P300 amplitude as an indicator of externalizing in
CHRISTOPHER J. PATRICK, EDWARD M. BERNAT, STEPHEN M. MALONE,
WILLIAM G. IACONO, ROBERT F. KRUEGER, and MATT MCGUE
Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
Reduced P300 amplitude is reliably found in individuals with a personal or family history of alcohol problems.
However, alcoholism is part of a broader externalizing spectrum that includes other substance use and antisocial
disorders. Wehypothesizedthatreduced P300 isanindicatorofthecommonfactorthatunderliesdisorders withinthis
spectrum. Community males (N5969) were assessed at age 17 in a visual oddball task. Externalizing was defined as
the common factor underlying symptoms of alcohol dependence, drug dependence, nicotine dependence, conduct
disorder, and adult antisocial behavior. A robust association was found between reduced P300 amplitude and the
externalizing factor, and this relation accounted for links between specific externalizing disorders and P300. Our
findings indicate that reduced P300 amplitude is an indicator of the broad neurobiological vulnerability that underlies
disorders within the externalizing spectrum.
Descriptors: P300, externalizing, psychopathology
Diagnostic comorbidity studies and behavioral genetic investi-
gations over the past decade have converged on the idea that
alcoholism, drug dependence, and antisocial deviance in child-
hood and later life comprise a spectrum of related disorders.
Coincident with these developments, evidence has accumulated
that reduced amplitude of the P300 brain potential response,
long known to be an indicator of risk for alcohol problems, is
associated with other disorders in this spectrum. The current
study addressed the following basic question, arising from these
of the general factor that these disorders have incommon, rather
than of specific disorders within this spectrum?
It is well established that reduced amplitude of the P300
component of the event-related potential, a positive brainwave
deflection evoked by infrequent, task-relevant events in a stim-
ulus sequence, is associated with alcohol problems and alcohol-
ism risk.1This link was first noted in work comparing abstinent
alcoholics with controls (Porjesz, Begleiter, & Garozzo, 1980).
Subsequent studies revealed that reduced P300 amplitude was
development of alcohol problems. For example, children and ad-
olescents with a paternal history of alcoholism show reliably re-
duced P300 compared with family-negative controls (Begleiter,
kit, & Bloom, 1982; Hill & Shen, 2002; for review, see Polich,
Pollock, & Bloom, 1994). Additionally, smaller P300 amplitude
prospectively predicts the later emergence of alcohol problems
(Berman, Whipple, Fitch, & Noble, 1993; Hill, Steinhauer, Low-
ers, & Locke, 1995; Iacono, Carlson, Malone, & McGue, 2002).
These results have led theorists to postulate that reduced P300
response is an indicator of brain-based impairments in cognitive-
executive function that confer a risk for alcohol dependence (e.g.,
Begleiter & Porjesz, 1999; Giancola & Tarter, 1999).
However, alcohol-related problems do not typically occur in
isolation. They routinely co-occur with symptoms of other dis-
orders such as drug dependence and antisocial personality
(Kessler et al., 1997; Robins & Regier, 1991; Sher & Trull,
1994). Moreover, this comorbidity is systematic rather than ran-
domFthat is, the presence of alcohol problems reliably predicts
Krueger, Caspi, Moffitt, & Silva, 1998). One interpretation of
this systematic co-occurrence is that substance abuse and anti-
social behavior disorders are connected at a fundamental etio-
vulnerability (Iacono, Carlson, Taylor, Elkins, & McGue, 1999;
Krueger et al., 1998; Tarter, 1988). Family and twin studies pro-
vide support for this position. Antisocial behavior problems are
This research was supported by grants MH 65137, DA 05147, and
AA 09367 from the National Institutes of Health, and by funds from the
Hathaway endowment at the University of Minnesota.
Address reprint requests to: Christopher J. Patrick, Department of
Psychology, University of Minnesota, Elliott Hall, 75 East River Road,
Minneapolis, MN 55455, USA; E-mail: firstname.lastname@example.org.
