a letter as used by us here can be regarded as a new object, but

this may not be true for the four small white dots which Folk et al. used as their onset

pre-cue. These might have been perceived as a property change of an old object, namely

the bounding box which they surrounded. For this reason, the capturing power of the

cue as used in Folk et al. paradigms might not have been sufficient for longstanding

effects, being the reason they found a lack of capture by an onset cue when participants

searched for a color target (though see Folk & Remington (1999) for a study of

contingent capture with new-object onsets).

Other support that new object onsets capture attention comes from research by

Brockmole and Henderson (2005). They conducted a study in which they tracked eye

movements over natural scenes. Incidentally a new object was abruptly presented either

during fixation or during a saccade. In both situations the new object was fixated more

often than chance. However, onsets that appeared during fixation were fixated sooner

and more often than those coinciding with saccades. This made the authors conclude

that a new object does not need to have a perceivable transient to capture the eyes; a

non-transient new object is capable of doing so as well, though to a lesser extent. The

fact that these effects were not modulated by observers’ expectations concerning the

appearance of new objects, strengthens the notion that onset prioritization is

involuntary and the finding that our eyes consistently move to new objects, underpins

that this prioritization is spatial in nature (see also Theeuwes, et al., 1998).

Identity intrusion

Schreij et al. (2008) found additional evidence for attentional capture by the onset in an

experiment using the so-called identity intrusion technique first introduced by

Theeuwes (1996; see also Theeuwes & Burger, 1998) Instead of presenting a neutral

CHAPTER6

133

abruptonset,theabruptonsetwaseithercompatibleorincompatiblewiththeresponse

totheidentityofthetarget.Thistechniquerestsontheassumptionthat ifattentionis

shifted to the locationof theabruptonset, its identitywillbepreferentiallyprocessed

(e.g. Kramer& Jacobson, 1991). An incompatible distractor identitywould thenmore

greatlydegradetaskperformancethanacompatibleone.Consistentwiththis,Schreijet

al.(2008)foundaresponsecompatibilityeffect.

Folk et al. (2009) however, have argued that this response compatibility effect

canalsobeexplainedbyparallelprocessingofthetargetandthedistractor.Insupport

of thisargument, theyconductedanexperiment inwhichparticipantswerepresented

withadisplaywithtwobox‐shapedplaceholdersontheleftandrightsideoffixation,in

whichtwocharactersappeared.Oneofthesecharacterswasaredtarget;theotherwas

a white distractor which could either be compatible or incompatible with the target.

Priortothetargetdisplay,oneofthepositionswas indicatedbyanuninformativered

cue.Theyfoundthatevenwhenthetargetwascorrectlycued,andthusattentionshould

befocusedonthetargetlocation,thecompatibilityofthedistractorstillaffectedRTs–

despitethefact,asarguedbyFolketal.,thatthisdistractordidnotappearasanabrupt

new onset. Since participants had no reason whatsoever to attend to the irrelevant

character when the cue was valid, but nonetheless its identity was registered, the

conclusion was that both characters were processed in parallel, contrary to what a

spatialattentionalcaptureaccountwouldpredict.

Note that this explanation assumes that filtering is not always perfect. If the

distractor is indeed processed in parallelwith the target to the extent that it directly

interfereswiththeresponsetothat targetthenthismeansthat thedistractorwasnot

filtered out successfully. If filtering were successful, there would be no interference

(whatwouldotherwisebethepurposeoffiltering).Butjustlikefilteringmaynotalways

beperfect,participantsmayalsonotalwaysperformperfectlyinattendingtothecue.In

otherwords,attentionmaynotalwaysbeperfectlyfocusedonthetargetasassumedby

Folketal.(2009)intheirexperiment.Observersmayoccasionallyaccidentallyattendto

thedistractor,alsobecausewhenitappeareditshowedasimilardynamicchangeasthe

target. The two stimulimight even group on the basis of such commondynamics. All

suchfactorsmightcontributetoaresponsecompatibilityeffect.

ATTENTIONALCAPTUREBYABRUPTONSETSINDEPENDENTOFACSII

134

Additivity

Note that just as in Schreij et al. (2008), we again found that the contingent cueing

effectsandthestandardonsetdistractoreffectwereadditive.Folketal.(2009)argued

thattheadditivityoftheonsetdistractoreffectsandthespatialcueingeffectsmeantthat

they could not both operate on the same level of spatial attention. If we accept that

contingent cueing affects spatial orienting, then onset capture cannot do so too.

However,we have arguments against this claim. It is conceivable that activation at a

cuedlocationishigherandmoresustainedovertime,becausethecuecontainedatask

relevantfeature.Forthisreason,attentionmight ‘snapback’tothecuedlocation,after

theabruptonset in the subsequent targetdisplaywasbrieflyable to attract attention

away fromthere.Theshortexcursionofattentioncausesanadditiveeffect.Folketal.

argue against this “rubber band” explanation on the ground that the cue has already

disappearedafterthetargetdisplayandonsetarepresentedandthusshouldnolonger

beabletoattractattention.Ifanything,attentionshouldberepelledbytheoldlocation

duetothemechanismknownasinhibitionofreturn(Posner&Cohen,1984).

We however believe that it would not be the first time that an already

disappearedstimulus still exerts considerableeffects in thecognitive system.Forone,

the(red)cueisnotmaskedandsoanycue‐relatedactivityisexpectedtoautomatically

lingerforawhile.Moreover,thisactivityislikelytobemaintainedorevenstrengthened

bymeritofitbeingrelevanttotheobserver(whoafterallislookingforsomethingred).

Inhibitionofreturn(IOR)isthenquiteunlikelybecausea)thecueisconsideredrelevant

by the system (IOR is found to be weak under these conditions, Pratt, Sekuler, &

McAuliffe,2001)andb)thetimebetweencueandtargetdisplayisonly150ms,whichis

typicallytooshorttogenerateIOR(Posner&Cohen,1984).

Furthermore, the cue may already have triggered higher order processes

involvingworkingmemoryandnonspecificresponsepreparation,processesthatarenot

easilydisengagedorwipedoutbythepresentationoftheonsetdistractorandthatmay

demand that resources return to the original location. In fact, Godijn and Theeuwes

(2002)conductedaneye‐movementstudy thatdirectlysupports the ideaof sustained

activation for locations of interest in the visual field, even when the stimulus has

disappeared. Participants searched for a color singleton in a circular array of disks,

while eye movements were recorded. On some of the trials, an irrelevant onset

distractor appeared which often captured the participants’ gaze. Important for the

CHAPTER6

135

present discussion, during the eyemovement to the onset distractor, the target color

singleton had moved to another location. Nevertheless, on 82% of the trials, the

participants’nexteyemovementwas towards theold target location,not the(bynow

moresalient)newtargetlocation.

Evenifweacceptthattheremustbetwodifferentstagesinvolved,canonereally

claimthatcontingentcueingeffectsonlyreflectspatialcapture,andnootherprocesses?

Forexample,thedisengagementtimesfrominvalidcuesasfoundbyFolketal.(1992)

areofamuchgreatermagnitudethantheonesusuallyfoundforitemsthatareassumed

toexogenouslyhavecapturedattention(Theeuwes,etal.,2000).Ashasbeenarguedby

Theeuwes et al. (2000), top‐down effects on attention such as those found in the

contingentcaptureparadigmmayatleastpartlyinvolvedisengagementand/ordecision

mechanisms, rather than just initial orienting. Such effects may well turn out to be

considered additive with the spatial capture effects caused by an abrupt onset, thus

reversingtheargument.

Conclusion

It is clear that many questions remain about the exact mechanisms of attentional

capture, and that more sophisticated paradigms as well as better definitions are

necessary.Whatwehavearguedhereisthatabruptonsetssummonattention,despite

observersemployinganattentionalsetforacertaincolor.Wedonotdenyarolefortop‐

downinfluencesonattentionalcapture,buthereweshowagainthatsomestimuliare,to

acertainextent,immunetothistop‐downset.

Acknowledgements

ThisworkwassupportedbyVIDIgrant452‐06‐007fromtheNetherlandsOrganization

forScientificResearch(NWO)grantedtoCNLO.Wewould liketo thankChipFolk, Jim

BrockmoleandDominiqueLamyfortheirconstructivereviewsandsuggestions.

Chapter 7 Abrupt Irrelevant onsets cause

inhibition of return regardless of attentional set

Schreij, D., Theeuwes, J. & Olivers C.N.L (2010) Abrupt Irrelevant onsets cause inhibition of return regardless of attentional set

Attention, Perception & Psychophysics 72(7), 1725-1729

IOR FOR IRRELEVANT ONSETS REGARDLESS OF ACS

138

Abstract

It is disputed if onsets capture spatial attention either in a purely stimulus-driven

fashion, or only when they are contingent on one’s attentional set. According to the

latter assumption, interference from irrelevant onsets may result from non-spatial

filtering costs. In the current study we used Inhibition of Return (IOR) as a marker for

spatial attention. IOR mainly occurs for locations attention has visited before.

Participants searched for a red object among white objects. An attentional set for

redness was demonstrated by a spatial validity effect of red cues on response times.

However, a stronger validity effect was found for irrelevant white onsets, as they slowed

responses when being a distractor, but speeded them when being a target. Most

importantly, this onset benefit for targets turned into a deficit at longer SOAs, indicating

IOR. We conclude that onset distractors capture spatial attention regardless of the

observer’s attentional set.

