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The heritability of trait frontal EEG asymmetry and negativeemotionality: Sex differences and genetic nonadditivity
Item Type text; Dissertation-Reproduction (electronic)
Authors Coan, Jr., James A.
Publisher The University of Arizona.
Rights Copyright © is held by the author. Digital access to this materialis made possible by the University Libraries, University of Arizona.Further transmission, reproduction or presentation (such aspublic display or performance) of protected items is prohibitedexcept with permission of the author.
Download date 12/05/2018 03:53:24
Link to Item http://hdl.handle.net/10150/280273
THE HERITABILITY OF TRAIT FRONTAL EEG ASYMMETRY AND NEGATIVE
EMOTIONALITY: SEX DIFFERENCES AND GENETIC NONADDITIVITY
by
James Arthur Coan, Jr.
Copyright James Arthur Coan, Jr. 200 3
A Dissertation Submitted to the Faculty of the
DEPARTMENT OF PSYCHOLOGY
In Partial Fulfillment of the Requirements
For the Degree of
DOCTOR OF PHILOSOPHY
In the Graduate College
THE UNIVERSITY OF ARIZONA
2003
UMI Number: 3089933
Copyright 2003 by
Coan, James Arthur, Jr.
All rights reserved.
UMI UMI Microform 3089933
Copyright 2003 by ProQuest Information and Learning Company.
All rights reserved. This microform edition is protected against
unauthorized copying under Title 17, United States Code.
ProQuest Information and Learning Company 300 North Zeeb Road
P.O. Box 1346 Ann Arbor, Ml 48106-1346
9
THE UNIVERSITY OF ARIZONA ® GRADUATE COLLEGE
As members of the Final Examination Committee, we certify that we have
read the dissertation prepared by JAMES ARTHUR COAN, J R .
entitled THE HERITABILITY OF TRAIT FRONTAL EEG ASYMMETRY
AND NEGATIVE EMOTIONALITY; SEX DIFFERENCES AND
GENETIC NONADDITIVITY
and recommend that it be accepted as fulfilling the dissertation
Doctor of Philosophy
John/fJ. bC Allen, Ph.D
Final approval and acceptance of this dissertation is contingent upon
the candidate's submission of the final copy of the dissertation to the
Graduate College.
I hereby certify that I have read this dissertation prepared under my
direction and recommend that it be accepted as fulfilling the dissertation
requirem^t.
Disseri irector xon
J Date
3
STATEMENT BY AUTHOR
This dissertation has been submitted in partial fulfillment of requirements for an advanced degree at The University of Arizona and is deposited in the University Library to be made available to borrowers under rules of the Library.
Brief quotations from this dissertation are allowable without special permission, provided that accurate acknowledgment of source is made. Requests for permission for extended quotation from or reproduction of this manuscript in whole or in part may be granted by the copyright holder.
SIGNED
4
TABLE OF CONTENTS
LIST OF FIGURES 6
LIST OF TABLES 7
ABSTRACT 8
INTRODUCTION 9
Heritability of Personality as Assessed by the
Multidimensional Personality Questionnaire 11
Frontal EEG Asymmetry, Personality and Psychopathology 12
The Heritability of EEG 16
Heritability of EEG spectra at individual sites 16
Heritability of EEG asymmetry 17
Study Goals and Hypotheses 18
METHOD 2 0
Participants and procedure 20
EEG Recordings 20
The Multidimensional Personality Questionnaire 22
RESULTS 23
Heritability of Frontal EEG asymmetry 25
Falconer's Estimate 25
Latent Variable Modeling 26
The Heritability of Absorption, Traditionalism, Negative
Emotionality, and Positive Emotionality 30
The Cholesky Hypothesis 33
Positive Emotionality and Traditionalism 33
Negative Emotionality 35
DISCUSSION 3 9
5
TABLE OF CONTENTS - Continued
Sex Differences in the Heritability
of Frontal EEG asymmetry 39
Mid-Frontal EEG asymmetry and the MPQ 41
Interpreting the Cholesky Model 4 4
Methodological constraints 45
The generalizability of trait EEG asymmetry measurement .... 45
The need for more EEG sites 4 7
Sample size 47
Concluding Remarks 4 8
REFERENCES 5 0
6
LIST OF FIGURES
Figure 1, Heritability of midfrontal EEG asymmetry 30
Figure 2, Heritability of Traditionalism 32
Figure 3, Heritability of Positive Emotionality 33
Figure 4, Heritability of Negative Emotionality 34
Figure 5, Midfrontal EEG Asymmetry/Negative
Emotionality Cholesky Model 37
Figure 6 , Bivariate Heritability Equation 38
7
LIST OF TABLES
Table 1, Means and standard deviations for mid-frontal
EEG asymmetry by zygosity, sex and reference scheme 24
Table 2, Zero order correlations between mid-frontal
EEG asymmetry and the primary and higher order
scales of the MPQ 25
Table 3, Fit statistics for ACE and ADE models,
by sex and reference scheme 27
The heritability of personality was addressed using a
psychophysiological measure, midfrontal EEG asymmetry, and a paper and
pencil measure, the Multidimensional Personality Questionnaire (MPQ).
The degree to which midfrontal EEG asymmetry was correlated with the
scales of the MPQ was assessed. Relatively greater right midfrontal
EEG asymmetry was associated with higher Absorption and Negative
Emotionality scores in both the Cz and linked mastoid reference schemes
in females, but not in males. Relatively greater right midfrontal EEG
asymmetry was also associated with higher Traditionalism and Positive
Emotionality scores in the Cz reference scheme in females but not in
males. Midfrontal EEG asymmetry was found to be modestly heritable in
females, but not in males. Further, each of the scales of the MPQ
correlated with midfrontal EEG asymmetry demonstrated moderate to high
heritability. A bivariate Cholesky model was used to estimate the
heritability of the phenotypic correlations between midfrontal EEG
asymmetry and each of the scales with which it was related. Only the
midfrontal EEG Asymmetry/Negative Emotionality Cholesky model
demonstrated sufficient fit the observed data. According to this
model, common genetic effects accounted for approximately 40% of the
observed phenotypic correlation between midfrontal EEG asymmetry and
Negative Emotionality.
9
INTRODUCTION
It is increasingly difficult to find traits that are not, at
least in part, heritable. This is certainly true of personality
measures, examples of which include, among a variety of others.
Hysterical Personality (Young, Fenton, & Lader, 1971), ''sleepiness''
(Toth, 2001) , impulsivity (Willcutt, Pennington, & DeFries, 2000) and
the ''big five'' dimensions of Neuroticism, Extraversion, Openness,
Agreeableness, and Conscientiousness (Jang, Livesley, Angleitner,
Riemann, & Vernon, 2002; Jang, Livesley, & Vernon, 1996), the latter
cluster of which has even been demonstrated to be heritable in
chimpanzees (Weiss, King, & Figueredo, 2000). Although genetic variance
clearly accounts for variance in personality constructs, the mechanism
by which this occurs is not obvious. Ultimately, a truly comprehensive
explanation will involve several levels of analysis (cf., Anderson &
Scott, 1999) spanning the molecular, cellular, physiological,
psychological, and behavioral levels of analysis. Toward this end,
psychophysiological investigations can prove particularly useful, for
if genetic effects on personality are mediated through effects on a
psychophysiological measure, a useful link may be established between
macro and micro level explanations of the genetics of temperament and
personality (Anderson & Scott, 1999). A potentially good candidate for
such a psychophysiological link is frontal EEC alpha asymmetry, a
measure which has itself frequently been linked to many of the
partially heritable constructs of personality, temperament, and
psychopathology (which may represent extreme personality tendencies,
10
e.g., Coan & Allen, 2003; Fowles, 1994). The nature of the
relationship between frontal EEG asymmetry and measures of personality
and psychopathology is itself of great theoretical interest. As a
measure, frontal EEG asymmetry is thought to index tendencies to
approach (indicated by relatively greater left frontal activity) and
withdraw (indicated by relatively less left frontal activity). While it
has been suggested that frontal EEG asymmetry in turn indexes a
predisposition for certain personality styles and risk for affective
disorders (Davidson, 1998) , this relationship has not been explored
causally (Coan & Allen, 2003a; Coan & Allen, 2003c). While behavior
genetic models are also entirely correlational, they suggest plausible
causal relationships that may serve as useful heuristics for the study
of frontal EEG asymmetry and a variety of personality dimensions,
including affective style (Davidson, 199 8) and risk for
psychopathology. Importantly, EEG spectral patterns have been shown to
be heritable (Lykken, Tellegen, & lacono, 1982; Stassen, Bomben, &
Hell, 1998; Stassen, Lykken, & Bomben, 1988), suggesting the
possibility that EEG asymmetries may be as well.
The present study therefore sought to 1) provide further support
for the link between frontal EEG asymmetry and measures of personality,
2) assess the heritability of frontal EEG asymmetry, and 3) use the
techniques of behavior genetic modeling to determine the nature of the
relationship between frontal EEG asymmetry and personality, as measured
by the Multidimensional Personality Questionnaire (MPQ).
11
Heritability of Personality as Assessed by the Multidimensional
Personality Questionnaire
The Multidimensional Personality Questionnaire (MPQ) was
developed with the aim of distilling the myriad common personality
constructs extant in the personality literature, and with an emphasis
on discriminant validity (Tellegen, Lykken, Bouchard, Wilcox, & et al.,
1988). While not constructed with a particular higher-order factor
structure in mind, the scales of the MPQ, including those intended to
measure Well-Being, Social Potency, Achievement, Social Closeness,
Absorption, Stress Reactivity, Alienation, Aggression, Control, Harm
Avoidance, and Traditionalism, commonly load onto higher order
orthogonal factors very similar to others found in the literature
(Tellegen et al., 1988). These factors include Positive Emotionality
(often compared to Extroversion), Negative Emotionality (often compared
to Neuroticism) and Constraint (Tellegen et al. , 1988) . Investigations
have found that these scales and factors have moderate heritabilities
(ranging from .39 to .58) for all of the subscales of the MPQ (Tellegen
et al., 1988). Other studies corroborate these findings while
suggesting that Alienation and Control may be less heritable in women
while Absorption may be more so (Finkel & McGue, 1997) . At least one
study has estimated the heritability of the Well Being scale to be
possibly as high as 80% (Lykken & Tellegen, 199 6).