1The term P3b is sometimes used for this frequency-sensitive
component, to distinguish it from the ‘‘P3a’’ or ‘‘novelty P3,’’ maximal
nontarget stimulus (Coles & Rugg, 1995). Unless otherwise specified,
‘‘P300’’ here refers to the P3b component, which has been studied most
extensively in relation to substance abuse and other externalizing
Psychophysiology, 43 (2006), 84–92. Blackwell Publishing Inc. Printed in the USA.
Copyright r 2006 Society for Psychophysiological Research
more common among the offspring of substance abusers com-
pared with controls (Clark et al., 1997; Luthar, Merikangas, &
Rounsaville, 1993; Malone, Iacono, & McGue, 2002; Sher,
Walitzer, Wood, & Brent, 1991) and rates of substance abuse are
elevated in offspring of antisocial individuals (Cadoret, Yates,
Troughton, Woodworth, & Stewart, 1995). Twin research studies
have yielded evidence of common genetic factors underlying pairs
of disorders within this spectrum (Grove et al., 1990; Pickens,
Svikis, McGue, & LaBuda, 1995; Slutske et al., 1998). Moreover,
recent large-scale epidemiological studies with twins have shown
that the broad externalizing factor, reflecting the shared variance
among disorders of this type, is substantially (480%) heritable
(Kendler, Prescott, Myers, & Neale, 2003; Krueger et al., 2002;
Young, Stallings, Corley, Krauter, & Hewitt, 2000).
Of particular relevance to the current study is growing evi-
dence that reduced P300 response is associated with other dis-
orders in the externalizing spectrum besides alcohol dependence,
including drug dependence (Attou, Figiel, & Timsit-Berthier,
2001; Biggins, MacKay, Clark, & Fein, 1997; Branchey, Buy-
dens-Branchey, & Horvath, 1993), nicotine dependence (An-
okhin et al., 2000; Iacono et al., 2002), child conduct disorder
(Bauer & Hesselbrock, 1999a, 1999b; Kim, Kim, & Kwon,
2001), and adult antisocial personality (Bauer, O’Connor, &
Hesselbrock, 1994; Costa et al., 2000). Furthermore, reduced
P300 is associated with risk for these other disorders as well as
with active symptoms. For example, Iacono et al. (2002) report-
ed smaller P300 amplitude among adolescent males whose fa-
thers met criteria for alcohol dependence, drug dependence, or
antisocial personality incomparison tocontrolswithnopaternal
history of these disorders. This was true whether or not the off-
the age at which brain potential response was assessed (see also
Brigham, Herning, & Moss, 1995). Additionally, P300 ampli-
tude tended to be smallest among participants whose fathers met
criteriaformore thanoneexternalizingdisorder. Takentogether,
these findings suggest that reduced P300 amplitude reflects an
underlying vulnerability not just to alcohol problems, but to all
disorders within the externalizing spectrum.
Following from this, the current study addressed the follow-
ing three interrelated questions:
1. Is There an Association between Externalizing and P300
Various lines of evidence converge on the hypothesis of a link
between reduced P300 and the common factor that underlies
disorders within the externalizing spectrum, but this possibility
has not been evaluated directly. We tested this hypothesis by
performing an analysis in which P300 comprised the dependent
drug dependence, nicotine dependence, conduct disorder, and
adult antisocial behavior was included as the primary independ-
2. Could the Connection between Externalizing and P300 Ac-
count for the Alcohol–P300 Relationship?
A second question was whether the association between the
externalizing factor and P300 amplitude might account for the
well-documented relationship between alcohol problems and re-
duced P300Fas well as for relations between P300 and other
externalizing syndromes (cf. Iacono et al., 1999). To address this
question, we performed hierarchical regression analyses for each
diagnostic symptom variable, examining whether its association
with P300 would besubstantially attenuated aftercontrollingfor
scores on the externalizing factor.
3. Can P300 Amplitude Be Considered an Indicator of Exter-
amplitude represents an indicator of externalizing vulnerability.
If so, when included in a factor analysis with disorder symptom
scores, P300 amplitude should show a robust association with a
single common externalizing factor rather than defining a sep-
arate factor. However, because P300 is assessed in a distinct
measurement domain (i.e., physiological response), we predicted
that its association with this underlying externalizing factor
would be lower than the associations of the diagnostic variables
(cf. Campbell & Fiske, 1959).