CHAPTER 7

139

Introduction

There is ongoing debate about whether abrupt visual onsets automatically capture

attention or not (Folk, et al., 1992; Folk, et al., 2009; Schreij, et al., 2008; Yantis &

Jonides, 1984). In a central study, Folk et al. (1992) provided evidence that capture by

abrupt onsets is contingent on the observer’s top-down attentional set. In their

paradigm, participants responded to a target character appearing in one of four possible

boxes positioned at equal distances from fixation. A spatial cue (four small dots

surrounding a box) was presented 150 ms before the target display. This cue was

uninformative, only coinciding with the target location at chance level. The target could

either consist of a single white element (onset type) or of a red element among white

elements (color type). Despite its irrelevance, Folk et al. found an effect of the cue, but

only when it was of the same type as the target. When participants searched for onset

targets, only onset cues drew attention, whereas color cues did not. Vice versa, when

participants searched for color targets, color cues captured attention whereas onsets did

not. Folk et al. (1992) concluded that in order for an object to capture attention, it has to

possess a feature that participants are actively looking for. In other words, attentional

capture is under top-down control.

However, in an adaptation of the classic Folk et al. (1992) paradigm, Schreij et al.

(2008) recently found evidence consistent with automatic, stimulus-driven capture by

abrupt onsets. In their version, participants were always instructed to look for a red

target, which was always preceded by a red cue. As in Folk et al., Schreij et al. found a

spatial validity effect of the cue, demonstrating that participants had adopted an

attentional set for color. The crucial manipulation was the presence of an abrupt onset

distractor simultaneous with the target display. If capture by abrupt onsets entirely

depends on the observer’s attentional set, then no interference from this distractor

should be expected. This turned out not to be the case: The presence of an abrupt onset

caused search times to increase, indicating stimulus-driven attentional capture by

abrupt onsets. To save the idea that capture by abrupt onsets is under top-down control,

Folk, Remington, and Wu (2009) proposed an alternative explanation for the Schreij et

al. (2008) results. The onset-related costs could be due to non-spatial filtering

operations (Folk & Remington, 1998; though see Schreij, Theeuwes, & Olivers, 2010).

Non-spatial filtering is a mechanism that was first described by Kahneman, Treisman


140

and Burkell (1983), who found that a response to a target was delayed when other

objects appeared concurrently with the target, even though the distinction between

targets and distractors was clear. They reasoned that these simultaneously appearing

distractors compete for attention and need to be filtered out. On this view, these objects

do not attract spatial attention themselves (i.e. there is no capture), but nevertheless

delay the moment at which attentional focus can be deployed to the target location.

A mechanism that could be used to determine more precisely whether or not

irrelevant onsets capture spatial attention is Inhibition of Return (IOR). IOR is

operationalized as the slowing of responses to previously attended locations (i.e. more

than about 300 ms ago), compared to previously unattended locations (Posner & Cohen,

1984). It is assumed that when attention is drawn to a location in space, and is

subsequently disengaged from that location, an inhibitory mechanism is implemented,

slowing the return of attention (see Klein, 2000 for a review). Thus, an important aspect

of IOR is that it is assumed to be spatial in nature (although it has also been shown that

IOR can be object-based, see Tipper, et al., 1994). The purpose of the present study was

therefore to determine whether the irrelevant onsets as used by Schreij et al (2008)

indeed cause IOR, while at the same time participants have an attentional set for the

color red. If so, this would provide strong evidence that onsets capture attention in a

spatially specific manner, despite an attentional set for a different property. On the other

hand, if any of the previously found onset-related costs are due to non-spatial filtering,

then no IOR would be expected. For this purpose, the colored search target could

occasionally (at less than chance level) appear inside the irrelevant abrupt onset, after

either a short or a long SOA. On the basis of the previous IOR literature (Posner & Cohen,

1984), we predicted that the abrupt onset would cause facilitation of target

identification at the short SOA, relative to a no onset condition, whereas at the long SOA

it would cause inhibition. No such IOR is expected under a filtering account, since it

assumes attention has never visited the onset location in the first place.

METHOD

Participants

Twenty students aged 18 to 27 years (average 20.3) participated. None reported color

blindness, or any other visual deficit.

CHAPTER 7

141

Apparatus

The experiment was run on a PC with a 19” , 120 Hz CRT at 1024 x 768 pixel resolution,

viewed from approximately 75 cm in a dimly lit, soundproof room. Stimulus

presentation and response recording were done in E-prime 1.2 (Psychological Software

Tools, 2003).

Stimuli

All backgrounds were black. First a bright white (CIE(0.286, 0.311), 59,50 cd/m2)

fixation cross at the center of the screen was surrounded by four light gray placeholder

boxes (CIE(0.285, 0.306), luminance 28.28 cd/m2 ; dimensions: 3.4o visual angle) . These

were positioned above, below, to the left and to the right of the fixation cross, at a

distance of 6.6o visual angle. In the cue display four sets of four dots (0.5o visual angle )

surrounded the boxes. Most sets were bright white (CIE(0.286, 0.311), 59,50 cd/m2),

except for the cued location, which was indicated by a red set (CIE(0.621, 0.345), 10.43

cd/m2). Each box contained a bright white masking figure consisting of overlapping

Figure 23: An illustration of a trial where the target appeared inside the onset. It is important to note that this occurred at less than chance level, and the target appeared inside one of the four already present boxes in the majority of cases. First a fixation display was presented of which the fixation cross was flashed for 50 ms to alert participants about the start of the trial. Then a fixation display was presented again for 1000 ms, followed by a color cue which was flashed for 50 ms. Then the fixation display was presented again for 100 ms. Depending on the block type, the target either directly appeared inside the onset element, or the onset appeared during the fixation display after which the target was revealed inside the onset 900 ms later. Black lines in reality were white against a black background, and the grey items were red.


142

“X”,”|” and “=” symbols (Myriad Roman). In the target display, the irrelevant line

segments were removed, revealing an “X” or an “=”. Simultaneously, the color of the

target character turned from white to red. There were always two ‘X’s and two ‘=’ s

present. In the onset condition an extra light grey box was added to the display.

containing either a placeholder, distractor or target character depending on the trials

conditions.

Design and procedure

Figure 23 shows the experimental procedure. The experiment took around 45 minutes.

Oral instructions were given to familiarize participants with the task. Participants were

instructed to look for a red X or = inside one of the placeholders and press “X” or “M”

correspondingly. They were told to keep an index finger on each response button and to

not move their eyes from fixation during a trial. Initially the fixation display was

presented for 500 ms, after which the fixation cross blinked for 100 ms, to indicate the

start of a trial. 1000 ms after this event, the red cue appeared for 50 ms. Following a

variable SOA, the search display was presented until response (with a maximum of

2,000 ms). When the given response was incorrect, the experiment paused for 5 seconds

and a corresponding sound was played. The onset, when present, always appeared 150

ms after the cue display, but its contents were only revealed simultaneously with the

target and remained masked until that moment. Between blocks, participants had to

take a mandatory break of 30 seconds.

There were three main factors, both varied within subjects: Onset Type (no onset,

onset distractor, onset target), Cue Validity (valid or invalid) and SOA (short or long).

When short, the Cue-to-Target SOA was 150 ms and the Onset-to-Target SOA was 0 ms;

In the long SOA condition these were 1050 ms and 900 ms respectively (see Figure 23

for full timeline). The red cue prior to the target was uninformative about the location of

the upcoming target. When the cue was valid, its location corresponded with the target’s

(25% of the cases). The onset only appeared in 50% of the trials randomly at one of the

four possible locations between two placeholders. In the onset distractor condition, it

contained a distractor character and in the onset target condition, it contained the target.

Note that in the onset target condition, the cue could only be invalid, since the empty

location in which the onset target appeared could not be cued. Cue Validity and Onset

Type were randomly mixed within 8 blocks of 80 trials each, preceded by two practice

CHAPTER 7

143

blocks. Only 6 of the 80 trials (7.5%) per block contained an onset target. The onset was

a distractor on 34 trials, and there was no onset on the remaining 40 trials. SOA was

counterbalanced across subjects: half of the subjects performed the short SOA condition

first and the long SOA in the second half of the experiment; for the other subjects this

order was switched.

Results

Incorrect responses (4.7% of the trials), as well as responses with RTs below and above

2.5 SD from the mean (another 2.5%) were removed from the dataset. The mean of the

remaining RTs and the error percentages are depicted in Figure 24.

First, an ANOVA was performed with SOA (short, long), Onset Type (no-onset,

onset distractor) and Cue Validity (valid, invalid) as factors. Note that the onset target

level was omitted in this particular analysis, because it could not be fully crossed with

Cue Validity (as onset targets could only be combined with invalid cues, see Method

section). This analysis revealed that Onset Type interacted with SOA, F(1,19) = 10.57, p

A. Short SOA B. Long SOA

Figure 24: Response times and error rates for the different onset distractor conditions with an invalidly or validly cued target. A) Data for the short SOA (150 ms) between cue and target onset. B) Data for the long SOA (1050 ms)


144

< .05. Onset interference was larger in the short SOA than in the long SOA condition.

There was also an interaction between Cue Validity and SOA, F(1,19) = 20.767, p < .001,

indicating that the effect of the red cue diminished with a longer SOA. There was no

three-way interaction between these factors (p > .2). A separate ANOVA for each SOA

condition, with Cue Validity (valid, invalid) and Onset Presence (no onset, onset

distractor) as factors revealed a significant main effect of Cue Validity in the short SOA

condition, F(1,19) = 35.44, p < .001, as participants were slower after an invalid cue than

after a valid cue. The presence of an onset distractor slowed responses too, Onset Type,

F(1,19) = 29.65 , p < .001. There was no interaction between Onset Type and Cue

Validity, F(1,19) < 1.0, p > .5, suggesting additive effects. In the long SOA condition, the

validity effect of the cue completely disappeared, F(1,19) = 0.62, p = .44. The cost

associated with the onset distractor was also reduced, to the extent that it was no longer

significant, F(1,19) = 2.635, p = .146. There was no interaction between these factors

either, F(1,19) = 2.293, p = .17. An analysis on the error rates revealed no significant

effects.