12
Frontal EEG Asymmetry, Personality and Psychopathology
Asymmetrical patterns of Electroencephalographic (EEG) activity
recorded over the frontal lobes at rest have proven useful in the
prediction of emotion-related traits and behaviors, including affective
disorders (see Coan & Allen, 2003a for a comprehensive review). As a
trait measure, frontal EEG asymmetry has been linked to depression
(Allen, lacono, Depue, & Arbisi, 1993; Henriques & Davidson, 1990),
anxiety (Wiedemann, Pauli, Dengler, Lutzenberger, Birbaumer, &
Buchkremer, 1999) , trait aggression (Harmon-Jones & Allen, 1998), trait
behavioral activation (Coan & Allen, 2003b; Harmon-Jones & Allen,
1997), shyness (Schmidt, 1999), subjective emotional experience reports
(Coan & Allen, in press), general ''affective style'' (Davidson, 1998)
and even immune responsivity (Davidson, Coe, Dolski, & Donzella, 19 99).
It is thought that at its most basic level trait frontal EEG asymmetry,
depending on its direction, indexes tendencies to approach (with
activity lateralized to the left) or withdraw (with activity
lateralized to the right) from novel or affective stimuli (Coan &
Allen, 2003a) . This approach/withdrawal continuum has itself been
proposed as the most fundamental decision-making dimension employed by
any organism (Schneirla, 1959).
A number of studies have related frontal EEG asymmetry to trait
personality measures, such as behavioral activation (derived from the
Behavioral Activation Scale or BAS, Coan & Allen, 2003b; Harmon-Jones &
Allen, 1997; Sutton & Davidson, 1997), defensive coping style (Kline,
Allen, & Schwartz, 1998; Tomarken & Davidson, 1994), social inhibition
(Fox, Rubin, Calkins, Marshall, Coplan, Porges, Long, & Stewart, 19 95;
Schmidt & Fox, 1994) and shyness (Schmidt, Fox, Schulkin, & Gold,
1999). Others have found that resting frontal asymmetries lateralized
to the left - indicating a propensity to approach - are related to
trait measures of aggression and/or angry behavior (Harmon-Jones &
Allen, 1998; Harmon-Jones & Sigelman, 2001). Studies of ''affective
style'' (e.g., Davidson, 19 98) have linked frontal EEG asymmetry to
global positive and negative affective responses to emotionally
evocative films or slides (Wheeler, Davidson, & Tomarken, 1993). In
these studies, participants tend to report the intensity of their
specific affective responses (e.g., of fear or sadness) in a manner
predicted by their resting frontal EEG asymmetry, and in accord with
the approach withdrawal model. For example, individuals with greater
right frontal activity at rest tend to respond with more intense levels
of negative affect to negatively-valenced film clips, particularly
those involving fear (Tomarken, Davidson, & Henriques, 1990), and with
more intense levels of positive affect in response to positively
valenced film clips (Wheeler et al., 1993) . Based on these studies and
others it has been argued that frontal EEG asymmetry may underlie
certain personality styles, and, indeed, may similarly index a
diathesis for certain affective disorders (Davidson, 1998) . Several
studies support the latter notion. In particular, relatively less left
frontal EEG activity - indicating a decreased propensity to approach -
has generally but not ubiquitously (Reid, Duke, Sc Allen, 1998) been
shown to correlate with depression (e.g., Baehr, Rosenfeld, Baehr, &
14
Earnest, 1998; Debener, Beauducel, Nessler, Brocke, Heilemann, &
Kayser, 2000; Gotlib, Ranganath, & Rosenfeld, 1998; Henriques &
Davidson, 1991; Schaffer, Davidson, & Saron, 1983), seasonal depression
(Allen, lacono, Depue, & Arbisi, 1993), and with risk for depression in
those with a history of depression who are not currently depressed
(Allen et al., 1993; Gotlib et al., 1998; Henriques & Davidson, 1990).
Other studies have associated relatively greater right frontal EEG
activity with anxiety (Davidson, Marshall, Tomarken, & Henriques, 2000;
Heller, Nitschke, Etienne, & Miller, 1997; Nitschke, Heller, Palmieri,
& Miller, 1999).
Many authors have speculated that certain forms of
psychopathology may arise out of extremes in the continua of normal
personality traits (Depue & Collins, 199 9; Fowles, 1994; Kring &
Bachorowski, 1999). Moreover, like many aspects of personality,
psychopathology tends to be rather heritable. Studies have yielded
moderate to high heritability estimates for depression (Brown, 1998;
Happonen, Pulkkinen, Kaprio, Van der Meere, Viken, & Rose, 2 002;
Johansson, Jansson, Linner, Yuan, Pedersen, Blackwood, Barden, Kelsoe,
& Schalling, 2001; Johnson, McGue, Gaist, Vaupe1, & Christensen, 2002;
Kendler & Aggen, 2001; Kendler, Gardner, Neale, & Prescott, 2001; Rice,
Harold, & Thaper, 2002), anxiety (Fyer, 1993; Gillespie-, Zhu, Heath,
Hickie, & Martin, 2000; Kendler, Gardner, & Prescott, 2001; Kendler,
Neale, Kessler, Heath, & et al. , 1992 ; Knowles, Mannuzza, & Fyer, 1 995;
Stein, Jang, & Livesley, 1999; Thapar & McGuffin, 1995), and clinical
levels of aggression (Gates, Houston, Vavak, Crawford, & et al., 19 93;
Coccaro, Bergeman, Kavoussi, & Seroczynski, 199 7; Coccaro, Bergeman, &
McClearn, 1993; Dionne, Tremblay, Boivin, Laplante, & Perusse, 2003;
Ghodsian-Carpey & Baker, 1987; Rowe, Almeida, & Jacobson, 1999;
Vierikko, Pulkkinen, Kaprio, Viken, & Rose, 2003). The relationship
between frontal EEG asymmetry and depression, including risk for
depression, is increasingly well documented (e.g., Allen et al., 1993;
Gotlib et al., 1998; Henriques & Davidson, 1990; Henriques & Davidson,
1991). Researchers are now investigating the role of frontal EEG
asymmetry in anxiety disorders (e.g., Davidson et al., 2000; Heller et
al. , 1997) and in tendencies toward trait aggression (Harmon-Jones &
Allen, 1998) . Further, it has been suggested that these disorders
represent extremes in personality style (e.g., Kring & Bachorowski,
1999). This is particularly true of personality styles related to
positive and negative affect, as evidenced by the frequent use of the
general rubric '"affective disorders'' in describing them (e.g.,
Davidson, 19 98). In sum, the links between frontal EEG asymmetry,
psychopathology, and personality warrant the inference that frontal EEG
asymmetry may underlie, at least in part, important aspects of
personality and risk for psychopathology, and, potentially, that
heritable aspects of EEG asymmetry contribute to the heritability of
personality and risk for psychopathology. This latter conjecture
assumes that frontal EEG asymmetry may in fact be heritable, a
possibility that has not been fully investigated.
16
The Heritability of EEG
A number of characteristics attributable to frontal EEG asymmetry
suggest that it may be heritable. This likelihood derives from the
fact that frontal EEG asymmetries tend to show fairly high inter-
individual variation while also showing relatively low intra-individual
variation. Investigations into the psychometric properties of frontal
EEG asymmetry have yielded very high internal consistency estimates,
with Cronbach's alphas ranging from .81 to .90 (Tomarken, Davidson,
Wheeler, & Kinney, 1992). Test-retest estimates of reliability have
shown acceptable to high intra-class correlations, ranging from .44 to
.71 across 3 weeks (Tomarken at al., 1992) and .50 to .75 across 5
months (Allen, Urry, Hitt, & Coan, 2003) . Similarly, Jones, Field,
Davalos and Pickens (1997) found that frontal EEG asymmetry recorded at
3 months of age was highly correlated with the same asymmetry at 3 yrs
(r = .66, p < .01). More recently, Hagemann, Naumann, Thayer, &
Bartussek (2002) determined that across four different measurement
occasions, 6 0% of the explained variance in EEG asymmetry measures was
due to individual differences in a temporally stable latent trait,
while 4 0% of the variance of the asymmetry scores was due to occasion-
specific fluctuations.
Heritability of EEG spectra at individual sites. With these
trait-like qualities attributable to EEG asymmetries, it is perhaps
unsurprising that research on the heritability of a variety of patterns
of EEG activity derived from numerous laboratories suggest that EEG
spectra are moderately to highly heritable (e.g., Lykken et al., 1982;
17
Stassen et al., 1998; Stassen et al., 1988). In particular, Stassen et
al. (19 98) arrived at a heritability estimate of 0.75 using two
independent analytic methods - one involving analyses of parent-
offspring similarity and the other using an analysis of the difference
in within-pair similarity between monozygotic and dizygotic twins.
Heritability of EEG asymmetry. In terms of EEG asymmetry
specifically, data are more limited, although two conference reports
suggest that it too is heritable (MacDhomhail, Allen, Katsanis, &
lacono, 1999; Rickman & Davidson, 1991). In one of these, frontal EEG
asymmetry showed that in females, but not in males, there is greater
similarity in monozygotic twins than dizygotic twins (MacDhomhail et
al., 19 99). In the other, a midparent (mean of father and mother) -
child correlation of .47 for frontal EEG asymmetry was reported
(Rickman & Davidson, 1991). No published reports have yet assessed the
heritability of frontal EEG asymmetry. It is noteworthy, however, that
infants of depressed mothers show relatively greater right frontal EEG
activity similar to that of their mothers (Dawson, Frey, Panagiotides,
Yamada, Hessl, & Osterling, 1999; Field, Fox, Pickens, & Nawrocki,
1995). While these studies are consistent with a genetic perspective,
they do not address the question of heritability, per se, as these
children share environments with their mothers. Nonetheless, although
environmental effects (e.g., interactions with the depressed mother)
cannot be ruled out, the possibility of genetic transmission - in the
form of a potential genetic vulnerability - is worth consideration.