Methods and Materials
The sample consisted of twin participants in the Minnesota Twin
Family Study (MTFS), a longitudinal and epidemiological in-
vestigation of the origins and development of substance use dis-
orders and related psychopathology. The MTFS employs a
population-based ascertainment method in which all twins born
the MTFS sample and study design, including ascertainment and
recruitment procedures, see Iacono et al., 1999.) The current
sampleconsistedofallmaletwinparticipantsfromthe MTFS for
whom diagnostic indicators of externalizing (see below) were
available. Specifically, the study sample consisted of 969 adoles-
cent males from 520 families, most assessed around the age of 17
(M517.66; SD50.53; range516.66 to 20.01). This sample
combined subjects from the two age cohorts of the MTFS: sub-
jects in one cohort were 17 years old at intake whereas subjects in
the otherwereapproximately11 yearsold atintake, with data for
the latter coming from their second three-year follow-up assess-
ment (i.e., data for the current study were obtained when par-
ticipants in this cohort were around age 17). Consistent with the
demographics of the state of Minnesota at the time the study
participants were born, nearly all were Caucasian.
Diagnostic ratings. Subjects who were still legal minors gave
written assent to participate and their parents consented to their
participation. Subjects who were 18 years old gave written in-
formed consent to participate. Trained interviewers with under-
graduate or Master’s degrees administered structured interviews
the Diagnosticand Statistical Manualof Mental Disorders, Third
Edition-Revised (DSM-III-R; American Psychiatric Associa-
tion, 1987), the diagnostic standard in place at the time data
Symptoms of alcohol, drug, and nicotine dependence were
assessed using an expanded version of the Substance Abuse
Module (SAM; Robins, Babor, & Cottler, 1987) from the Com-
posite International Diagnostic Interview (Robins et al., 1988).
Subjects were also interviewed using an instrument developed by
MTFS staff to assess symptoms of DSM-III-R conduct disorder
occurring before age 15 and adult antisocial behavior symptoms
P300 and externalizing 85
occurring after age 15 (cf. Iacono et al., 1999). Mothers of the
twins reported on the substance use and childhood antisocial
behaviors of each twin through interviews using the parent ver-
sion of the Diagnostic Interview for Children and Adolescents–
Revised (DICS-R; Reich, 2000; Welner, Reich, Herjanic, Jung,
& Amado, 1987). Advanced graduate students trained in de-
scriptivepsychopathology determinedthe presence or absenceof
DSM-III-R symptoms working in teams, using a consensus,
‘‘best-estimate’’ approach (Kosten, Rounsaville, Kosten, & Me-
rikangas, 1992; Leckman, Sholomskas, Thompson, Belanger, &
Weissman, 1982) thatcombinedreportsfrom boththe individual
and his mother. Becauseyouths weresoleinformantsabout their
antisocial behavior occurring after age 15, these symptoms were
assigned on the basis of self-report only.
Symptom counts (i.e., number of diagnostic criteria met) for
each of the following disorders were used: alcohol dependence;
illicit drug dependence, representing the number of symptoms of
dependence on the illicit substance used most heavily, whether
cannabis, amphetamines, cocaine, hallucinogens, opiates, psych-
edelics, or sedatives; nicotine dependence; conduct disorder (12
of the 13 criterion A symptoms; item 5, concerning coercive sex-
10 criterion Csymptomsof ASPD;owingtosubjects’youngage,
the item concerning inability to remain in a monogamous rela-
tionship was omitted). Reliability coefficients for the various
disorders examined in the present study all achieved acceptable
levels and are summarized in Iacono et al. (1999). Kappa coef-
ficients were greater than or equal to .81 for the disorders con-
sidered in the present investigation. The frequencies of the
various disorders among participants in the sample (where pres-
ence ofthe disorder was definedas probableor definite, meaning
at threshold or within one symptom of threshold for a diagnosis)
were as follows: alcohol dependence, 16.6%; drug dependence,
10.8%; nicotine dependence, 27.6%; conduct disorder, 38.6%;
and adult antisocial behavior, 11.4%.