Second, we assessed the effects of onset targets for invalidly cued trials. An

ANOVA with Onset Type (no-onset, onset distractor, onset target) and SOA (short, long)

as factors revealed a significant interaction, F(2,38) = 25.40, p < .001, reflecting the fact

that, compared to the no onset condition, onset targets led to faster responses at the

short SOA, but to slower responses that the long SOA. This was confirmed by separate

analyses. The short SOA, there was a significant benefit for onset target trials relative to

no onset trials and onset distractor trials, t(19) = 4.75, p < .001 and t(19) = 5.69, p <

.001, respectively. RTs on onset distractor trials were significantly slower than on no-

onset trials, t(19) = 4.55, p < .001. In the long SOA condition, RTs for onset targets were

significantly slower than for no-onset trials, t(19) = -2.61, p < .05. There was no

significant difference between response times in onset target and distractor conditions,

t(19) = 1.339, p = 0.20. There was a significant difference between the onset distractor

and no-onset conditions, t(19) = -1.34, p < .05. Analyses on the error pattern revealed no

significant effects or speed/accuracy trade-offs.

Discussion

The results of this experiment replicate Schreij et al. (2008) in that onset distractors

presented together with color targets led to interference, even though participants were

CHAPTER 7

145

looking for color. The experiment also shows that when the onset happens to coincide

with the target location, detection is speeded. This in itself suggests that an abrupt onset

is preferentially processed, rather than filtered out. The filtering operation’s main goal is

to prevent an irrelevant onset from acquiring attention and therefore one would not

expect an irrelevant onset to receive priority in processing (also see Schreij, et al., 2010).

More importantly, we show that this RT benefit turns into a cost when the interval

between the onset and the target at the same location is prolonged, thus revealing the

typical characteristics of IOR. Our data also show that the color cue loses its capacity to

drive attention with a long SOA. This was to be expected, because participants have

ample time in this condition to disengage their attention from the cue, which is known to

be uninformative. In addition, all responses in the long SOA condition are as fast as for a

validly cued target in the short SOA condition. This pattern of overall decreasing RTs

with increasing SOA is one that is found in most IOR studies (Klein, 2000).

Finding IOR at the onset location is important for two reasons. First, the

occurrence of IOR is a strong indicator that spatial attention was directed to the onset

location – something which cannot be explained by a mere filtering operation. Second,

IOR is thought to mainly follow reflexive shifts of attention (Posner & Cohen, 1984;

Rafal, Calabresi, Brennan, & Sciolto, 1989), and thus the current results support the idea

that onsets drive attention automatically, in a stimulus-driven fashion. Even though it is

generally assumed that IOR only occurs when attention is captured reflexively (for an

overview see Klein, 2000) recently a few exceptions were reported For example, Weger,

Abrams, Law, and Pratt (2008), as well as Berlucchi, Chelazzi, and Tassinari (2000),

showed that t it is possible to obtain IOR-like effects under certain conditions of

endogenous orienting (also see Berlucchi, 2006).

Note that at the long SOA, the onset distractor still inflicted RT costs when the cue

was invalid. Thus, while we found evidence for onset targets to be inhibited, the onset

distractor still caused an RT cost. One might explain these remaining costs as the result

of a filtering operation still working at the long SOA. However, in their original

conception of filtering, Kahneman et al. (1983) have argued that filtering costs are tied

to perceptual events like the sudden appearance of an object, rather than to the mere

presence of an object. They showed that filtering costs disappeared when objects had

been present for a while, as was the case here in the long SOA condition. Another

possibility is that onset distractors are suppressed, and that this suppression is


146

accompanied by a surrounding gradient of inhibition. Bennett and Pratt (2001)

demonstrated that IOR is indeed not constrained to the inhibited location, but spreads

out to the surrounding area. This inhibitory annulus then suppresses no-onset targets

appearing nearby. This would lead to slowed target-related responses, especially when

attention is not cued towards the target.

The occurrence of IOR in the Folk et al. (1992) contingent cueing paradigm has

been demonstrated before in studies of Gibson and Amelio (2000) and Pratt, Sekuler

and McAuliffe (2001). In contrast to the present study, these studies looked at IOR

towards the cue, rather than towards an additional distractor, by prolonging the usual

SOA of around 150 ms between the presentation of the cue and the target displays to an

SOA that would permit IOR. Both studies showed that an onset cue could evoke IOR, but

only when participants were also looking for an onset target, not when looking for a

color target – thus providing support for contingent capture rather than stimulus-driven

capture. However, a later study by Pratt and McAuliffe (2002) demonstrated that the

onset cue can elicit IOR even when the target is defined by color. Pratt and McAuliffe

(2002) argued that the absence of IOR in their earlier study was due to outliers in the

data set, and that the absence of IOR in the Gibson and Amelio (2000) study may have

been due to the peculiarities of their displays. For example, Gibson and Amelio used a

short brightening of the placeholder box as an onset cue instead of the usual four

surrounding dots. In the presence of an attentional control setting for a color-defining

target, perhaps such a brightening of an existing object may not be a sufficiently strong

stimulus to capture attention. There is substantial evidence that the effectiveness of

luminance transients largely depends on whether a new perceptual object is being

created (Enns, et al., 2001). In the present study, the abrupt onset stimulus was always a

new object, and, together with the Pratt and McAuliffe (2002) study, it now

unequivocally shows that IOR – and thus involuntary attentional orienting – towards an

onset is possible even when observers look for color. Our findings further extend those

of Pratt and McAuliffe (2002) by demonstrating capture by onsets simultaneously with

(i.e. occurring on the very same trials as) the presumed capture by the color cues, as is

demonstrated through the cue validity effect. This indicates that contingent and

stimulus-driven capture do not need to be mutually exclusive. Thus, unlike what Folk et

al. (2009) argue, it is not necessary to assume an attentional orienting mechanism for

CHAPTER 7

147

the one effect, and a completely different filtering mechanism for the other. The current

results cannot be explained by filtering, since filtering would not predict IOR.

This is not to say that contingent capture and stimulus-driven capture reflect one

and the same mechanism. Note that in the Gibson and Amelio, the Pratt and McAuliffe, as

well as in the present study, a color cue never elicited IOR, even when participants had

adopted an attentional set for color. This raises strong doubts if contingent capture

really is a form of capture, often receiving the additional labels of being automatic and

exogenous in nature (Folk & Remington, 1998). Instead, one could argue that when

observers are instructed to look for the red object that will appear shortly, they will do

exactly that, and take the occasional selection of the near simultaneous cue for granted

(see also Belopolsky, et al., 2010; Pratt, et al., 2001). In other words, attention would be

endogenously driven. The fact that there was no IOR for the cued locations fits with a

more endogenous source of attention (Klein, 2000; Posner & Cohen, 1984). This is not to

say that colors cannot capture attention in an exogenous, stimulus-driven fashion.

Theeuwes and Godijn (2002) and Folk and Remington (2006) have shown IOR to a color

singleton when this color singleton is not relevant to the observer.

In conclusion, we have shown that even when observers have an attentional set

for color, irrelevant onsets cause IOR. Since IOR can be taken as a measure of stimulus-

driven allocation of spatial attention, we conclude that onsets capture spatial attention

in an automatic fashion regardless of attentional set.

Summary in Dutch Nederlandse samenvatting

SUMMARY IN DUTCH

150

Aandacht voor verschijnende objecten

De wereld om ons heen bevat een immens aantal objecten. Om een coherent beeld te

houden van de omgeving, onderhoudt ons brein representaties van de objecten die het

waarneemt onder de aanname dat deze objecten continue zijn in ruimte en tijd. Een

object zal doorgaans niet ergens plots verdwijnen en op een geheel andere plek weer

tevoorschijn komen, maar moet zich gradueel van het ene naar het andere punt

verplaatsen. Deze eigenschap van spatietemporele continuïteit stelt ons in staat om ons

bewust te blijven van objecten die we voor korte momenten niet kunnen waarnemen,

omdat we bijvoorbeeld simpelweg in een andere richting kijken en een bepaald object

niet meer in ons visueel veld valt, of wanneer een bewegend object tijdelijk achter een

ander object verdwijnt en zo aan het zicht ontnomen wordt. Dit proefschrift onderzoekt

hoe deze objectrepresentaties de manier waarop we onze aandacht op zo’n object

richten beïnvloeden.

In het eerste deel bestuderen we of de kennis die iemand heeft opgedaan tijdens

een eerste waarneming van een object beïnvloedt hoe hij z’n aandacht toewijst aan

ditzelfde object wanneer hij het naderhand opnieuw tegenkomt. Met ditzelfde bedoelen

we overigens dat het object als één en dezelfde wordt gezien omdat het continue is in

ruimte en tijd; het heeft dus geen betrekking op identiekheid qua uiterlijke kenmerken.