18
Thus, EEG asymmetries represent possible indices of physiological
processes underlying the phenotypic expression of various aspects of
personality and psychopathology. To date it has been shown that
personality and psychopathology are heritable, and it appears that EEG
asymmetry may be as well. These findings, in concert with those of
numerous studies linking frontal EEG asymmetry and personality, suggest
the possibility that frontal EEG asymmetry and personality are linked
to similar genetic and/or environmental origins, and, indeed, that the
heritability of personality may in part be mediated by heritability of
resting frontal EEG asymmetry. Behavior genetic models in turn suggest
the promise of testing these possibilities.
Study Goals and Hypotheses
For this study, it was hypothesized that certain personality
attributes are genetically mediated, and that the genes that act on
those personality attributes do so in part via their effects on brain
mechanisms indexed by activity asymmetries over the frontal cortex.
For the purposes of this study, this hypothesis will be referred to as
the ''Cholesky hypothesis,'' after the so-called ''Cholesky'' models
frequently employed to evaluate such relationships (e.g., McGue &
Lykken, 1992) . In order to evaluate the Cholesky hypothesis, several
initial criteria need to be evaluated. First, if the Cholesky
hypothesis is true, then it must also be true that frontal EEG
asymmetry is correlated with the measures of personality that EEG
specific genetic effects are thought to underlie. Thus, it was first
hypothesized that frontal EEG asymmetry will be correlated with some or
all measures of personality derived from the MPQ. Within this
hypothesis, specific hypotheses include 1) relatively greater left
frontal resting EEG activity will predict higher scores on the higher
order factor of Positive Emotionality and its derivatives, including
Weil-Being, Social Potency, Achievement, Social Closeness and
Absorption; 2) Relatively greater right frontal activity will predict
higher scores on the higher order factors of Negative Emotionality and
Constraint, in addition to their constituent scales.
Second, if the Cholesky hypothesis is true, then both frontal EEG
asymmetry and those dimensions of personality with which it correlates
must to some extent be heritable. Current evidence clearly supports
this condition in the case of those dimensions of personality measured
by the MPQ (e.g., Finkel & McGue, 1997; Krueger, 2000; Patrick, Curtin,
& Tellegen, 2002; Tellegen et al., 1988) , and suggests that it is
likely in the case of frontal EEG asymmetry (Coan & Allen, 2003a;
MacDhomhail et al., 1999; Rickman & Davidson, 1991). Thus, it is also
hypothesized that both frontal EEG asymmetry and those personality
characteristics with which frontal EEG asymmetry is correlated will be
partially determined by genetic influences.
20
METHOD
Participants and procedure
EEG and personality measures were collected from 197 twin pairs
who participated in the Minnesota Twin/Family Study (see lacono,
Carlson, Taylor, Elkins, & McGue, 199 9). Because of missing or bad
data in EEG, 36 twin pairs were excluded from analysis. An additional
36 twin pairs had to be excluded from analysis due to incomplete MPQ
data. The final sample consisted of 125 twin pairs (250 individual
participants) comprised of 59 male twin pairs (MZ = 29, DZ = 30) and 66
female twin pairs (MZ =30, DZ 3 6). The mean age for the sample was 19
years. In this sample, zygosity was determined using 3 different
procedures: 1) Parents filled out a questionnaire of physical
similarity; 2) staff rated the physical similarity of twins; and 3) an
algorithm was applied based on ponderal index, cephalic index and
finger print ridge count. In the case of discrepancies, blood samples
were drawn and analyzed with regard to blood group antigens and protein
polymorphisms.
EEG Recordings
Five minutes of resting EEG was recorded simultaneously from each
twin pair while they sat with eyes closed in adjacent, identically
configured laboratories. EEG was recorded from 5 channels (F3, F4, and
Cz referenced to linked mastoids [A1 and A2] and two bipolar
derivations T5-01, T6-02), each placed according to the standard 10-20
electroencephalographic lead placement scheme. For these analyses data
21
were additionally re-referenced off-line using a Cz reference scheme,
per the recommendations of Reid et al. (1998), who pointed out that the
various reference schemes commonly used for EEG recordings do not
correlate well. During the original recording of these EEG data, a
half-amplitude high pass filter was set at IHz and the half-amplitude
high pass filter was set at 30 Hz. Signals were digitized online at a
sampling rate of 128 Hz, at a resolution of 12 bits and subsequently
partitioned into 117 two-second epochs, overlapping by 1.5 seconds. EEG
impedances were kept below 5 kQ. Eye movements were recorded
diagonally with Ag-AgCl electrodes placed on the outer canthus and
above one eye. EOG impedances were kept below 10 kQ.
For the present analyses, all EEG data were visually screened for
artifacts, such as can be caused by body movements, muscle activation,
eyeblinks, clipped signals, etc., and epochs containing artifacts were
omitted. A Fast Fourier Transform (FFT), using a Hamming window, was
performed on each epoch, and the average power spectrum across
artifact-free epochs for each minute was subsequently obtained. Total
power within the Alpha frequency band (8-13 Hz) in the left and right
mid-frontal region (F3 and F4, respectively) was then extracted using
both Cz and Linked Mastoids reference schemes, and these values were
log transformed using the natural log (to normalize the distributions).
A measure of EEG hemispheric asymmetry (right hemisphere compared to
left hemisphere) was then be derived using the formula [ln(F4) -
ln(F3)] . The use of this asymmetry metric assumes that cortical alpha
power represents the inverse of cortical activity. Thus, higher scores
(scores greater than zero) on the left/right difference score indicate
relatively less left alpha power and, it is assumed, relatively greater
cortical activity. By contrast, lower scores (scores less than zero)
on this scale indicate relatively less right frontal alpha power and
relatively greater right frontal activity. In the derivation of this
scale, alpha power is assumed to represent the inverse of cortical
activity (see Allen, Coan, & Nazarian, 2003, for a thorough review of
this assumption).
The Multidimensional Personality Questionnaire
The Multidimensional Personality Questionnaire (MPQ) was used to
assess relationships between frontal EEG asymmetry and personality.
These scales are intended to measure Well Being, Social Potency,
Achievement, Social Closeness, Stress Reactivity, Alienation,
Aggression, Control, Harm Avoidance, Traditionalism and Absorption.
The MPQ also includes three higher order factors similar to many found
in the literature. These include Positive Emotionality (related to
Extroversion), Negative Emotionality (related to Neuroticism) and
Constraint. The scales of the MPQ, as well as the higher order factors
associated with it, show relatively low intercorrelations, consistent
with its emphasis on discriminant validity.
23
RESULTS
Results reported here are repeated across two different reference
montages. Although rational arguments have been levied in favor of one
or another reference scheme (Hagemann, Naumann, & Thayer, 2001; Raid et
al., 1998), it remains a somewhat empirical question which reference
scheme has the greatest predictive validity with respect to
motivational and emotional constructs, as well as in estimating
heritability. For this study, all analyses requiring tests of
statistical significance will include data derived from both reference
schemes. Generally, results that replicate across reference schemes
should be considered the most generalizable, being less likely to
reflect only the reference-specific ''method'' variance (cf . , Campbell &
Fiske, 1959) . By contrast, findings that are statistically significant
in only one reference montage will not be considered generalizable.
Also, because an earlier conference report (MacDhomhail et al.,
1999) suggested a sex difference in EEG heritability, all analyses will
be conducted separately for males and females. These subjects were run
as an earlier subsample of the sample considered here.
In assessing the internal consistency of the EEG data, each of the five
minutes of recorded EEG were used as scale ''items.'' With this
approach, internal consistency estimates of mid-frontal EEG asymmetry
in the Cz and LM reference schemes were .97 and .95, respectively. Mid-
frontal EEG asymmetry means ranged from between .002 to .046, depending
upon zygosity, sex and reference scheme (see Table 1). In 2X2
(zygosity by sex) ANOVAs conducted for each reference scheme, no mean
24
by zygosity. sex and reference scheme.
Males (N = = 118) Females (N = 132)
Cz LM Cz LM Monozygotic .03 (.14) .01 (.06) .02 (.09) .01 (.05) Dizygot ic .05 (.16) .01 (.07) .01 (.09) .00 (.04)
differences in zygosity, sex, or their interaction, were discovered,
all Fs 1.29, all ps .26.
In order to determine whether mid-frontal EEG asymmetry was
related to any of the scales of the MPQ, a series of zero order
correlations was calculated. The results indicated no such
relationships in males, but a few in females (see Table 2). In
particular, in females, mid-frontal EEG asymmetry was significantly
correlated with Absorption = -.24; r^^ = -.20) and Negative
Emotionality (r^.^ = -.19; r^^ = - .23) . These negative correlations
indicate that individuals who score highly on the Absorption and
Negative Emotionality scales were more right mid-frontally active at
rest. It is unclear what this means in the case of Absorption, but the
correlation with negative emotionality is in line with prevailing
theories of the affective components of behavior that frontal EEG
asymmetries are thought to index (cf. , Coan & Allen, 2003a) .
Interestingly, mid-frontal EEG asymmetry using the Cz reference scheme
is also negatively correlated with both Traditionalism and Positive
Emotionality. While it is worth noting these correlations, it is also
apparent that they do not replicate significantly across reference
schemes and are thus of dubious generalizability. Such lack of
replication suggests that these relationships are not as likely to be
25
Table 2• Zero order correlations between mid-frontal EEG asymmetry and the primary and higher order scales of the MPQ.
Males (N = 118) Females (N = 132)
Cz LM Cz LM Primary
Well Being - . 05 - .09 - . 10 - . 04 Social Potency . 02 . 02 - . 15 - . 14 Achievement . 08 . 04 - . 16 - . 10 Social Closeness . 03 .01 . 09 . 08 Stress Reaction - . 02 - . 07 - . 12 - . 13 Alienat ion - . 03 - . 06 - . 04 - . 09 Aggress ion - . 06 - . 09 - . 03 - .10 Control . 11 . 07 - . 04 - . 04 Harm Avoidance . 10 . 11 - . 01 . 00 Traditionalism . 04 . 00 - . 18* - . 16 Absorption . 08 - . 04 - . 24** - .20*
Higher Order
Positive - . 03 - . 03 - .21* - . 16 Emotionality Negative . 01 - . 08 - . 19* -.23** Emotionality Constra int . 12 . 08 - . 11 - . 09
*p < .05; **p < .01 Positive correlations indicate that higher scores on the scale are associated with relatively greater left mid-frontal activity at rest. Negative correlations indicate that higher scores on the scale are associated with relatively greater right mid-frontal activity at rest.
replicated in future studies. Nevertheless, it is also apparent that
the correlations associated with them are not significantly different
from those of the other correlated scales. Ultimately, all correlated
scales will be considered in subsequent analyses.