Externalizing variable. Scores on the externalizing factor
were derived from a principal components analysis (PCA) of
symptom counts for the syndromes described in the preceding
section, that is, alcohol dependence, drug dependence, nicotine
dependence, conduct disorder, and adult antisocial behavior.
Correlations among the various symptom variables were all sig-
nificant, and ranged from .33 to .59 (median5.42). For the
principal components analysis, scores on each symptom variable
were Blom-transformed and rank normalized in order to correct
for skewness (cf. Krueger et al., 2002). This involved replacing
raw scores with ranks (the mean rank was assigned in cases in-
volving ties) and then expressing these ranks in z-score units. By
standard eigenvalue and scree plot criteria, the principal com-
ponents analysis yielded a single dominant component, account-
ing for 60% of the variance in the five disorders. Loadings of the
individual symptom variables on this common externalizing fac-
tor were all robust and comparable in magnitude to those ob-
served by Krueger et al. (2002): alcohol dependence, .81; drug
dependence, .78;nicotinedependence,.78;conductdisorder, .66;
and adult antisocial behavior, .85. Scores on the externalizing
factor were computed for each participant using the regression
variable in the primary analyses reported below.
We used the rotated-heads visual oddball task of Begleiter et al.
(1984; see Figure 1), a procedurethat yieldedrobust P300 effects
in this and other subsequent alcohol risk studies (e.g., Hill &
Steinhauer, 1993; Hill, Shen, et al., 1999; O’Connor, Bauer,
Tasman, & Hesselbrock, 1994). Each of the 240 stimuli com-
prising this task was presented on a computer screen for 98 ms,
withthe intertrial interval (ITI) varying randomly between 1 and
2 s. A small dot, upon which subjects were instructed to fixate,
of the trials, participants saw a plain oval to which they were
instructed not to respond. On the remaining third of the trials,
participants saw a superior view of a stylized head, depicting the
noseandoneear. Thesestylized headsservedas ‘‘target’’ stimuli.
Participants were instructed to press one of two response
buttons attached to each arm of their chair to indicate whether
the ear was on the left side of the head or the right. Half of these
the left ear would be on the left side of the head as it appeared to
the subject (easy discrimination). Half consistedofheads rotated
1801 so that the nose pointed down, such that the left ear would
appear on the right side of the screen and the right ear would
appear on the left side of the screen (hard discrimination).
Recording procedure. All participants completed the assess-
mentat approximately the same time in the morning. They sat in
a comfortable high-backed chair while electroencephalographic
86 C.J. Patrick et al.
Figure 1. Schematic depiction of stimuli used in the rotated-heads visual
response. Each of the four target stimuli was presented on 20 trials; for
these stimuli, the participant pressed a button with either the left or right
easy head targets (top), the nose was pointed up and thus the correct
button response (‘‘left’’ or ‘‘right’’) corresponded directly to the side of
the screen on which the ear appeared. For hard targets (middle), the nose
was pointed down and thus the correct button response was opposite to
the side of the screen on which the ear appeared.
(EEG) data were recorded from three parietal scalp locations,
one on the midline (Pz) and one over each hemisphere (P3 and
P4). Linked earlobes served as reference and an electrode on the
right shin as ground. Blinks and eye movements were recorded
with a pair of biopotential electrodes arranged in a transverse
montage, oneelectrode superior tothe eye andthe other overthe
outer canthus. A Grass Model 12A Neurodata acquisition sys-
tem was used to collect EEG data, with each signal passed
through an amplifier with a bandpass of 0.01 to 30 Hz (half-
amplitude) anda roll-offof 6 dB per octave. Foreach trial, 2 sof
EEG, including a 500-ms prestimulus baseline, were digitized to
12 bits resolution at a rate of 256 Hz. If participants failed to
respond to a given target, or if any EEG signal exceeded the
range of the A-D converter, the trial was repeated. Trials re-
peated more than twice were excluded from averaging.