Denk bijvoorbeeld aan een situatie waarin we een schotel waarnemen met allerlei

hapjes, en we vinden kaasstengels aan de linkerbovenkant van deze schotel, zijn we dan

ook weer geneigd om de kaasstengels op deze zelfde plek te zoeken wanneer we

dezelfde schotel een tijdje later weer zien? En hoe gaan we dan om met een schotel die

er precies hetzelfde uitziet, maar waarvan we weten dat het een andere, nieuwe schotel

is? Met andere woorden, bewaren wij zogenaamde “aandachtsinstellingen” bij de

representatie van een object en beïnvloeden deze instellingen vervolgens ons

zoekgedrag met betrekking tot dit object? Verder vragen we of deze instellingen alleen

bewaard worden aan de hand van de spatietemporele eigenschappen van een een

object, of ook aan de hand van het uiterlijk.

In het onderzoek beschreven in Hoofdstuk 2 lieten we mensen zoeken naar een

specifieke doelvorm (ook wel target genoemd) dat gepresenteerd werd ergens binnen

een groter object. We bestudeerden of de aandachtsinstelling die mensen aannemen

voor de locatie van het target binnen dit object ervoor zorgen dat ze onbewust het target

NEDERLANDSE SAMENVATTING

151

op dezelfde plaats verwachten te vinden wanneer ze naderhand weer hetzelfde object te

zien krijgen. Indien dit het geval is, kan men snellere reactietijden verwachten wanneer

de target ook inderdaad weer op z’n oude locatie te vinden is. In het experiment waren

er twee identiek uitziende objecten die fungeerden als displays en grotendeels

verborgen waren achter twee van de muren die zich aan elke rand van het scherm

bevonden. Gedurende iedere meting of ‘trial’ schoof een van de twee displays naar het

midden van het scherm en bevatte een verzameling vormen waartussen de

proefpersoon het target moest zoeken. Wanneer hij deze gevonden had schoof het

display weer terug achter een van de muren en begon de volgende trial. We vonden

inderdaad dat proefpersonen sneller reageerden op het target, wanneer deze zich op

dezelfde plek in het zoekveld bevond als in de trial ervoor, maar belangrijker was dat ze

nog sneller waren wanneer het zoekveld ook weer werd gepresenteerd op hetzelfde

object als de vorige trial, in vergelijking met presentatie in het andere object (dat verder

dus niet te onderscheiden was qua uiterlijk). Dit duidt er dus op dat mensen inderdaad

aandachtsinstellingen verbinden aan de spatietemporele representatie van een object en

dat deze instellingen consequent zoekgedrag m.b.t. dit object beïnvloed.

Hoofdstuk 3 onderzocht welke spatietemporele factor belangrijker is om een

object als hetzelfde te beschouwen: continuïteit in ruimte of continuïteit in tijd. Wanneer

een zoekdisplay achter een voorwerp bewoog en aan de andere kant weer tevoorschijn

kwam op de plaats waar men het zou verwachten, dan suggereerde het

reactietijdpatroon als gevolg van een herhaling of verandering van de targetlocatie dat

proefpersonen het verschenen display als dezelfde zagen als degene die zojuist achter

het verhullende voorwerp verdween. Wanneer het display vanachter een onverwacht

deel van de muur verscheen, dan was een dergelijk patroon nagenoeg afwezig. Het

maakte niet uit voor de reactietijden of het display een moment achter het voorwerp stil

bleef staan of in een vloeiende beweging naar z’n eindpunt bewoog. Dit duidt erop dat

objectcontinuïteit meer afhangt van continuïteit in de ruimte dan in de tijd.

Hoofdstuk 4 toont aan dat naast aandachtsinstellingen voor de locatie van een

target er ook instellingen bewaard blijven voor diens uiterlijke kenmerken zoals vorm of

kleur (ook wel features genoemd). Wanneer target features veranderen t.o.v. de trial

ervoor en het target in hetzelfde object verschijnt, dan zijn responstijden hoger dan

wanneer het veranderde target in een ander object verschijnt. Dit duidt erop dat target

feature informatie bewaard blijft en dat zoekprestaties vervolgens worden aangetast

SUMMARY IN DUTCH

152

wanneer de features van de target niet meer overeenkomen met degene die in de

representatie waren opgeslagen. Verder onderzochten we of het uiterlijk van het

displayobject invloed heeft op de handhaving van aandachtsinstellingen die aan een

representatie gebonden zijn. We toonden de twee aanwezige zoekdisplays ieder in het

schermgebied van een mobiel apparaat, zoals een iPod of mobiele telefoon. Dit frame

kon tussen trials veranderen wanneer het zoekdisplay verborgen was achter een van de

muren aan weerszijden van het scherm. Het zoekdisplay kon op die manier met een

ander frame verschijnen als toen het verdween. We vonden dat een verandering in of

herhaling van het frame van het displayobject geen invloed had op de handhaving en

hergebruik van aandachtsinstellingen. Deze bleken dus sterker verbonden aan de

spatietemporele representatie van het object dan aan diens uiterlijk.

Het tweede deel van dit proefschrift gaat in op een controverse die onderzoekers

van aandacht al een geruime tijd bezig houdt. Het is geregeld aangetoond dat sommige

objecten of gebeurtenissen de aandacht van een toeschouwer kunnen trekken buiten

zijn intenties om, wat ook wel “attentional capture” wordt genoemd. Enerzijds bestaat er

het standpunt dat een object alleen de aandacht kan vangen wanneer het een eigenschap

deelt met hetgeen waar de toeschouwer eigenlijk naar op zoek is. Als iemand

bijvoorbeeld op zoek is naar aardbeien, dan kan hij hun rode kleur gebruiken om ze

makkelijker te kunnen vinden. De toeschouwer heeft dan zogezegd een

aandachtsinstelling (of attentional set) voor de kleur rood. In dit geval is echter de kans

ook groot dat de toeschouwer onïntentioneel zijn aandacht op tomaten zal richten

gezien deze net als aardbeien een rode kleur hebben. Deze vorm van attentional capture

wordt contingent capture genoemd. Anderzijds zijn er studies die aangetoond hebben

dat een uit het niets verschijnend object (of onset) altijd de aandacht van een

toeschouwer vangt, ongeacht wat zijn attention set is. Deze studies laten zien dat een

onset altijd prioriteit krijgt tijdens een zoekproces.

Onze veronderstelling was dat deze tegenstrijdige bevindingen ten grondslag

zouden kunnen liggen aan verschillen in de ontwerpen van experimenten die gebruikt

zijn om beide standpunten aan te tonen. Bij paradigma’s die aantoonden dat onsets altijd

prioriteit krijgen in aandacht, werden deze vaak tegelijkertijd met het target

gepresenteerd. In de paradigma´s die voornamelijk contingent capture aantoonden

verscheen een onset echter vaak een moment voor de presentatie van de target,

waardoor een potentieel capture effect van de onset al uitgewerkt kon zijn op het

NEDERLANDSE SAMENVATTING

153

moment dat de target verscheen. Om deze discrepantie te overbruggen, namen wij een

typisch paradigma dat vaak gebruikt is om contingent capture aan te tonen over en

presenteerden de onset daarin gelijktijdig met het target.

In het onderzoek beschreven in Hoofdstuk 5 onderwierpen wij proefpersonen

aan een zoektaak waarin ze doelgericht moesten zoeken naar een rode letter (de color

target) die in één van vier aanwezige vakjes op het scherm kon verschijnen.

Ondertussen kon op een lege locatie uit het niets een nieuwe letter verschijnen die door

zijn witte kleur compleet irrelevant was voor de taak (de onset distractor). Kort voordat

de color target en onset distractor beiden verschenen, werd een van de potentiële target

locaties kort omringd door een cue bestaande uit vier rode balletjes. Omdat de cue dus

dezelfde kleur bezat als de target, konden proefpersonen deze cue vrijwel niet negeren,

ondanks dat ze wisten dat de cue- en targetpositie slechts op kansniveau samenvielen,

en reageerden ze sneller als de target dan ook toevalligerwijs op de gecuede locatie

verscheen. Deze cues waren dus van belang omdat deze aantoonden dat proefpersonen

daadwerkelijk op zoek waren naar de kleur rood en deze hun attention set vormde. Wij

vonden dat de onset distractor ondanks dat hij vanwege zijn witte kleur geen deel

uitmaakte van de attention set toch de aandacht ving en zodoende de reactietijden op de

target beïnvloedde, onafhankelijk van het effect van de cue.

Verder controleerden wij of aandacht ook echt naar de locatie van de onset

distractor ging en de verhoging in reactietijd niet te wijten was aan factoren die geen

spatiële aandacht betroffen. Men neemt over het algemeen aan dat hetgeen waar wij ons

aandacht op richten tot een dieper niveau (of niveau van betekenis) verwerkt wordt,

wat dan ook zou moeten gelden voor de letter op de onsetlocatie. In dit geval kan men

een grotere interferentie verwachten door de onset distractor, wanneer diens letter

verschilt met die van de color target dan wanneer beide letters identiek zijn. Wij vonden

inderdaad dat een verschil in letters hogere reactietijden veroorzaakte dan bij identieke

letters, hetgeen erop duidt dat aandacht ook werkelijk naar de onset locatie ging.