Heritability of Frontal EEG Asymmetry
Falconer's estimate. Two statistical methods were used to assess
the heritability of frontal EEG asymmetry. The first of these was
simply to compute one-way random intra-class correlations among mono
zygotic (MZ) twins and di-zygotic (DZ) twins separately for use in
26
calculating a rough estimate of heritability using the Falconer's
estimate, h^ = 2 (r„j. - r^z) . On occasion, intra-class correlations are
estimated to be less than zero. In such instances, the correlation is
generally assumed to be zero, and this assumption was made in the
analyses discussed here. With this in mind, it was impossible to
estimate EEG asymmetry heritability in males using the Cz reference
scheme, as both intraclass correlations (MZ and DZ twins) were negative
and assumed to be zero. Using the LM reference, intra-class
correlations for MZ and DZ male twins were .11 and 0, respectively,
yielding a Falconer's estimate of .21. In females, using the Cz
reference scheme, intraclass correlations for MZ and DZ twins were .24
and 0, respectively, yielding a Falconer's estimate of .4 9. Using the
LM reference, the intraclass correlations for MZ and DZ twins were .13
and 0 respectively, yielding a Falconer's estimate of .26.
Latent Variable Modeling. In addition to Falconer's estimate, a
Maximum Likelihood (ML) latent variable modeling approach was applied,
using path coefficient estimates to estimate this same heritability
parameter mentioned above. In all cases, Mx (Neale, 1997), a
statistical software package for latent variable modeling commonly used
in behavior genetics research, was used to estimate path coefficients,
variance components and model fit statistics.
Because MZ twin intraclass correlations estimated for EEG were in
all but one case more than double the magnitude of those estimated for
DZ twins, it is likely that the EEG asymmetries are influenced by
27
Table 3. Fit statistics for ACE and APE models, by sex and reference scheme.
df P-value AIC RMSEA
Males (N=118)
Cz
LM a +d^+e^
a +d^+e^
8 . 71 8 .71
8 . 84 8 . 84
Females (N = 132) Cz
LM a^+d^+e^
a +d^+e^
2 . 71 2 . 0 8
2 . 8 0
2 . 54
, 03 , 03
. 03 , 03
,44 . 56
,43 ,47
2 . 71 2 . 71
2 . 84 2 . 84
•3.29 •3 . 92
•3 . 24 •3.46
. 18
. 18
.20
. 2 0
. 05
. 04
. 06
. 06
In thistable, represents additive genetic variance, ? represents common environmental variance, d^ represents non-additive genetic variance, and = unique environmental variance.
nonadditive genetic effects as much or more so than by additive ones^.
With this in mind, covariance matrices, representing MZ and DZ twins
separately, were fit to an ACE and an ADE model. In ACE models, three
components of variance thought to influence a given variable are
estimated: an '"A'' factor, representing additive genetic influences, a
Additive genetic effects occur when alleles simply *'add up'' in the ultimate determination of some trait predisposition or behavior. Nonadditive effects occur when the effects of one or more alleles are dependent upon the presence or absence of other alleles. Such nonadditive effects can result from genetic dominance, or from epistasis. Genetic dominance -refers to situations where on allele appears to dominate another at some specific locus. Epistasis refers to the nonadditive interaction of alleles at different loci. In either type of nonadditive genetic influence, MZ twins will be highly similar, whereas DZ twins may be disproportionately dissimilar. Estimates of heritability derived from a combination of additive and nonadditive genetic effects are referred to as estimates of broad heritability.
28
''C' factor, representing the effects of common environment between
siblings, and an ''E" factor representing unique environmental
influences. In an ADE model the A and the E factors remain, but the C
factor is replaced with a ''D'' factor representing non-additive
variance. Table 3 shows fit statistics for these models of genetic and
environmental influences on mid-frontal EEG asymmetry. Interestingly,
male twin data did not fit either model in either reference scheme.
Thus, heritability estimates for male twins are not reported here. By
contrast, all models fit well to the female twin data, 2.80 (df =
3), p .43, AIC -3.24, and RMSEA .06.^ According to the ACE model,
additive genetic effects account for 14% and 4% of the trait variance
in Cz and LM derived mid-frontal EEG asymmetry, respectively. By
contrast, according to the ADE model, additive genetic effects account
for approximately zero percent of the variance in both reference
In general, latent variable model *'fit" is determined by the degree to which observed data deviates from the specified model. Thus, when
the ̂ statistic is large and statistically significant, the model is thought to fit poorly, because the observed data are significantly
different from the model specification. In addition to the statistic, two other useful fit statistics are reported here. These are Akaike's Information Criterion (AIC) and the Root Mean Square Error of Approximation (RMSEA). The AIC statistic includes a consideration of the number of unknown parameter estimates in its calculation, providing by extension a consideration of model parsimony. Relatively poor model fit is indicated by higher AIC values while lower values indicate relatively good model fit (Loehlin, 19 98). The RMSEA statistic is thought to be relatively independent of sample size by virtue of being a population-based index. It, too, is sensitive to model parsimony. A perfect model fit is indicated by an RMSEA of zero. An RMSEA of less than .05 is though to indicate an '"excellent'' fit to the data, an RMSEA of less then .10 is thought to indicate '*good'' fit, and ''one would not want to employ'' a model with an RMSEA greater than .10 (Loehlin, 1998, pp. 76-77)
schemes, while nonadditive genetic effects account for approximately
22% and 9% of the trait variance in Cz and Lm derived mid-frontal EEC
asymmetry, respectively. Ultimately, the Cz reference ADE model (see
Figure 1) was judged the most promising for additional bivariate
analyses of those compared. This was because 1) the estimate of
heritability increased from the additive ACE to the nonadditive ADE Cz
reference scheme models and 2) the Cz ADE model fits nominally (though
not significantly statistically) better than its LM counterpart. (This
last criterion is relevant only in that it is not inconsistent with a
preference for the Cz model.) Thus, in subsequent bivariate genetic
analyses, only female data from the Cz reference scheme will be used.
As an additional check on the data reported here, alpha power
heritability was estimated for each hemisphere separately (left mid-
frontal or F3 and right mid-frontal or F4). Because past research
(Stassen et al., 1998; Stassen et al., 1988) has provided very little
evidence of effects of common environment on EEG power spectra, and
because an ADE model was the optimal model for EEG asymmetry, an ADE
model was fit to mid-frontal alpha power for both F3 and F4 separately,
independent of sex (both male and female data were included in this
model). Both models fit very well, ')^ 3.82 (df = 3), p .28, AIC
2.78, and RMSEA .06. Further, variance attributable to additive
genetic, nonadditive genetic, and nonshared environment were in each
case estimated to be .75, 0.00 and .25, respectively. These estimates
are virtually identical to those reported elsewhere in the
30
Figure 1, Heritability of Midfrontal EEG Asymmetry. ADE model path coefficients and variance proportions for mid-frontal EEG asymmetry in females, using the Cz reference scheme. A represents additive genetic effects, D represents nonadditive genetic effects and E represents nonshared environmental effects. This model demonstrated an excellent fit
to the observed data, with = 2.08 (df =3), p = .56, AIC = -3.92, RMSEA = .04.
literature (Stassen et al., 1998; Stassen et al., 1988). Such
replication lends credibility to the data underlying asymmetry
estimates reported above.
The Heritability of Absorption, Traditionalism, Negative Emotionality,
and Positive Emotionality
To establish whether Positive Emotionality, Negative
Emotionality, Traditionalism and Absorption are good candidates for a
test of the Cholesky hypothesis, it is necessary that these variables
Proportions of Variance A = .00 D = .22 E = .78
F4-F3
0.88
demonstrate heritability in addition to their established correlational
relationship with mid-frontal EEG asymmetry. To this end, and keeping
in mind that the relationship between these personality variables and
mid-frontal EEG asymmetry was found only in females, covariance
matrices among MZ and DZ female twins were for both variables fit to
ACE and ADE models, just as with EEG asymmetry. Absorption data did not
fit to the models outlined.
In the case of Traditionalism, both the ACE and ADE models
demonstrated excellent fits to the observed data, 3.34 (df = 3), p
.34, AIC -2.67, and RMSEA .04. According to the ACE model,
additive genetic effects accounted for approximately 25% of the trait
variance, while common environmental effects accounted for the 29% and
unique environmental effects accounted for 46% (see figure 2). By
contrast, in the ADE model, additive genetic effects accounted for
approximately 56% of the trait variance, unique environmental effects
accounted for 44%; nonadditive genetic effects accounted for no
variance at all.
In the case of Positive Emotionality, the ACE model did not fit,
but the ADE model did fit, = 4.32 (df =3), p = .23, AIC < -1.68, and
RMSEA < .10. According to this ADE model, additive genetic effects
accounted for approximately 21% of the trait variance in Positive
Emotionality, nonadditive genetic variance accounted for approximately
64% and unique environmental effects accounted for approximately 15%
(see Figure 3) .
32
Figure 2, Heritability of Traditionalism. ACE model path coefficients and variance proportions for Traditionalism in females, using the Cz reference scheme. A represents additive genetic effects, C represents common environmental effects and E represents non-shared environmental effects. This model demonstrated an excellent fit to the observed
data, with /= 2.57 [df = 4 ) , p = . 4 6 , A I C = - 3 . 4 1 , R M S E A = . 0 3 .