EEG data processing and reduction. The procedure of Grat-
ton, Coles, and Donchin (1983) was used to correct for blinks
and other ocular artifacts in the EEG. Signals were digitally fil-
tered using a third-order Butterworth highpass filter at 0.5 Hz to
attenuate low frequency artifact present in some of the data due
Pz. (Differences in activity between the lateral and central elec-
trodes did not produce significant interactions with scores on the
externalizing factor in a preliminary analysis, and thus only data
from the Pz electrode are reported.) The P300 was defined as the
point between 280 and 600 ms at which amplitude of the average
waveform was maximal.2P300 amplitude scores were obtained
for the target conditions (easy discrimination, hard discrimina-
tion) at the Pz electrode site.
analysis of variance procedures. Behavioral response data were
unavailable for 12 subjects, leaving 957 for these specific anal-
yses. A mixed-model analysis of variance (ANOVA) was first
conducted in which continuous externalizing factor scores and
categorical target difficulty (easy vs. hard) were included as be-
tween-subjects and within-subject factors, respectively, and re-
sponseaccuracy (i.e., number ofcorrect button presses following
target stimuli) was the dependent variable. A second External-
izing ? Target Difficulty mixed-model ANOVA was conducted
with response latency (in milliseconds) for correct response trials
externalizing scores and number of false alarms (i.e., erroneous
button presses to nontarget stimuli) was examined via Pearson
For the brain potential data, two analyses were conducted.
First, a mixed-model ANOVA was constructed in which con-
tinuous scores on the externalizing factor served as the between-
subjects factor, target difficulty the within-subjects factor, and
P300 amplitude the dependent variable. Our main hypothesis
was that externalizing scores would be significantly related to
P300 amplitude. Second, hierarchical regression analyses were
performed separately for each DSM disorder to assess whether
externalizing scores accounted for observed relations between
specific disorder symptoms and P300 amplitude. The first step in
each analysis was to regress P300 amplitude on the symptom
count score for a givendisorder. In the second step, externalizing
score was added to the model. If externalizing accounts for the
associationbetweenthedisordersymptoms andP300 amplitude,
then the effectofthe disorder shouldbe significantintheabsence
of the externalizing variable (i.e., in step 1) but become nonsig-
nificant in the presence of the externalizing variable (i.e., in
step 2). Our hypothesis was that the externalizing factor would
account for all significant relations between individual disorders
and P300 amplitude.
A final analysis was conducted to quantify the loading of
P300 amplitude on the externalizing factor. This analysis was a
principal components analysis incorporating P300 amplitude as
a variate in addition to the four DSM-III-R symptom scores.
In what follows, only effects significant beyond po.01 are
reported and discussed as being statistically significant. This
more stringent criterion was adopted to adjust for the effect of
correlated observations arising from the use of data from twins,
who were treated as individual cases in the analyses.3
A total of 240 stimuli were presented: 40 easy targets, 40 hard
targets, and 160 nontargets. Overall, the number of correct re-
sponses to targets was very high (M578.81 out of 80,
SD51.70) and the number of erroneous button presses to non-
registered any false alarms). Response accuracy was higher for
easy than hard targets, Ms539.54 and 39.27, respectively,
SDs5.90 and 1.19, F(1,955)545.59, po.001, and on correct
response trials, response latency was faster for easy targets than
hard, Ms5833.33 and 1048.16, respectively, SDs5162.16 and
221.04, F(1,955)52608.54, po.001. There was no significant
effect of externalizing score on either target response accuracy or
latency, and no Externalizing x Target Difficulty interaction was
evident for either variable. Thecorrelationbetween externalizing
scores and false alarms was not significant, r5.061.
Assessing the relation between P300 amplitude and external-
izing. In the analysis of P300 response amplitude to target stim-
uli, significant main effects were observed for both independent
variables: externalizing score, F(1,967)528.26, po.001, and
target difficulty (easy, hard), F(1,967)535.35, po.001. Higher
externalizing was associated with significantly smaller P300.
Figure 2 illustrates this effect by comparing the average ERP
waveform for participants in the lowest quartile of the distribu-
P300 and externalizing87
2In addition to analyses employing these peak amplitude scores, we
performed a principal components analysis on the ERP waveform to
isolate the P300 component, and reran the main analysis assessing the
relation between P300 and externalizing using the scores for this com-
ponent in place of the peak amplitude scores. This analysis yielded es-
sentially the same results. Because the peak amplitude parameter is more
straightforward and more commonly used in psychopathology studies,
we report this as the primary measure in the current analyses.