In Hoofdstuk 6 vonden we dat een distractor die een relevante targeteigenschap

droeg (opnieuw de kleur rood) net als een irrelevante onset distractor een additief effect

vertoont met de cue. Dit duidt erop dat een object of gebeurtenis dat de aandacht vangt,

niet per sé de effecten van een eerder ‘capture event’ hoeft te elimineren. Stel dat dit wel

het geval zou zijn, dan zou aandacht niet meer naar de origineel gecuede locatie terug

moeten gaan nadat de tweede distractor de aandacht ervan ‘weggevangen’ heeft. Echter,

SUMMARY IN DUTCH

154

ook wanneer deze distractor aanwezig was dan waren reactietijden flink sneller

wanneer de target op de locatie verscheen die eerder gecued was. In een tweede

experiment toonde we aan dat er wel degelijk situaties mogelijk zijn waarin een object

of gebeurtenis dat de aandacht vangt een eerder attentional capture effect teniet kan

doen, maar dat dit aandachtsvangende object een hoge saillantie moet hebben en

tegelijkertijd taakrelevant moet zijn om in staat te zijn dit te doen. Tenslotte

demonstreerden we dat de reactietijden voor een color target nog sneller zijn

(vergelijkbaar met die voor een valide gecuede target positie) wanneer deze in de onset

zelf verschijnt, hetgeen verder bewijs vormt dat de onset zelf daadwerkelijk de aandacht

vangt.

Hoofdstuk 7 toont daarnaast aan dat er Inhibition of Return (IOR) optreedt voor

een target die met een vertraging in de onset verschijnt. IOR is een fenomeen dat

aandacht er langer over doet om terug te keren naar een eerder bezochte locatie; in het

bijzonder wanneer de tijd tussen de twee bezoeken meer dan 300 ms bedraagt en het

eerste bezoek plaatsvond omdat de stimulus onvrijwillig de aandacht ving. Door IOR te

vinden voor een target die op de onset positie verschijnt tonen we aan dat aandacht de

onset locatie bezocht heeft op het moment dat hij verscheen en dat dit gebeurde buiten

de intentie van de proefpersoon.

In het licht van onze bevindingen komen we tot de conclusie dat men

aandachtsinstellingen bewaart bij representaties die ze van waargenomen objecten

onderhouden. Deze aandachtsinstellingen bepalen hoe we onze aandacht toewijzen aan

interne eigenschappen van die objecten als we deze later opnieuw aantreffen. We

gebruiken spatietemporele continuïteit als voornaamste factor om te bepalen of een

object dat we waarnemen hetzelfde is als voorheen en laten dit verder weinig afhangen

van continuïteit in de uiterlijke kenmerken van het object. Verder tonen we aan dat

objecten die uit het niets verschijnen prioriteit krijgen bij aandachtstoewijzing, zelfs als

men doelgericht op zoek is naar eigenschappen die het verschijnende object niet bezit.

REFERENCES

155

References

Abrams, R. A., Davoli, C. C., & Suszko, J. W. (2007). New objects can capture attention without a unique luminance transient. Psychonomic Bulletin & Review, 14(2), 338-343.

Bacon, W. F., & Egeth, H. E. (1994). Overriding Stimulus-Driven Attentional Capture. Perception & Psychophysics, 55(5), 485-496.

Becker, S. I. (2007). Irrelevant singletons in pop-out search: Attentional capture or filtering costs? Journal of Experimental Psychology-Human Perception and Performance, 33(4), 764-787.

Belopolsky, A. V., Schreij, D., & Theeuwes, J. (2010). What is top-down about contingent capture? Attention, Perception & Psychophysics, 72(2), 326-341.

Belopolsky, A. V., & Theeuwes, J. (2010). No capture outside the attentional window. Vision Research, 50(23), 2543-2550.

Belopolsky, A. V., Theeuwes, J., & Kramer, A. F. (2005). Prioritization by transients in visual search. Psychonomic Bulletin & Review, 12(1), 93-99.

Belopolsky, A. V., Zwaan, L., Theeuwes, J., & Kramer, A. F. (2007). The size of an attentional window modulates attentional capture by color singletons. Psychonomic Bulletin & Review, 14(5), 934-938.

Bennett, P. J., & Pratt, J. (2001). The spatial distribution of inhibition of return. Psychological Science, 12(1), 76-80.

Berlucchi, G. (2006). Inhibition of return: A phenomenon in search of a mechanism and a better name. Cognitive Neuropsychology, 23(7), 1065-1074.

Berlucchi, G., Chelazzi, L., & Tassinari, G. (2000). Volitional covert orienting to a peripheral cue does not suppress cue-induced inhibition of return. Journal of Cognitive Neuroscience, 12(4), 648-663.

Boot, W. R., Brockmole, J. R., & Simons, D. J. (2005). Attention capture is modulated in dual-task situations. Psychonomic Bulletin & Review, 12(4), 662-668.

Bower, T. G. R. (1967). Development of Object-Permanence - Some Studies of Existence Constancy. Perception & Psychophysics, 2(9), 411-418.

Bower, T. G. R., Broughto.J, & Moore, M. K. (1971). Development of Object Concept as Manifested in Changes in Tracking Behavior of Infants between 7 and 20 Weeks of Age. Journal of Experimental Child Psychology, 11(2), 182-&.

Breitmeyer, B. G., & Ganz, L. (1976). Implications of Sustained and Transient Channels for Theories of Visual-Pattern Masking, Saccadic Suppression, and Information-Processing. Psychological Review, 83(1), 1-36.

Broadbent, D. E. (1958). Perception and Communication. London: Pergamon Press. Brockmole, J. R., & Henderson, J. M. (2005). Prioritization of new objects in real-world

scenes: Evidence from eye movements. Journal of Experimental Psychology-Human Perception and Performance, 31(5), 857-868.

Burke, L. (1952). On the Tunnel Effect. Quarterly Journal of Experimental Psychology, 4, 121-138.

REFERENCES

156

Burnham, B. P. (2007). Displaywide visual features associated with a search display's appearance can mediate attentional capture. Psychonomic Bulletin & Review, 14(3), 392-422.

Cave, K. R., & Wolfe, J. M. (1990). Modeling the Role of Parallel Processing in Visual-Search. Cognitive Psychology, 22(2), 225-271.

Christ, S. E., & Abrams, R. A. (2006). Abrupt onsets cannot be ignored. Psychonomic Bulletin & Review, 13(5), 875-880.

Christ, S. E., & Abrams, R. A. (2008). The Attentional Influence of New Objects and New Motion. Journal of Vision, 8(3), 1-8.

Chun, M. M. (2000). Contextual cueing of visual attention. Trends in Cognitive Sciences, 4(5), 170-178.

Chun, M. M., & Jiang, Y. H. (1998). Contextual cueing: Implicit learning and memory of visual context guides spatial attention. Cognitive Psychology, 36(1), 28-71.

Desimone, R., & Duncan, J. (1995). Neural Mechanisms of Selective Visual-Attention. Annual Review of Neuroscience, 18, 193-222.

Di Lollo, V., Enns, J. T., & Rensink, R. A. (2000). Competition for consciousness among visual events: The psychophysics of reentrant visual processes. Journal of Experimental Psychology-General, 129(4), 481-507.

Donk, M., & van Zoest, W. (2008). Effects of salience are short-lived. Psychological Science, 19(7), 733-739.

Duncan, J. (1985). Visual search and visual attention. In M. I. Posner & O. S. Marin (Eds.), Attention and performance XI (pp. 85-106). Hillsdale: NJ:Erlbaum.

Egeth, H. E., & Yantis, S. (1997). Visual attention: Control, representation, and time course. Annual Review of Psychology, 48, 269-297.

Egly, R., Driver, J., & Rafal, R. D. (1994). Shifting Visual-Attention between Objects and Locations - Evidence from Normal and Parietal Lesion Subjects. Journal of Experimental Psychology-General, 123(2), 161-177.

Enns, J. T., Austen, E. L., Di Lollo, V., Rauschenberger, R., & Yantis, S. (2001). New objects dominate luminance transients in setting attentional priority. Journal of Experimental Psychology-Human Perception and Performance, 27(6), 1287-1302.

Eriksen, C. W., & Hoffman, J. E. (1972). Temporal and Spatial Characteristics of Selective Encoding from Visual Displays. Perception & Psychophysics, 12(2B), 201-&.

Flombaum, J. I., Kundey, S. M., Santos, L. R., & Scholl, B. J. (2004). Dynamic object Individuation in rhesus macaques - A study of the tunnel effect. Psychological Science, 15(12), 795-800.

Flombaum, J. I., & Scholl, B. J. (2006). A temporal same-object advantage in the tunnel effect: Facilitated change detection for persisting objects. Journal of Experimental Psychology-Human Perception and Performance, 32(4), 840-853.

Flombaum, J. I., Scholl, B. J., & Pylyshyn, Z. W. (2008). Attentional resources in visual tracking through occlusion: The high-beams effect. Cognition, 107(3), 904-931.

Folk, C. L., & Annett, S. (1994). Do Locally Defined Feature Discontinuities Capture Attention. Perception & Psychophysics, 56(3), 277-287.

REFERENCES

157

Folk, C. L., Leber, A. B., & Egeth, H. E. (2002). Made you blink! Contingent attentional capture produces a spatial blink. Perception & Psychophysics, 64(5), 741-753.

Folk, C. L., & Remington, R. (1998). Selectivity in distraction by irrelevant featural singletons: Evidence for two forms of attentional capture. Journal of Experimental Psychology-Human Perception and Performance, 24(3), 847-858.

Folk, C. L., & Remington, R. (1999). Can new objects override attentional control settings? Perception & Psychophysics, 61(4), 727-739.

Folk, C. L., & Remington, R. (2006). Top-down modulation of preattentive processing: Testing the recovery account of contingent capture. Visual Cognition, 14(4-8), 445-465.

Folk, C. L., Remington, R. W., & Johnston, J. C. (1992). Involuntary Covert Orienting Is Contingent on Attentional Control Settings. Journal of Experimental Psychology-Human Perception and Performance, 18(4), 1030-1044.