In the case of Negative Emotionality, the ADE model did not fit, and
the ACE model fit well, = 3.07 {df =3), p = .38, AIC < -2.93, and
RMSEA < .07. According to the ACE model, however, additive genetic
effects accounted for approximately 41% of the trait variance in
Negative Emotionality, while unique environmental effects accounted for
the remaining variance; common environmental effects accounted for no
variance at all. Thus, data from this variable were fit to an AE
model. The AE Negative Emotionality model demonstrated a substantial
Proportions of Variance A = .25 C = .29 E = .46
TRAD
0.68
33
Figure 3, Heritability of Positive Emotionality. ADE model path coefficients and variance proportions for Positive Emotionality in females, using the Cz reference scheme. A represents additive genetic effects, D represents nonadditive genetic effects and E represents nonshared environmental effects. This model demonstrated an good fit to
the observed data, with = 4.32 (df =3), p = .23, AIC < -1.68, and RMSEA < .10.
improvement in model fit, 2^= 4.43 {df = 4 ) , p = . 3 5 , A I C = - 3 . 5 7 ,
RMSEA = .05 (see Figure 4). Thus, it appears that Traditionalism,
Positive Emotionality and Negative Emotionality are each candidates for
testing the Cholesky hypothesis with mid-frontal EEC asymmetry.
The Cholesky Hypothesis
Pos itive Emotionality and Traditional ism. The phenotypic
correlations between midfrontal EEG asymmetry (derived using a Cz
Proportions of Variance A = .21 D = .64 E = .15
PEM
0.39
34
Figure 4, Heritability of Negative Emotionality. AE model path coefficients and variance proportions for Negative Emotionality in females, using the Cz reference scheme. A represents additive genetic effects, and E represents non-shared environmental effects. This model
demonstrated an excellent fit to the observed data, with = 4.43 [df = 4), p = .35, AIC = -3.57, RMSEA = .05.
reference) and both Positive Emotionality and Traditionalism scores
were modeled in terms of their genetic and environmental constituents
using Cholesky models. In these models, genetic and environmental
effects on each of two variables, as well as the relationships between
those two variables, can be estimated. Unfortunately, these parameters
could not be estimated for frontal EEG asymmetry in the cases of
Traditionalism and Positive Emotionality, because in neither case did
the bivariate Cholesky model fit the observed data. Models attempted
included the ACE, ADE, AE and DE models. Ultimately, the relationships
between midfrontal EEG asymmetry and both Traditionalism and Positive
Emotionality remain uncertain, both in terms of their reliable
phenotypic manifestations (because they did not replicate across
reference schemes) and in terms of their bivariate heritabilities.
O /"
Proportions of Variance A = .41 E = .59
NEM
Negative Emotionality. A test of the Cholesky hypothesis, that
the phenotypic correlation between two trait variables is attributable
to shared genetic influences, presents some logical difficulties at the
outset in the case of mid-frontal EEG asymmetry and Negative
Emotionality. A significant phenotypic correlation between these two
variables was present in both reference schemes, suggesting that the
relationship is reliable, but latent variable models of each individual
trait variable are inconsistent in terms of the estimated sources of
genetic variance. In the case of mid-frontal EEG asymmetry, genetic
effects appear to be primarily if not entirely nonadditive; in the case
of Negative Emotionality, genetic effects appear to be almost entirely
additive in nature. Both models attribute sizable effects to unique
environmental influences and virtually no effects to common
environment. Thus, the ADE bivariate model appears to be the most
theoretically tenable. Bivariate covariance matrices for both MZ and
DZ twins were indeed fit to the ADE model, which demonstrated an
excellent fit to the observed data, 2^ = 11.47 {df = 11), p = .41, AIC =
-10.53, and RMSEA = .04. According to this model (Figure 5), the
proportion of variance attributable to additive genetic effects
was .01, while the proportion of variance attributable to nonadditive
genetive effects (d^g) was .21, resulting in a total heritability of
mid-frontal EEG asymmetry of .22. The heritability of Negative
Emotionality is comprised of additive genetic influences shared with
mid-frontal EEG asymmetry (a^„^ = .39), additive genetic influences
specific to Negative Emotionality (a^„^ = .00), nonadditive genetic
36
influences shared with mid-frontal EEG asymmetry (d^„c = -02), and
nonadditive genetic influences specific to Negative Emotionality {d^ns =
.00), resulting in a total Negative Emotionality heritability {h^„) of
.41. Further, the proportion of variance in trait mid-frontal EEG
asymmetry attributable to nonshared environmental effects (e^^) was .78.
The same proportion for Negative Emotionality was comprised of
nonshared environmental effects common to mid-frontal EEG asymmetry
= .04), and nonshared environmental effects specific to Negative
Emotionality = .55), summing to a total estimate of nonshared
environmental influence {e^„) of .59.
From these indices, it is further possible to estimate a number
of additionally useful proportions (of., Jockin, McGue, & Lykken,
1996). The proportion of the heritability of Negative Emotionality that
can be explained by the additive genetic factors common to mid-frontal
EEG asymmetry (r^^) can be estimated by / hj^. Similarly, the
proportion due to nonadditive genetic factors common to mid-frontal EEG
asymmetry can be estimated by / h^)^, and the proportion of
variance in nonshared environment that can be explained by nonshared
environmental effects common to mid-frontal EEG asymmetry (r^g) can be
estimated by Following these calculations, was estimated
to be .94, was estimated to be .05 and was estimated to be .07.
It is further possible to calculate an estimate of the proportion
of the covariance between two traits attributable to genetic
contributions (Jockin et al., 1996). This proportion of bivariate
37
Figure 5, Midfrontal EEG Asymmetry/Negative Emotionality Cholesky Model. ADE model path coefficients and variance proportions for Negative Emotionality in females, using the Cz reference scheme. A represents additive genetic effects, D represents nonadditive genetic effects and E represents non-shared environmental effects. For the path coefficients, subscript e represents effects specific to mid-frontal EEG asymmetry, subscript nc represents effects on Negative Emotionality from sources shared with mid-frontal EEG asymmetry, subscript ns represents effects specific to Negative Emotionality, and subscript n represents the total effects (specific and common) on Negative Emotionality. From these estimates it was possible to calculate or the proportion of heritability in Negative Emotionality attributable to additive genetic factors also underlying mid-frontal EEG asymmetry, r^j,, the proportion attributable to nonadditive genetic factors, and the proportion of unique environmental influences on Negative Emotionality attributable to unique environmental influences also underlying mid-frontal EEG asymmetry. It was also possible to calculate the proportion of covariance between mid-frontal EEG asymmetry and Negative Emotionality attributable to shared genetic (both additive and nonadditive) influences. This model demonstrated excellent fit to the observed
data, with 2^= 11.47 {df = 11), p = .41, AIC = -10.53, RMSEA = .04.
Proportions of Variance
Additive genetic effects a\ = .01
• nc *39 1 2 _ -in = .00 J ~
Nonadditive genetic effects = .21
EEG NEM
= .94 = .22 /o = .05 /i^„ = .41 /e = .07 /i^i = .42
Unique environmental effects = .78
38
heritability can be estimated by the equation specified in Figure 6.
With this equation, a bivariate heritability again, the proportion
of the covariance between mid-frontal EEG asymmetry and Negative
Emotionality attributable to genetic factors) estimate of .42 was
obtained. This estimate suggests that 42% of the relationship between
mid-frontal EEG asymmetry and Negative Emotionality is due to
underlying genetic factors.
Figure 6, Bivariate Heritability Equation. Equation used for determining the bivariate heritability of the phenotypic relationship between midfrontal EEG asymmetry and Negative Emotionality.
39
DISCUSSION
This is the first study to estimate the relative contributions of
genetic and environmental influences on trait variance in mid-frontal
EEG asymmetry. Further, it is the first study to estimate the degree
to which the phenotypic relationship between mid-frontal EEG asymmetry
and a paper and pencil personality test, in this case Negative
Emotionality as measured by the MPQ, is due to common genetic versus
environmental influences. Of initial interest was the fact that males
and females appear to differ in the degree to which mid-frontal EEG
asymmetry is heritable, with males showing virtually zero heritability
and females showing modest heritability estimates (in the range of
20%). Of further interest was that female mid-frontal EEG asymmetry
heritability was best accounted for by nonadditive genetic effects, a
fact suggested also by the large discrepancies between mono and
dizygotic twin intraclass correlation coefficients. What follows is a
discussion of the sex differences in the heritability of mid-frontal
EEG asymmetry, the relative contributions of additivity and nonaddivity
to trait variance in frontal EEG asymmetry, and the interpretation of
the phenotypic relationship between mid-frontal EEG asymmetry and
Negative Emotionality
Sex Differences in the Heritability of Frontal EEG asymmetry
While no clear hypothesis was stated with regard to sex
differences in the heritability of mid-frontal EEG asymmetry, such a
difference was not entirely unanticipated. A previous conference
40
report {MacDhomhail et al., 1999) noted a similar sex difference in a
portion of the sample reported on here. The critical question regards
the reason that such a sex difference might exist. One possibility is
that the difference is the result of epigenetic effects, where the same
genes are impacting males and females in different ways or in differing
magnitudes. Such effects can result from the interaction between
certain genes and sex hormones, for example, or from sex-specific
chromosomal differences.
Another possibility is that the genes underlying female mid-
frontal EEG asymmetry heritability are expressing themselves no
differently than they do in males, but that unique environmental
pressures are dominating male trait mid-frontal EEG variance in ways
that are relatively unrelated to the expression of mid-frontal EEG
asymmetry-relevant genes. While the data under consideration in this
study are not sufficient for supporting or refuting any of these
possibilities, prevailing stereotypes of social attitudes regarding
male and female emotional behavior might be consistent with the later
explanation. For example, male emotional behavior is often thought to
be more constrained than female emotional behavior, particularly with
regard to the emotions associated with right mid-frontal EEG activity,
such as fear and sadness (Fabes & Martin, 1991) . Unfortunately, this
possibility is based on what may be a popular stereotype with little
empirical support, and in any case may involve a great deal of
complexity in determining the particular aspects of emotion, emotion
regulation and emotional personality that may be implicated in reliable
41
sex differences. For example, though some have reported sex
differences in subjective experience reports (e.g., Barrett, Lane,
Sechrest, & Schwartz, 2000) , the literature on more objectively
measured emotional behavior has produced inconsistent results, with
some studies finding few or no sex differences (Barrett, Robin,
Pietromonaco, & Eyssell, 1998; Gross & Levenson, 1993) and others
finding sex differences consistent with many prevailing stereotypes
(van der Bolt & Tellegen, 1995). For example, van der Bolt and
Tellegen (19 95) found evidence that females are generally more ''open''
to dysphoric emotions than males are. It may be that this difference
reflects a cultural (and by extension, environmental) constraint,
whereby males are influenced to regulate their emotions more according
to environmental cues than by temperamental emotional tendencies. This
could, in theory, limit the degree to which male trait mid-frontal EEG
asymmetry is controlled by genetic influences. Such questions await
further exploration and study.