3We also conducted supplementary analyses in which we directly
controlled for the correlation between twins with respect to P300 am-
plitude. These analyses employed multilevel models with random inter-
cepts to account for characteristics shared by twins that relate to P300
amplitude (cf. Goldstein, 1995). The results of these more complex sup-
plemental analysesFconsisting of multivariate analyses with target dif-
ficulty and externalizing as fixed effects as well as multilevel versions of
the mediational analysesFcorroborated those of our primary analyses.
Because the primary analyses are more readily interpretable, we focus on
the findings of these in the main text.
tionof scoresonthe externalizing factorwithaverage waveforms
for individuals who scored (a) above the median, (b) in the high-
est quartile, and (c) in the highest decile (10%) of the distribu-
tion. Effects oftarget difficulty paralleled those for externalizing:
Hard targets evoked smaller P300 responses than easy targets,
Ms517.29 and 17.89, respectively, SDs55.50 and 5.51. The
interaction between externalizing and target difficulty was not
significant, F(1,967)5.67, n.s.
Role of externalizing in accounting for relations between indi-
vidual DSM disorders and P300. Table 1 summarizes the results
of hierarchical regression analyses that were conducted to deter-
mine whether observed relations between individual disorder
symptoms and P300 amplitude were attributable to the shared
variance among disorders represented by externalizing factor
scores. Because the ANOVA that included data for all task trials
revealed only a main effect of externalizing, with no moderation
as a function of task difficulty (easy, hard), average P300 am-
plitude across all target stimuli was used as the dependent var-
iable in these regression analyses. A significant negative
association between symptom count and P300 amplitude was
apparent in step 1 of the analysis for all symptom variables.
However, for all disorders this relationship became negligible
relations between individual DSM syndromes and P300 ampli-
tude are due to the shared variance among these disorders (i.e.,
externalizing). In no casedidthe unique variance associated with
a particular disorder contribute significantly to its relation with
P300 independently of externalizing.
P300 amplitude as an indicator of externalizing and to quantify
components analysisincludingoverall P300 amplitude scores for
each participant (i.e., across easy and hard targets) along with
symptom scores for the four DSM-III-R disorders as variates.
The analysis yielded evidence of a single dominant component:
Only one eigenvalue exceeded a magnitude of 1 (i.e., 3.07), and
the scree plot revealed a marked break after the first component
(i.e., remaining eigenvalues50.96, 0.71, 0.47, 0.45, and 0.35,
respectively). The first component accounted for 51.10% of the
total variance in scores. The loadings of the five symptom var-
iables on this component were: alcohol dependence, .81; drug
dependence, .77; nicotinedependence,.78;conductdisorder, .66;
and adult antisocial behavior, .85. The loading for P300 ampli-
tude was ?.25. Figure 3 depicts the association between P300
amplitude and scores on the broad externalizing factor across
individuals in this analysis.
We evaluated the significance of the loading of each variable
on the first principal component by computing 99% bootstrap
confidence intervals for the values of these loadings. Each boot-
strap confidence interval was bias-corrected and accelerated,
based on 10,000 bootstrap samples. Bias-corrected and acceler-
ated bootstrap confidence intervals have been shown to approx-
Tibishirani, 1998). In no case did the 99% confidence interval
include zeroFthat is, loadings for all variables, including P300
amplitude, were significant at po.01.
Based on recent research findings, we predicted a relationship
between P300 brain potential amplitude and the broad external-
izing factor linking alcohol dependence, drug dependence,
nicotine dependence, conduct disorder, and adult antisocial
deviance. In a multivariate analysis in which continuous
externalizing scores, defined as scores on the first component
extracted from a PCA of symptom scores for these disorders,
were included as a factor along with task difficulty (easy vs.
hard), a robust main effect of externalizing was found: Higher
scores on the externalizing factor, reflecting greater severity and
breadth of externalizing symptoms, were associated with smaller
88C.J. Patrick et al.