Folk, C. L., Remington, R. W., & Wright, J. H. (1994). The Structure of Attention Control - Contingent Attentional Capture by Apparent Motion, Abrupt Onset, and Color. Journal of Experimental Psychology-Human Perception and Performance, 20(2), 317-329.

Folk, C. L., Remington, R. W., & Wu, S. C. (2009). Additivity of abrupt onset effects supports nonspatial distraction, not the capture of spatial attention. Attention Perception & Psychophysics, 71(2), 308-313.

Franconeri, S. L., Hollingworth, A., & Simons, D. J. (2005). Do new objects capture attention? Psychological Science, 16(4), 275-281.

Franconeri, S. L., & Simons, D. J. (2003). Moving and looming stimuli capture attention. Perception & Psychophysics, 65(7), 999-1010.

Franconeri, S. L., Simons, D. J., & Junge, J. A. (2004). Searching for stimulus-driven shifts of attention. Psychonomic Bulletin & Review, 11(5), 876-881.

Gellatly, A. (1999). Perception and information processing. Behavioral and Brain Sciences, 22(3), 377-+.

Gellatly, A., Cole, G., & Blurton, A. (1999). Do equiluminant object onsets capture visual attention? Journal of Experimental Psychology-Human Perception and Performance, 25(6), 1609-1624.

Gibson, B. S., & Amelio, J. (2000). Inhibition of return and attentional control settings. Perception & Psychophysics, 62(3), 496-504.

Gibson, B. S., & Kelsey, E. M. (1998). Stimulus-driven attentional capture is contingent on attentional set for displaywide visual features. Journal of Experimental Psychology-Human Perception and Performance, 24(3), 699-706.

Gordon, R. D., & Irwin, D. E. (1996). What's in an object file? Evidence from priming studies. Perception & Psychophysics, 58(8), 1260-1277.

Gordon, R. D., & Irwin, D. E. (2000). The role of physical and conceptual properties in preserving object continuity. Journal of Experimental Psychology-Learning Memory and Cognition, 26(1), 136-150.

Hickey, C., McDonald, J. J., & Theeuwes, J. (2006). Electrophysiological evidence of the capture of visual attention. Journal of Cognitive Neuroscience, 18(4), 604-613.

REFERENCES

158

Hickey, C., Olivers, C., Meeter, M., & Theeuwes, J. (2011). Feature priming and the capture of visual attention: Linking two ambiguity resolution hypotheses. Brain Research, 1370, 175-184.

Hoffman, J. E. (1979). 2-Stage Model of Visual-Search. Perception & Psychophysics, 25(4), 319-327.

Hollingworth, A., Richard, A. M., & Luck, S. J. (2008). Understanding the function of visual short-term memory: Transsaccadic memory, object correspondence, and gaze correction. Journal of Experimental Psychology-General, 137(1), 163-181.

Hommel, B. (1998). Event files: Evidence for automatic integration of stimulus-response episodes. Visual Cognition, 5(1-2), 183-216.

Hommel, B. (2004). Event files: feature binding in and across perception and action. Trends in Cognitive Sciences, 8(11), 494-500.

Hommel, B. (2007). Feature integration across perception and action: event files affect response choice. Psychological Research-Psychologische Forschung, 71(1), 42-63.

Hommel, B., Musseler, J., Aschersleben, G., & Prinz, W. (2001). The Theory of Event Coding (TEC): A framework for perception and action planning. Behavioral and Brain Sciences, 24(5), 849-+.

Huang, L. Q., Holcombe, A. O., & Pashler, H. (2004). Repetition priming in visual search: Episodic retrieval, not feature priming. Memory & Cognition, 32(1), 12-20.

Jonides, J. (1981). Voluntary versus automatic control over the mind's eye's movement. In J. Long & A. Baddeley (Eds.), Attention and performance (Vol. IX, pp. 187-203). Hillsdale, NJ: Erlbaum.

Jonides, J., & Yantis, S. (1988). Uniqueness of Abrupt Visual Onset in Capturing Attention. Perception & Psychophysics, 43(4), 346-354.

Juola, J. F., Koshino, H., & Warner, C. B. (1995). Tradeoffs between Attentional Effects of Spatial Cues and Abrupt Onsets. Perception & Psychophysics, 57(3), 333-342.

Kahneman, D., & Treisman, A. (1984). Changing views of attention and automaticity. In R. Parasuraman & D. A. Davies (Eds.), Varieties of attention (pp. 29-61). San Diego, CA: Academic Press.

Kahneman, D., Treisman, A., & Burkell, J. (1983). The Cost of Visual Filtering. Journal of Experimental Psychology-Human Perception and Performance, 9(4), 510-522.

Kahneman, D., Treisman, A., & Gibbs, B. J. (1992). The Reviewing of Object Files - Object-Specific Integration of Information. Cognitive Psychology, 24(2), 175-219.

Keizer, A. W., Colzato, L. S., & Hommel, B. (2008). Integrating faces, houses, motion, and action: Spontaneous binding across ventral and dorsal processing streams. Acta Psychologica, 127(1), 177-185.

Kim, M. S., & Cave, K. R. (1999). Top-down and bottom-up attentional control: On the nature of interference from a salient distractor. Perception & Psychophysics, 61(6), 1009-1023.

Klein, R. M. (2000). Inhibition of return. Trends in Cognitive Sciences, 4(4), 138-147. Kramer, A. F., & Jacobson, A. (1991). Perceptual Organization and Focused Attention -

the Role of Objects and Proximity in Visual Processing. Perception & Psychophysics, 50(3), 267-284.

REFERENCES

159

Kristjansson, A., Mackeben, M., & Nakayama, K. (2001). Rapid, object-based learning in the deployment of transient attention. Perception, 30(11), 1375-1387.

Kruschke, J. K., & Fragassi, M. M. (1996). The Perception of Causality: Feature binding in interacting objects. Paper presented at the Eighteenth Annual Conference of the Cognitive Science Society.

Kumada, T. (1999). Limitations in attending to a feature value for overriding stimulus-driven interference. Perception & Psychophysics, 61(1), 61-79.

Lamy, D. (2005). Temporal expectations modulate attentional capture. Psychonomic Bulletin & Review, 12(6), 1112-1119.

Lamy, D., & Egeth, H. E. (2003). Attentional capture in singleton-detection and feature-search modes. Journal of Experimental Psychology-Human Perception and Performance, 29(5), 1003-1020.

Lamy, D., Tsal, Y., & Egeth, H. E. (2003). Does a salient distractor capture attention early in processing? Psychonomic Bulletin & Review, 10(3), 621-629.

Lavie, N. (1995). Perceptual Load as a Necessary Condition for Selective Attention. Journal of Experimental Psychology-Human Perception and Performance, 21(3), 451-468.

Leber, A. B., & Egeth, H. E. (2006). It's under control: Top-down search strategies can override attentional capture. Psychonomic Bulletin & Review, 13(1), 132-138.

Logan, G. D. (1988). Toward an Instance Theory of Automatization. Psychological Review, 95(4), 492-527.

Lu, S., & Zhou, K. (2005). Stimulus-driven attentional capture by equiluminant color change. Psychonomic Bulletin & Review, 12(3), 567-572.

Maljkovic, V., & Nakayama, K. (1996). Priming of pop-out .2. The role of position. Perception & Psychophysics, 58(7), 977-991.

MartinEmerson, R., & Kramer, A. F. (1997). Offset transients modulate attentional capture by sudden onsets. Perception & Psychophysics, 59(5), 739-751.

Masson, M. E. J., & Loftus, G. R. (2003). Using confidence intervals for graphically based data interpretation. Canadian Journal of Experimental Psychology-Revue Canadienne De Psychologie Experimentale, 57(3), 203-220.

Michotte, A. (1963). The perception of causality (M. R. Miles & E. Miles, Trans.). Londen: Methuen.

Miller, J. (1989). The Control of Attention by Abrupt Visual Onsets and Offsets. Perception & Psychophysics, 45(6), 567-571.

Mitroff, S. R., & Alvarez, G. A. (2007). Space and time, not surface features, guide object persistence. Psychonomic Bulletin & Review, 14(6), 1199-1204.

Mitroff, S. R., Scholl, B. J., & Noles, N. S. (2007). Object files can be purely episodic. Perception, 36(12), 1730-1735.

Mitroff, S. R., Scholl, B. J., & Wynn, K. (2004). Divide and conquer - How object files adapt when a persisting object splits into two. Psychological Science, 15(6), 420-425.

Moore, C. M., & Enns, J. T. (2004). Object updating and the flash-lag effect. Psychological Science, 15(12), 866-871.

REFERENCES

160

Moore, C. M., Stephens, T., & Hein, E. (2010). Features, as well as space and time, guide object persistence. Psychonomic Bulletin & Review, 17(5), 731-736.

Muller, N. G., & Kleinschmidt, A. (2003). Dynamic interaction of object- and space-based attention in retinotopic visual areas. Journal of Neuroscience, 23(30), 9812-9816.

Noles, N. S., Scholl, B. J., & Mitroff, S. R. (2005). The persistence of object file representations. Perception & Psychophysics, 67(2), 324-334.

Nothdurft, H. C. (1993). Saliency Effects across Dimensions in Visual-Search. Vision Research, 33(5-6), 839-844.

Nothdurft, H. C. (2006). Salience and target selection in visual search. Visual Cognition, 14(4-8), 514-542.

Pashler, H. (1988). Cross-Dimensional Interaction and Texture Segregation. Perception & Psychophysics, 43(4), 307-318.