Mid-Frontal EEG asymmetry and the MPQ
In this study, a relationship between mid-frontal trait EEG
asymmetry and the Negative Emotionality scale of the MPQ was identified
and explored. Negative Emotionality is thought to be high in
individuals who have a low general threshold for negative emotions.
Such individuals are thought to be highly sensitive to stress, and are
likely to view the world as a dangerous or threatening place (Tellegen,
1985). It is interesting that this relationship was significant only
42
in females in the present sample. In past studies, relatively greater
right frontal EEG asymmetry has been associated with Negative
Affectivity as measured by the Positive and Negative Affect Schedule
(PANAS) in females (Tomarken, Davidson, Wheeler, & Doss, 1992).
Interestingly, in tests of this association in males, relatively
greater left frontal EEG asymmetry was associated with greater Positive
Affectivity, but relatively greater right frontal EEG activity was not
associated with greater Negative Affectivity (Jacobs & Snyder, 1996).
In light of past studies, and given the predictions of the
approach/withdrawal model of anterior EEG asymmetry and emotion, the
association between mid-frontal EEG asymmetry and Negative Emotionality
is readily interpretable. Less certain is the association with
Absorption, Positive Emotionality and Traditionalism. Because
Absorption loads strongly on Positive Emotionality (e.g., Krueger,
2000), it may be tempting to attribute the weak association between
mid-frontal EEG asymmetry and Positive Emotionality primarily to the
more robust association with Absorption. However, a perusal of the
remaining constituents of Positive Emotionality suggests that both
Social Potency and Achievement are weakly associated with mid-frontal
EEG asymmetry as well. What is difficult about these relationships,
weak as they are, is that they are the opposite of what would be
predicted by the approach/withdrawal model, and indeed run counter to a
large portion of the literature on anterior EEG asymmetry and
personality. The same relationship is weakly evident in the case of
Traditionalism. While an association between relatively greater right
43
mid-frontal EEG asymmetry and Traditionalism is not immediately
obvious, it does' not run counter to the approach/withdrawal model the
way absorption and positive emotionality do. Indeed, traditionalism
has been associated with the higher order factor of Constraint, and is
related to tendencies to control one's environment and avoid harm.
Such characteristics are not inconsistent with the trait withdrawal
orientation that relatively greater right anterior activity is thought
to index.
Nevertheless, the unanticipated relationships between right
frontal activity. Absorption and Positive Emotionality merit further
consideration. It is possible that these relationships reflect similar
sex differences in anterior EEG asymmetry identified elsewhere. For
example, in past research, females who are relatively more left
frontally active at rest are more temperamentally defensive, while the
opposite pattern is true of males (Kline et al. , 1998). Adding to the
complexity of this sex difference, other studies have found that the
female relationship between left frontal activity and high
defensiveness is particularly strong when those females are in the
presence of males (Kline, Blackhart, & Joiner, 2002) . Further, women
have been found to differ in men in the pattern of anterior activity
associated with negative moods resulting from EEG hookup procedures.
In men, individuals who responded to EEG hookup with more negative mood
were more right frontally active at rest. The opposite was true of
women, who were more left frontal active if they responded to EEG
hookup with more negative mood (Blackhart, Kline, Donohue, LaRowe, &
44
Joiner, 2002). In a study of state changes in frontal EEG asymmetry
during different motivational conditions, men were found to become more
left frontally active during moments of high expectation, while women
were found to become more left frontally active during moments of low
expectation (Miller & Tomarken, 2001). It may be critical that in the
latter study, the proper interpretation is that "relative left
midfrontal asymmetry indexed increases in the likelihood of success in
males but [...] decreases in relative left midfrontal asymmetry were
related to greater chances of successful outcomes in females'' (Miller
& Tomarken, 2001, p. 509). These researchers speculated that such sex
differences may reflect the interaction between implicated brain
regions and different sex hormones or may be related to other sex
differences, such as differences in tendencies toward emotional
rumination and emotional coping styles (e.g., Finkel & McGue, 1997) .
Particularly interesting is the possibility that the sex differences in
the relationship between midfrontal EEG asymmetry and these personality
characteristics are mediated by the same factors that underlie the sex
difference in midfrontal EEG asymmetry heritability. As new research
replicates these sex differences and uncovers new ones, it will be
increasingly important to identify these mediators.
Interpreting the Cholesky Model. It appears that the
relationship between frontal EEG asymmetry and negative emotionality is
1) small, but reliable, 2) approximately 40% attributable to common
genetic effects and 3) mediated through common additive genetic
effects. This last point is troublesome because additive genetic
45
effects account for very little overall trait variance in mid-frontal
EEG asymmetry per se (probably less than 1%). On the other hand, this
may reflect the very small effect size of the phenotypic relationship
between midfrontal EEG asymmetry and NEM, which is approximately .04 in
the Cz reference scheme. Thus, the proper way to interpret the
Cholesky Model may be that common genetic effects exert little
influence on mid-frontal EEG per se, but great influence on NEM, and in
any case largely account for the relationship between mid-frontal EEG
asymmetry and NEM.
Methodological Constraints
This study represents an important '"first look'' at the
heritability of asymmetries in anterior brain activity. Because with
these data it was also possible to investigate the heritability of the
relationship between midfrontal EEG asymmetry and affective personality
measures, it is also of important heuristic value to the field. Future
investigators should embed theoretically grounded measures into
research of this type in an effort to replicate and extend the field's
understanding of sex differences in frontal EEG asymmetry as well as
the variables that mediate and moderate those differences . In any
•case, methodological constraints limit the conclusions that can be made
from this study.
The General!zability of Trait BEG Asymmetry Measurement. First,
while frontal EEG asymmetry always shows high internal consistency,
it's test-retest reliability has been modest (e.g., Tomarken, Davidson,
46
Wheeler, & Kinney, 1992). Generalizability analyses of frontal EEG
asymmetry suggest that trait measures are highly susceptible to
interference attributable to state and occasion sources of variance
(Coan & Allen, 2003c) . These researchers estimated that this
interference could alone account for much of the inconsistency in the
literature on frontal EEG asymmetry, and used the Spearman-Browne
prophecy formula to estimate that trait variance in frontal EEG
asymmetry would be optimally estimated from four separate occasions of
measurement (Coan & Allen, 2003c). It is possible that if such a
procedure had been used in this case the pattern of heritability, as
well as the pattern of relationships with the scales of the MPQ, could
look different. In particular, more reliable measurement of trait
variance in frontal EEG asymmetry could result in greater heritability
estimates and a larger effect size in the relationships between frontal
EEG asymmetry and the MPQ scales. This might be particularly true in
the case of heritability estimates, since non-trait variance
interfering with trait measurement would count as unshared
environmental effects.
Another consideration concerns the generalizability of state
changes in frontal EEG asymmetry in response to emotional stimuli
(e.g., Coan, Allen, & Harmon-Jones, 2 001). For example, Coan and
Allen (2003c) estimated the generalizability of such state
manipulations to be approximately .97, which is extraordinarily high
for most psychophysiological measures associated with emotion. In
future studies of the heritability of frontal EEG asymmetry, it will be
47
important to identify the heritability of such state changes, as well
as the heritability of the interaction between such state changes and
resting trait levels.
The need for more EEG sites. Another limitation of the current
study concerns the number of EEG sites from which asymmetry data could
be derived. In this case, only the midfrontal region could be
assessed, but in previous studies, anterior asymmetry effects are also
seen in the lateral frontal, frontal-temporal-central, anterior
temporal and frontal-central regions of the scalp. It is possible that
the heritability of such anterior asymmetries varies somewhat by
particular region. Future researchers should endeavor to acquire data
from all anterior regions implicated in this literature.
The acquisition of EEG data from additional sites would confer
other advantages as well. For example, it will be important in future
studies to compare the heritability of frontal EEG asymmetries to the
heritability of asymmetries elsewhere on the head. This will be
particularly important with regard to the relationships between such
asymmetries and measures of emotion and personality. Further, the
acquisition of additional sites will make it possible to estimate
asymmetry data using yet another reference scheme, such as an average
reference. The addition of such a reference could shed greater light
on the generalizability of the heritability estimates derived here, as
well as the estimates of the magnitude of the relationship between
frontal EEG asymmetry and Negative Emotionality.
Sample size. Finally, a potential limitation of the current
study regards the size of the sample involved. By comparison with
other studies of frontal EEG asymmetry, the size of the current sample
is more than adequate. Indeed, it is substantially larger than most.
The models used here in estimating heritabilities, however, ordinarily
include larger samples, often numbering in the thousands of
participants. This is particularly true when estimating more complex
models, such as the Cholesky model described here, in part because the
probability of rejecting a complex latent variable model that is in
fact wrong is partially a function of statistical power. That is, it
is potentially easier to fit a model (according to the statistic)
with a relatively small sample size. Fortunately, the RMSEA estimate,
included as a fit statistic in all models reported here, is, by virtue
of being a population based estimate, less sensitive to sample size
than other fit indices. In sum, while it would be ideal to have
analyzed a larger sample of twins in this case, that ideal does not
render the current analyses by default incorrect or untenable (see
Loehlin, 199 8).
Concluding Remarks
Ultimately, such methodological constraints should inspire
caution in interpreting the results reported here. Nevertheless, this
study provides a valuable first look at the relative contributions of
genetic and environmental effects on the development of trait frontal
EEG asymmetries. The relationships reported here between frontal EEG
49
asymmetry and negative emotionality, as well as the sex differences
identified here, should also serve as useful heuristics in the
development of future similar studies.
A wide variety of studies implicate frontal EEG asymmetry as an
indicator of both trait predispositions to respond in emotionally
characteristic ways, and of specific emotional states. As researchers
come to understand how the brain regions indicated by these cortical
measures both affect and are affected by emotional environmental
stimuli, it will become increasingly important to identify the degrees
to which patterns of responding associated with these regions are due
to genetic versus environmental effects. The vast and growing body of
work in the field of EEG asymmetry, as well as the data reported here,
should encourage researchers to explicate such patterns and
relationships.
