The heritability of trait frontal EEG asymmetry and negativeemotionality: Sex differences and genetic nonadditivity

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Authors Coan, Jr., James A.

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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

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