Pinto, Y., Olivers, C. N. L., & Theeuwes, J. (2005). Target uncertainty does not lead to more distraction by singletons: Intertrial priming does. Perception & Psychophysics, 67(8), 1354-1361.

Posner, M. I. (1980). Orienting of Attention. Quarterly Journal of Experimental Psychology, 32(Feb), 3-25.

Posner, M. I., & Cohen, Y. (1984). Components of Visual Orienting. Attention and Performance(10), 531-556.

Posner, M. I., Snyder, C. R. R., & Davidson, B. J. (1980). Attention and the Detection of Signals. Journal of Experimental Psychology-General, 109(2), 160-174.

Pratt, J., & McAuliffe, J. (2002). Determining whether attentional control settings are inclusive or exclusive. Perception & Psychophysics, 64(8), 1361-1370.

Pratt, J., & Sekuler, A. B. (2001). The effects of occlusion and past experience on the allocation of object-based attention. Psychonomic Bulletin & Review, 8(4), 721-727.

Pratt, J., Sekuler, A. B., & McAuliffe, J. (2001). The role of attentional set on attentional cueing and inhibition of return. Visual Cognition, 8(1), 33-46.

Pylyshyn, Z. W. (2000). Situating vision in the world. Trends in Cognitive Sciences, 4(5), 197-207.

Pylyshyn, Z. W. (2001). Visual indexes, preconceptual objects, and situated vision. Cognition, 80(1-2), 127-158.

Pylyshyn, Z. W., & Storm, R. W. (1988). Tracking multiple independent targets: Evidence for a parallel tracking mechanism. Spatial Vision, 3, 18.

Rafal, R. D., Calabresi, P. A., Brennan, C. W., & Sciolto, T. K. (1989). Saccade Preparation Inhibits Reorienting to Recently Attended Locations. Journal of Experimental Psychology-Human Perception and Performance, 15(4), 673-685.

Rauschenberger, R. (2003a). Attentional capture by auto- and allo-cues. Psychonomic Bulletin & Review, 10(4), 814-842.

Rauschenberger, R. (2003b). When something old becomes something new: Spatiotemporal object continuity and attentional capture. Journal of Experimental Psychology-Human Perception and Performance, 29(3), 600-615.

REFERENCES

161

Remington, R., Johnston, J. C., & Yantis, S. (1986). Do Abrupt Onsets Capture Attention Involuntarily. Bulletin of the Psychonomic Society, 24(5), 347-347.

Remington, R. W., Johnston, J. C., & Yantis, S. (1992). Involuntary Attentional Capture by Abrupt Onsets. Perception & Psychophysics, 51(3), 279-290.

Reynolds, J. H., & Desimone, R. (2003). Interacting roles of attention and visual salience in V4. Neuron, 37(5), 853-863.

Richard, A. M., Luck, S. J., & Hollingworth, A. (2008). Establishing object correspondence across eye movements: Flexible use of spatiotemporal and surface feature information. Cognition, 109(1), 66-88.

Ruz, M., & Lupianez, J. (2002). A review of attentional capture: On its automaticity and sensitivity to endogenous control. Psicologica(23), 289-309.

Scholl, B. J. (2001). Objects and attention: the state of the art. Cognition, 80(1-2), 1-46. Scholl, B. J. (2007). Object persistence in philosophy and psychology. Mind & Language,

22(5), 563-591. Schreij, D., & Olivers, C. N. L. (2009). Object representations maintain attentional control

settings across space and time. Cognition, 113(1), 111-116. Schreij, D., & Olivers, C. N. L. (submitted). Object representations maintain attentional

control settings for task-relevant information. Journal of Experimental Psychology-Human Perception and Performance.

Schreij, D., Owens, C., & Theeuwes, J. (2008). Abrupt onsets capture attention independent of top-down control settings. Perception & Psychophysics, 70(2), 208-218.

Schreij, D., Theeuwes, J., & Olivers, C. N. L. (2010). Abrupt onsets capture attention independent of top-down control settings II: additivity is no evidence for filtering. Attention, Perception & Psychophysics, 72(3), 672-682.

Simons, D. J., & Chabris, C. F. (1999). Gorillas in our midst: sustained inattentional blindness for dynamic events. Perception, 28(9), 1059-1074.

Sternberg, S. (1969). Discovery of Processing Stages - Extensions of Donders Method. Acta Psychologica, 30, 276-+.

Theeuwes, J. (1990). Perceptual Selectivity Is Task Dependent - Evidence from Selective Search. Acta Psychologica, 74(1), 81-99.

Theeuwes, J. (1991a). Cross-Dimensional Perceptual Selectivity. Perception & Psychophysics, 50(2), 184-193.

Theeuwes, J. (1991b). Exogenous and Endogenous Control of Attention - the Effect of Visual Onsets and Offsets. Perception & Psychophysics, 49(1), 83-90.

Theeuwes, J. (1992). Perceptual Selectivity for Color and Form. Perception & Psychophysics, 51(6), 599-606.

Theeuwes, J. (1994a). Endogenous and Exogenous Control of Visual Selection. Perception, 23(4), 429-440.

Theeuwes, J. (1994b). Stimulus-Driven Capture and Attentional Set - Selective Search for Color and Visual Abrupt Onsets. Journal of Experimental Psychology-Human Perception and Performance, 20(4), 799-806.

REFERENCES

162

Theeuwes, J. (1995a). Abrupt Luminance Change Pops out - Abrupt Color-Change Does Not. Perception & Psychophysics, 57(5), 637-644.

Theeuwes, J. (1995b). Perceptual selectivity for color and form: On the nature of the interference effect. In A. F. Kramer , M. G. H. Coles & G. D. Logan (Eds.), Converging operations in the study of visual selective attention (pp. 297-314). Washington, DC: American Psychological Association.

Theeuwes, J. (1996). Perceptual selectivity for color and form: On the nature of the interference effect. In A. F. Kramer , M. G. H. Coles & G. D. Logan (Eds.), Converging operations in the study of visual selective attention (pp. 297-314). Washington, DC: American Psychological Association.

Theeuwes, J. (2000). Attentional capture and oculomotor control. Perception, 29, 2-2. Theeuwes, J. (2004). Top-down search strategies cannot override attentional capture.

Psychonomic Bulletin & Review, 11(1), 65-70. Theeuwes, J. (2010). Top-down and bottom-up control of visual selection. Acta

Psychologica, 135(2), 77-99. Theeuwes, J., & Burger, R. (1998). Attentional control during visual search: The effect of

irrelevant singletons. Journal of Experimental Psychology-Human Perception and Performance, 24(5), 1342-1353.

Theeuwes, J., De Vries, G. J., & Godjin, R. (2003). Attentional and oculomotor capture with static singletons. Perception & Psychophysics, 65(5), 735-746.

Theeuwes, J., & Godijn, R. (2001). Attentional and oculomotor capture with static singletons. In C. L. Folk & B. S. Gibson (Eds.), Attraction, distraction and action: Multiple perspectives on attentional capture (pp. 121-149). New York: Elsevier.

Theeuwes, J., & Godijn, R. (2002). Irrelevant singletons capture attention: Evidence from inhibition of return. Perception & Psychophysics, 64(5), 764-770.

Theeuwes, J., Kramer, A. F., & Atchley, P. (2000). On the time course of top-down and bottom-up control of visual attention. In S. Monsell & J. Driver (Eds.), Attention & Performance (Vol. 18). Cambridge: MIT Press.

Theeuwes, J., Kramer, A. F., Hahn, S., & Irwin, D. E. (1998). Our eyes do not always go where we want them to go: Capture of the eyes by new objects. Psychological Science, 9(5), 379-385.

Theeuwes, J., Kramer, A. F., Hahn, S., Irwin, D. E., & Zelinsky, G. J. (1999). Influence of attentional capture on oculomotor control. Journal of Experimental Psychology-Human Perception and Performance, 25(6), 1595-1608.

Theeuwes, J., & van der Burg, E. (2008). The role of cueing in attentional capture. Visual Cognition, 16(2-3), 232-247.

Tipper, S. P., Brehaut, J. C., & Driver, J. (1990). Selection of Moving and Static Objects for the Control of Spatially Directed Action. Journal of Experimental Psychology-Human Perception and Performance, 16(3), 492-504.

Tipper, S. P., Grison, S., & Kessler, K. (2003). Long-term inhibition of return of attention. Psychological Science, 14(1), 19-25.

REFERENCES

163

Tipper, S. P., Weaver, B., Jerreat, L. M., & Burak, A. L. (1994). Object-Based and Environment-Based Inhibition of Return of Visual-Attention. Journal of Experimental Psychology-Human Perception and Performance, 20(3), 478-499.

Todd, J. T., & Van Gelder, P. (1979). Implications of a Transient-Sustained Dichotomy for the Measurement of Human-Performance. Journal of Experimental Psychology-Human Perception and Performance, 5(4), 625-638.

Treisman, A., & Gelade, G. (1980). Feature-Integration Theory of Attention. Cognitive Psychology, 12(1), 97-136.

Treisman, A., & Kahneman, D. (1983). The Accumulation of Information within Object Files. Bulletin of the Psychonomic Society, 21(5), 354-354.

Treisman, A., & Sato, S. (1990). Conjunction Search Revisited. Journal of Experimental Psychology-Human Perception and Performance, 16(3), 459-478.

Tsal, Y., & Benoni, H. (2010a). Diluting the Burden of Load: Perceptual Load Effects Are Simply Dilution Effects. Journal of Experimental Psychology-Human Perception and Performance, 36(6), 1645-1656.