50
REFERENCES
Allen, J. J., lacono, W. G., Depue, R. A., & Arbisi, P. (1993). Regional electroencephalographic asymmetries in bipolar seasonal affective disorder before and after exposure to bright light. Biological Psychiatry, 33, 642-646.
Allen, J. J., lacono, W. G., Depue, R. A., & Arbisi, P. (1993). Regional electroencephalographic asymmetries in bipolar seasonal affective disorder before and after exposure to bright light. Biological Psychiatry, 33, 642-646.
Allen, J. J. B., Coan, J. A., & Nazarian, M. (2003). What's the difference?: Issues and assumptions in the use of difference scores and other metrics of anterior brain asymmetry in emotion. Submitted to the special issue of. Biological Psychology.
Allen, J. J. B., Urry, H. L., Hitt, S. K., & Coan, J. A. (2003). The stability of resting frontal electroencephalographic asymmetry in depress ion. Manuscript submitted for publication.
Anderson, N. B., & Scott, P. A. (1999). Making the case for psychophysiology during the era of molecular biology. Psychophysiology, 36, 1-13.
Baehr, E., Rosenfeld, J. P., Baehr, R., & Earnest, C. (1998). Comparison of two EEG asymmetry indices in depressed patients vs. normal controls. International Journal of Psychophysiology, 31, 89-92.
Barrett, L. F., Lane, R. D., Sechrest, L., & Schwartz, G. E. (2000). Sex differences in emotional awareness. Personality & Social Psychology Bulletin, 26, 1027-1035.
Barrett, L. F., Robin, L., Pietromonaco, P. R., & Eyssell, K. M. (1998) . Are women the ''more emotional'' sex? Evidence from emotional experiences in social context. Cognition & Emotion, 12, 555-578 .
Blackhart, G. C., Kline, J. P., Donohue, K. F., LaRowe, S. D., & Joiner, T. E. (2002) . Affective responses to EEG preparation and their link to resting anterior EEG symmetry. Personality & Individual Differences, 32, 167-174.
Brown, G. W. (1998) . Genetic and population perspectives on life events and depression. Social Psychiatry & Psychiatric Epidemiology, 33, 363-372 .
51
Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological
Bulletin, 56, 81-105.
Cates, D. S., Houston, B. K., Vavak, C. R., Crawford, M. H., & et al. (1993). Heritability of hostility-related emotions, attitudes, and behaviors. Journal of Behavioral Medicine, 16, 237-256.
Coan, J. A., & Allen, J. J. B. (2003a). The state and trait nature of frontal EEC asymmetry in emotion. In K. Hugdahl & R. J. Davidson (Eds.), The Asymmetrical Brain (pp. 565-615). Cambridge, MA: MIT Press.
Coan, J. A., & Allen, J. J. B. (2003b). Frontal EEG asymmetry and the behavioral activation and inhibition systems. Psychophysiology, 40, 106-114.
Coan, J. A., & Allen, J. J. B. (2003c). Frontal EEG Asymmetry as a Moderator and Mediator of Emotion. Submitted to the special issue of. Biological Psychology.
Coan, J. A., & Allen, J. J. B. (in press). Varieties of emotional experience during voluntary emotional facial expressions. Annals of the New York Academy of Sciences.
Coan, J. A., Allen, J. J. B., & Harmon-Jones, E. (2001). Voluntary facial expression and hemispheric asymmetry over the frontal cortex. Psychophysiology, 3 8, 912-925.
Coccaro, E. F., Bargeman, C. S., Kavoussi, R. J., & Seroczynski, A. D. (1997). Heritability of aggression and irritability: A twin study of the Buss-Durkee aggression scales in adult male subjects. Biological Psychiatry, 41, 273-284.
Coccaro, E. F., Bergeman, C. S., & McClearn, G. E. (1993) . Heritability of irritable impulsiveness: A study of twins reared together and apart. Psychiatry Research, 48, 229-242.
Davidson, R. J. ( 1998) . Affective style and affective disorders: Perspectives from affective neuroscience. Cognition & Emotion, 12, 307-330.
Davidson, R. J., Coe, C. C. , Dolski, I., & Donz alia, B. (1999). Individual differences in prefontal activation asymmetry predict natural killer cell activity at rest and in response to challenge. Brain, Behavior, & Immunity, 13, 93-108.
Davidson, R. J., Marshall, J. R., Tomarken, A. J., & Henriques, J. B. (2000). While a phobic waits: regional brain electrical and
52
autonomic activity in social phobics during anticipation of public speaking. Biological Psychiatry, 47, 85-95.
Dawson, G., Frey, K., Panagiotides, H., Yamada, E., Hessl, D., & ©sterling, J. (1999) . Infants of depressed mothers exhibit atypical frontal electrical brain activity during interactions with mother and with a familiar, nondepressed adult. Child Development, 70, 1058-1066.
Debener, S., Beauducel, A., Nessler, D., Brocke, B., Heilemann, H., & Kayser, J. (2000) . Is resting anterior EEG alpha asymmetry a trait marker for depression? Findings for healthy adults and clinically depressed patients. Neuropsychohiology, 41, 31-37.
Depue, R. A., & Collins, P. F. (1999). Neurobiology of the structure of personality: Dopamine, facilitation of incentive motivation, and extraversion. Behavioral & Brain Sciences, 22, 491-569.
Dionne, G., Tremblay, R., Boivin, M., Laplante, D., & Perusse, D. (2003). Physical aggression and expressive vocabulary in 19-month-old twins. Developmental Psychology, 39, 261-273.
Fabes, R. A., & Martin, C. L. (1991). Gender and age stereotypes of emotionality. Personality & Social Psychology Bulletin, 17, 532-540 .
Field, T., Fox, N., Pickens, J., & Nawrocki, T. (1995) . Relative right frontal EEG activation in 3 - to 6-month-old infants of depressed'' mothers. Developmental Psychology, 31, 358- 363.
Finkel, D., & McGue, M. (1997). Sex differences and nonadditivity in heritability of the Multidimensional Personality Questionnaire Scales. Journal of Personality & Social Psychology, 72, 929-938.
Fowles, D. C. (1994) . A motivational theory of psychopathology. In W. D. Spaulding (Ed.), Integrative views of motivation, cognition, and emotion. Nebraska symposium on motivation (Vol. 41, pp. 181-238). Lincoln, NE: University of Nebraska Press.
Fox, N. A., Rubin, K. H., Calkins, S. D., Marshall, T. R., Coplan, R. J., Porges, S. W. , Long, J. M., & Stewart, S. (1995) . Frontal activation asymmetry and social competence at four years of age. Child Development, 66, 1770-1784.
Fyer, A. J. (1993) . Heritability of social anxiety: A brief review. Journal of Clinical Psychiatry, 54, 10-12.
Ghodsian-Carpey, J., & Baker, L. A. (1987). Genetic and environmental influences on aggression in 4- to 7-year-old twins. Aggressive Behavior, 13, 173-186.
53
Gillespie, N. A., Zhu, G., Heath, A. C., Hickie, I. B., & Martin, N. G. (2000) . The genetic aetiology of somatic distress. Psychological Medicine, 30, 1051-1061.
Gotlib, I. H., Ranganath, C., & Rosenfeld, J. P. (1998). Frontal EEG alpha asymmetry, depression, and cognitive functioning. Cognition & Emotion, 12, 449-478.
Gross, J. J., & Levenson, R. W. (1993). Emotional suppression: Physiology, self-report, and expressive behavior. Journal of Personality & Social Psychology, 64, 970-986.
Hagemann, D., Naumann, E., & Thayer, J. F. (2001). The quest for the EEG reference revisited: A glance from brain asymmetry research. Psychophysiology, 38, 847-857.
Hagemann, D., Naumann, E., Thayer, J. F., & Bartussek, D. (2002). Does resting electroencephalograph asymmetry reflect a trait?: An application of latent state-trait theory. Journal of Personality & Social Psychology, 82, 619-641.
Happonen, M., Pulkkinen, L., Kaprio, J., Van der Meere, J., Viken, R. J., & Rose, R. J. (2002). The heritability of depressive symptoms: Multiple informants and multiple measures. Journal of Child Psychology & Psychiatry & Allied Disciplines, 43, 471-480.
Harmon-Jones, E., & Allen, J. J. B. (1997). Behavioral activation sensitivity and resting frontal EEG asymmetry; covariation of putative indicators related to risk for mood disorders. Journal of Abnormal Psychology, 106, 159-163.
Harmon-Jones, E., & Allen, J. J. B. (1998). Anger and frontal brain activity: EEG asymmetry consistent with approach motivation despite negative affective valence. Journal of Personality & Social Psychology, 74, 1310-1316.
Harmon-Jones, E., & Sigelman, J. (2001). State anger and prefrontal brain activity: Evidence that insult-related relative left-prefrontal activation is associated with experienced anger and aggression. Journal of Personality & Social Psychology, 80, 797-803 .
Heller, W., Nitschke, J. B., Etienne, M. A., & Miller, G. A. (1997) . Patterns of regional brain activity differentiate types of anxiety. Journal of Abnormal Psychology, 106, 376-385.
Henriques, J. B., & Davidson, R. J. (1990). Regional brain electrical asymmetries discriminate between previously depressed and healthy control subjects. Journal of Abnormal Psychology, 99, 22-31.
54
Henriques, J. B., & Davidson, R. J. (1991). Left frontal hypoactivation in depression. Journal of Abnormal Psychology, 100, 535-545.
lacono, W. G., Carlson, S. R., Taylor, J., Elkins, I. J., & McGue, M. (1999). Behavioral disinhibition and the development of substance-use disorders: Findings from the Minnesota Twin Family Study. Development & Psychopathology, 11, 869-900.
Jacobs, G. D., & Snyder, D. (1996). Frontal brain asymmetry predicts affective style in men. Behavioral Neuroscience, 110, 3-6.
Jang, K. L., Livesley, W. J., Angleitner, A., Riemann, R., & Vernon, P. A. (200 2). Genetic and environmental influences on the covariance of facets defining the domains of the five-factor model of personality. Personality & Individual Differences, 33, 83-101.