Tsal, Y., & Benoni, H. (2010b). Much Dilution Little Load in Lavie and Torralbo's (2010) Response: A Reply. Journal of Experimental Psychology-Human Perception and Performance, 36(6), 1665-1668.

Tsal, Y., & Benoni, H. (2010c). Where have we gone wrong? Perceptual load does not affect selective attention. Vision Research, 50(13), 1292-1298.

Tsotsos, J. K., Culhane, S. M., Wai, W. Y. K., Lai, Y. H., Davis, N., & Nuflo, F. (1995). Modeling Visual-Attention Via Selective Tuning. Artificial Intelligence, 78(1-2), 507-545.

von Muhlenen, A., Rempel, M. I., & Enns, J. T. (2005). Unique temporal change is the key to attentional capture. Psychological Science, 16(12), 979-986.

Weger, U. W., Abrams, R. A., Law, M. B., & Pratt, J. (2008). Attending to objects: Endogenous cues can produce inhibition of return. Visual Cognition, 16(5), 659-674.

Wolfe, J. M. (1994). Guided Search 2.0 - a Revised Model of Visual-Search. Psychonomic Bulletin & Review, 1(2), 202-238.

Xu, F., & Carey, S. (1996). Infants' metaphysics: The case of numerical identity. Cognitive Psychology, 30(2), 111-153.

Xu, F., & Carey, S. (2000). The emergence of kind concepts: a rejoinder to Needham and Baillargeon (2000). Cognition, 74(3), 285-301.

Xu, Y. D., & Chun, M. M. (2006). Dissociable neural mechanisms supporting visual short-term memory for objects. Nature, 440(7080), 91-95.

Yantis, S. (1993). Stimulus-Driven Attentional Capture and Attentional Control Settings. Journal of Experimental Psychology-Human Perception and Performance, 19(3), 676-681.

Yantis, S. (1996). Attentional capture in vision. In A. F. Kramer, M. G. H. Coles & G. D. Logan (Eds.), Converging operations in the study of visual selective attention (pp. 45-76). Washington, DC: American Psychological Association.

REFERENCES

164

Yantis, S., & Egeth, H. E. (1999). On the distinction between visual salience and stimulus-driven attentional capture. Journal of Experimental Psychology-Human Perception and Performance, 25(3), 661-676.

Yantis, S., & Hillstrom, A. P. (1994). Stimulus-Driven Attentional Capture - Evidence from Equiluminant Visual Objects. Journal of Experimental Psychology-Human Perception and Performance, 20(1), 95-107.

Yantis, S., & Johnson, D. N. (1990). Mechanisms of Attentional Priority. Journal of Experimental Psychology-Human Perception and Performance, 16(4), 812-825.

Yantis, S., & Jonides, J. (1984). Abrupt Visual Onsets and Selective Attention - Evidence from Visual-Search. Journal of Experimental Psychology-Human Perception and Performance, 10(5), 601-621.

Yantis, S., & Jonides, J. (1990). Abrupt Visual Onsets and Selective Attention - Voluntary Versus Automatic Allocation. Journal of Experimental Psychology-Human Perception and Performance, 16(1), 121-134.

Yi, D. J., Turk-Browne, N. B., Flombaum, J. I., Kim, M. S., Scholl, B. J., & Chun, M. M. (2008). Spatiotemporal object continuity in human ventral visual cortex. Proceedings of the National Academy of Sciences of the United States of America, 105(26), 8840-8845.

ACKNOWLEDGEMENTS / DANKWOORD

165

Acknowledgements / Dankwoord

Over the past four years that I have been doing research for this thesis, many people have in their own way contributed to its realization. To these people I would like to dedicate a few words of appreciation.

First of all, I would of course like to thank Chris Olivers, my supervisor and co-promotor, for guiding me in taking the first steps in the world of science. Thanks to you, I have gained numerous invaluable skills which I would never have acquired on my own. Not only did you greatly contribute to all the things I have learned, you also made sure our scientific endeavors always were a lot of fun and remained interesting to pursue, even if experiments sometimes did not seem to work out as well as hoped in the beginning. Thanks for being such an awesome supervisor!

Second, I would like to thank Jan Theeuwes, my promotor and professor, for coming up with the idea to pursue a career in science while we were hiking through the Blue Mountains in Australia. Many times you have been able to steer shaky research ideas in the right direction, often leading to successful experiments. I always liked your witty and provocative jokes, together with the interesting discussions you often managed to incite during lunch breaks. And remember, if you ever need my help with getting your phone or laptop on the wireless network of the VU again, just call.

My time at the Cognitive Psychology department of course wouldn’t have been as enjoyable without all of its other members. I would like to thank Artem, Mieke, Dirk, Richard, Hannie, Adelbert, Martijn, Erik, Thomas, Yaïr, Manon and Durk for making the last four years as fun and cultivating as they were. I am going to miss our lunch-break volleyball matches! Wieske and Clayton, thanks for helping me with preparing my trip to Vancouver and assisting me in creating my first conference poster. Sander, I always appreciated the sound advice you were able to give me whenever I got lost in the wonderland of complex statistical analyses again. Jaap, I am glad you could often help me with important organizational matters and that we could always share our enthusiasm for technical stuff with each other. Sebastiaan, thanks for the great toolset you built from scratch for creating and conducting experiments. I could always count on your help and expertise when the occasional problem occurred. And of course I could not forget Janne, Anna, Lisette, Alisha, Judith, Mauricio, Isabel, Kim, Wouter, Marlou and Shanna. We have always had lots of fun at the office, but even more so during the activities and trips we undertook outside working hours. Thanks for the dinners, excursions, afternoons in the park and the great atmosphere you generally created at the department!

Furthermore, I would like to thank prof. Jim Enns, prof. Alan Kingstone and all the other people at the Vision and BAR labs at the University of British Columbia in Vancouver, Canada for making the five months that I visited the best I could imagine. Jim, a special thanks to you, for providing the support and fruitful ideas for the experiments I

ACKNOWLEDGEMENTS/DANKWOORD

166

conducted at your lab. I have very fond memories of my time in Vancouver and I hope I will be able visit all of you again sometime soon.

I also would like to thank René, Henk-Jan and Sam for having been such good friends as long as I can remember. Sam, I am very impressed by the cover that you have created for this thesis. I have always appreciated your artist’s perspective on things and am still grateful that you sparked my interest in photography years ago.

I would also like to thank my friends Paul and Ronald, who were willing to stand by me during the defense of my dissertation. Together with Jurgen and Dorine, you have been the most valuable friends for years. We have known many good times together when traveling, going out or just hanging out. Thanks for lightening me up with one of your crazy jokes whenever I had ‘one of those days’ again.

Kah-Kin, Esmeralda, Kah-Wai, Myrthe and Wasja, thanks for having been such wonderful flat mates and friends for so many years. Together we made sure that we had a place which really felt like home, to which we could return after work each day.

Furthermore, I’d like to say thanks to Hanneke and Suzan, for being the best surfing and travelling buddies. No wave or mountain has been too high for us (ok, the wave part is indeed a lie). To Fong and Emma, for lending me your hands to exhibit on the cover. To all the people of the SDVA, for the numerous swims, dives and just very gezellige days I have experienced with you for many years now.

And most of all I would like to thank my parents, Leonie and Gerard, and my sister Michèle for their unfaltering support of me no matter what decision I made, good or bad, and for just having been there all my life.

CURRICULUM VITAE

167

Curriculum Vitae

Daniel was born on July 14th, 1982 in Amsterdam, the Netherlands. He received a

bachelor’s degree in Artificial Intelligence from the VU University Amsterdam in August

of 2003 and continued his studies there to receive a Master’s degree in Cognitive Science

in August of 2006. He conducted part of the required research for his Master’s thesis at

the University of Sydney, Australia under the supervision of dr. Caleb Owens and prof.dr.

Jan Theeuwes. The thesis is titled “Involuntary Contingent Orienting is subject to

Bottom-Up Attentional Capture”. He began as a PhD student at the VU University

Amsterdam in September of 2007 and conducted part of his research at the University of

British Columbia in Vancouver, Canada in the first half of 2011 under supervision of

prof.dr. Jim Enns.

AUTHOR PUBLICATIONS

168

Author publications

Belopolsky, A. V., Schreij, D., & Theeuwes, J. (2010). What is top-down about contingent capture? Attention, Perception & Psychophysics, 72(2), 326-341.

Mathôt, S., Schreij, D., & Theeuwes, J. (in press). OpenSesame: An open-source, graphical

experiment builder for the social sciences. Behavior Research Methods.

Schreij, D., Owens, C., & Theeuwes, J. (2008). Abrupt onsets capture attention

independent of top-down control settings. Perception & Psychophysics, 70(2), 208-218.

Schreij, D., & Olivers, C. N. L. (2009). Object representations maintain attentional

control settings across space and time. Cognition, 113(1), 111-116. Schreij, D., Theeuwes, J., & Olivers, C. N. L. (2010). Abrupt onsets capture attention

independent of top-down control settings II: additivity is no evidence for filtering. Attention, Perception & Psychophysics, 72(3), 672-682.

Schreij, D., Theeuwes, J., & Olivers, C. N. L. (2010). Irrelevant onsets cause inhibition of

return regardless of attentional set. Attention Perception & Psychophysics, 72(7), 1725-1729.

Vrije Universiteit Amsterdam · VRIJE UNIVERSITEIT. Attention to Emerging Objects . ACADEMISCH...

Documents

Transcript of Vrije Universiteit Amsterdam · VRIJE UNIVERSITEIT. Attention to Emerging Objects . ACADEMISCH...