Jang, K. L., Livesley, W. J., & Vernon, P. A. (1996) . Heritability of the big five personality dimensions and their facets: A twin study. Journal of Personality, 64, 577-591.
Jockin, v., McGue, M., & Lykken, D. T. (1996). Personality and divorce: A genetic analysis. Journal of Personality & Social Psychology, 71, 288-299.
Johansson, C., Jansson, M., Linner, L., Yuan, Q.-P., Pedersen, N. L., Blackwood, D., Harden, N., Kelsoe, J., & Schalling, M. (2001). Genetics of affective disorders. European Neuropsychopharmacology, 11, 385-394.
Johnson, W., McGue, M., Gaist, D., Vaupel, J. W., & Christensen, K. (2002) . Frequency and heritability of depression symptomatology in the second half of life: Evidence from Danish twins over 45. Psychological Medicine, 32, 1175-1185.
Jones, N. A., Field, T., Davalos, M., & Pickens, J. (1997). EEG stability in infants/children of depressed mothers. Child Psychiatry & Human Development, 28, 59-70.
Kendler, K., & Aggen, S. H. (2001). Time, memory and the heritability of major depression. Psychological Medicine, 31, 923-928.
Kendler, K. S. , Gardner, C. O., Neale, M. C., & Prescott, C. A. (2001). Genetic risk factors for major depression in men and women: Similar or different heritabilities and same or partly distinct genes? Psychological Medicine, 31, 605-616.
Kendler, K. S., Gardner, C. 0., & Prescott, C. A. (2001). Panic syndromes in a population-based sample of male and female twins. Psychological Medicine, 31, 989-1000.
55
Kendler, K. S., Neale, M. C., Kessler, R. C., Heath, A. C., & et al. (1992). Generalized anxiety disorder in women: A population-based twin study. Archives of General Psychiatry, 49, 267-272.
Kline, J. P., Allen, J. J. B., & Schwartz, G. E. (1998). Is left frontal brain activation in defensiveness gender specific? Journal of Abnormal Psychology, 107, 149-153.
Kline, J. P., Blackhart, G. C., & Joiner, T. E. (2002). Sex, lie scales, and electrode caps: An interpersonal context for defensiveness and anterior electroencephalographic asymmetry. Personality & Individual Differences, 33, 459-478.
Knowles, J. A., Mannuzza, S., & Fyer, A. J. (19 95). Heritability of social anxiety. In M. B. Stein (Ed.), Social phobia: Clinical and research perspectives. Washington, DC: American Psychiatric Press.
Kring, A. M. , & Bachorowski, J.-A. (1999) . Emotions and psychopathology. Cognition & Emotion, 13, 575-599.
Krueger, R. F. (2000). Phenotypic, genetic, and nonshared environmental parallels in the structure of personality: A view from the Multidimensional Personality Questionnaire. Journal of Personality & Social Psychology, 79, 105 7-1067.
Loehlin, J. C. (1998) . Latent Variable Models: An Introduction to Factor, Path and Structural Analysis (3'^'' ed.) . Mahwah, New Jersey: Lawrence Erlbaum Associates.
Lykken, D., & Tellegen, A. (1996) . Happiness is a stochastic phenomenon. Psychological Science, 7, 186-189.
Lykken, D. T., Tellegen, A. , & lacono, W. G. (1 982) . EEG spectra in twins: Evidence for a neglected mechanism of genetic determination. Physiological Psychology, 10, 60-65.
MacDhomhail, S., Allen, J. J. B., Katsanis, J., & lacono, W. G. (1999). Heritability of frontal alpha asymmetry. Psychophysiology, 36, S74 .
McGue, M., & Lykken, D. T. (1992). Genetic influence on risk of divorce. Psychological Science, 3, 36 8-373.
Miller, A., & Tomarken, A. J. (2001). Task-dependent changes in frontal brain asymmetry: Effects of incentive cues, outcome expectancies, and motor responses. Psychophysiology, 38, 500-511.
56
Neale, M. C. (1997). Mx: Statistical modeling (4"'* ed. ) . Box 126 MCV, Richmond, VA 23298: Medical College of Virginia, Department of Psychiatry.
Nitschke, J. B., Heller, W., Palmieri, P. A., & Miller, G. A. (1999). Contrasting patterns of brain activity in anxious apprehension and anxious arousal. Psychophysiology, 36, 628-637.
Patrick, C. J., Curtin, J. J., & Tellegen, A. (2002) . Development and validation of a brief form of the Multidimensional Personality Questionnaire. Psychological Assessment, 14, 150-163.
Reid, S. A., Duke, L. M., & Allen, J. J. B. (1998). Resting frontal electroencephalographic asymmetry in depression: inconsistencies suggest the need to identify mediating factors. Psychophysiology, 35, 389-404.
Rice, F., Harold, G., & Thaper, A. (2002). The genetic aetiology of childhood depression: A review. Journal of Child Psychology & Psychiatry & Allied Disciplines, 43, 65-79.
Rickman, M. D., & Davidson, R. J. (1991) . Frontal EEG asymmetry in parents of behaviorally inhibited and unihibited children. Psychophysiology, 28, S46.
Rowe, D. C., Almeida, D. M., & Jacobson, K. C. (1999). School context and genetic influences on aggression in adolescence. Psychological Science, 10, 277-2 80.
Schaffer, C. E., Davidson, R. J., & Saron, C. (1983) . Frontal and parietal electroencephalogram asymmetry in depressed and nondepressed subjects. Biological Psychiatry, 18, 753-762.
Schmidt, L. A. (1999). Frontal brain electrical activity in shyness and sociability. Psychological Science, 10, 316-320.
Schmidt, L. A., & Fox, N. A. (1994). Patterns of cortical electrophysiology and autonomic activity in adults' shyness and sociability. Biological Psychology, 38, 183-198.
Schmidt, L. A., Fox, N. A., Schulkin, J., & Gold, P. W. (1999). Behavioral and psychophysiological correlates of self-presentation in temperamentally shy children. Developmental
Psychobiology, 35, 119-135.
Schneirla, T. (1959). An evolutionary and developmental theory of biphasic processes underlying approach and withdrawal. In M. Jones (Ed.), Nebraska Symposium on Motivation (pp. 1-42). Lincoln, NE: University of Nebraska Press.
57
Stassen, H. H., Bomben, G., & Hell, D. (1998). Familial brain wave patterns: Study of a 12-sib family. Psychiatric Genetics, 8, 141-
153 .
Stassen, H. H., Lykken, D. T., & Bomben, G. (1988) . The within-pair EEG similarity of twins reared apart. European Archives of Psychiatry & Neurological Sciences, 237, 244-252.
Stein, M. B., Jang, K. L., & Livesley, W. J. (1999). Heritability of anxiety sensitivity: A twin study. American Journal of Psychiatry, 156, 246-251.
Sutton, S. K., & Davidson, R. J. (1997). Prefrontal brain asymmetry: A biological substrate of the behavioral approach and inhibition systems. Psychological Science, 8, 204-210.
Tellegen, A. (198 5) . Structures of mood and personality and their relevance to assessing anxiety, with an emphasis on self-report. In A. H. Tuma & J. D. Maser (Eds.), Anxiety and the anxiety disorders. Hillsdale, NJ: Erlbaum
Tellegen, A., Lykken, D. T., Bouchard, T. J., Wilcox, K. J., & et al. (1988). Personality similarity in twins reared apart and together. Journal of Personality & Social Psychology, 54, 1031-1039 .
Thapar, A., & McGuffin, P. (1995). Are anxiety symptoms in childhood heritable? Journal of Child Psychology & Psychiatry & Allied Disciplines, 36, 439-447.
Tomarken, A. J., & Davidson, R. J. (1994) . Frontal brain activation in repressors and nonrepressors. Journal of Abnormal Psychology, 103, 339-349.
Tomarken, A. J., Davidson, R. J., & Henriques, J. B. (1990). Resting frontal brain asymmetry predicts affective responses to films. Journal of Personality & Social Psychology, 59, 791-801.
Tomarken, A. J., Davidson, R. J., Wheeler, R. E., & Doss, R. C. (1992). Individual differences in anterior brain asymmetry and fundamental dimensions of emotion. Journal of Personality & Social Psychology, 62, 676-687.
Tomarken, A. J., Davidson, R. J., Wheeler, R. E., & Kinney, L. (1992). Psychometric properties of resting anterior EEG•asymmetry: Temporal stability and internal consistency. Psychophysiology, 29, 576-592.
58
Toth, L. A. (2001). Identifying genetic influences on sleep: An approach to discovering the mechanisms of sleep regulation. Behavior Genetics, 31, 39-4 6.
van der Bolt, L., & Tellegen, S. (1995) . Sex differences in intrinsic reading motivation and emotional reading experience. Imagination, Cognition & Personality, 15, 337-349.
Vierikko, E., Pulkkinen, L., Kaprio, J., Viken, R., & Rose, R. J. (2003). Sex differences in genetic and environmental effects on aggresion. Aggressive Behavior, 29, 55-68.
Weiss, A., King, J. E., & Figueredo, A. J. (2000). The heritability of personality factors in chimpanzees (Pan troglodytes). Behavior Genetics, 30, 213-221.
Wheeler, R. E., Davidson, R. J., & Tomarken, A. J. (1993) . Frontal brain asymmetry and emotional reactivity: A biological substrate of affective style. Psychophysiology, 30, 82-89.
Wiedemann, G., Pauli, P., Dengler, W., Lutzenberger, W., Birbaumer, N., & Buchkremer, G. (1999). Frontal brain asymmetry as a biological substrate of emotions in patients with panic disorders. Archives of General Psychiatry, 56, 78-84.
Willcutt, E. G., Pennington, B. F., & DeFries, J. C. (2000). Etiology of inattention and hyperactivity/impulsivity in a community sample of twins with learning difficulties. Journal of Abnormal Child Psychology, 28, 149-159.
Young, J. P. , Fenton, G. W. , & Lader, M. H. (1971) . The inheritance of neurotic traits: A twin study of the Middlesex Hospital Questionnaire. British Journal of Psychiatry, 119, 393-398.