P300 Amplitude (µV)
100 200 300 400 500 600 700 800 900 1000
Low EXT Quartile
High EXT Median
High EXT Quartile
High EXT Decile
Figure 2. AverageERP waveformsforparticipantsinthelowestquartile
of the distribution of scores on the externalizing (EXT) factor, and for
highest quartile of the distribution, and (c) in the highest decile (10%) of
the distribution. The externalizing factor is defined as the first principal
component derived from a PCA of DSM-III-R symptoms of alcohol
dependence, drug dependence, nicotine dependence, conduct disorder,
and adult antisocial behavior. A score on this factor was computed for
each individual participant using the regression method.
Table 1. Hierarchical Regression Analyses Demonstrating that
Externalizing Vulnerability Accounts for Relations between
Individual DSM-III-R Disorders and P300 Amplitude
Unadjusted (step 1)Adjusted (step 2)
Adult Antisocial behavior ?0.75 ?4.46 o.001
?0.70 ?4.20 o.001
?0.82 ?4.92 o.001 ?0.37 ?1.39 .164
?0.60 ?3.59 o.001 ?0.04 ?0.17 .869
0.02 0.07 .947
Note. B is the raw regression coefficient obtained by regressing P300
amplitude, averaged across easy and hard target stimuli, on normalized
symptom counts of each individual DSM disorder. It therefore reflects
thedecreasein P300amplitude (inmicrovolts)associatedwithastandard
deviation increase in symptoms of the relevant disorder. t is the test
statistic for each B coefficient, and p its associated probability. The un-
adjusted coefficients were derived in the first step, in which disorder
symptom count for each disorder was the sole predictor in the model.
Adjusted coefficients were derived in the second step of each analysis, in
which externalizing vulnerability score was added to the model as a sec-
ond predictor, and therefore are adjusted for scores on this vulnerability
With regard to the second major question of the study, a
hierarchical regression analysis revealed that scores on the broad
externalizing factor accounted for the association between alco-
hol dependence and P300 amplitude in the current study sample.
When externalizing was controlled statistically, the significant
alcohol–P300 correlation was reduced to nonsignificance. Par-
allel analyses revealed that relations between P300 and each of
the other symptom variables (drug dependence, nicotine de-
pendence, conduct disorder, and adult antisocial behavior) were
alsoattributable entirely tothisgeneral externalizingfactor. This
pattern of results has important implications. It encourages a
shift away from the perspective that reduced P300 is associated
specifically withalcoholproblems. It also provides an alternative
to the idea that the association between P300 and alcohol prob-
lems is mediated by its relationship with antisocial deviance (cf.
Bauer & Hesselbrock, 1999a, 1999b). Instead, the current data
suggest that it is what these disorders have in common, rather
than what is unique to any one of them, that is primarily asso-
ciated with reduced P300 response.
Finally, when mean P300 amplitude was included with the
five diagnostic variables in a principal components analysis, a
single dominant factor was evident on which all variables loaded
significantly. Because it reflects a separate measurement domain
with its own unique method variance (cf. Campbell & Fiske,
1959), the loading of P300 on the common externalizing factor
was modest (?.25) in comparison to the very high loadings for
the symptom variables (M5.77)Fbut it was nonetheless sta-
tistically robust. Moreover, the fact that P300 amplitude loaded
with the symptom variables on a common factor rather than
the same underlying construct as the symptom variables.
What is the nature of the common factor on which P300
amplitude loads along with symptoms of these various external-
izing disorders? The findings of recent behavior genetic investi-
gations suggest that this factor reflects a broad underlying
neurobiological vulnerability to disorders of this kind. For ex-
ample, Krueger et al. (2002) assessed genetic and environmental
contributions to this factor (defined as the shared variance
among symptoms ofalcohol dependence, drug dependence, con-
duct disorder, adult antisocial behavior, and disinhibitory per-
sonality) in a large twin cohort. The externalizing factor was
foundto be strongly (81%) genetic (see also Kendler et al., 2003;
Young et al., 2000). In contrast, environmental factors contrib-
uted most to the unique part of each disorder not attributable to
this common factor. These findings support a hierarchical model
of the externalizing spectrum in which varying disorders are
viewed as alternative manifestations of a broad, heritable vul-
nerability. This broad vulnerability confers a risk for a range of
different disorders. However, its expression as one disorder or
another is determined by specific causal influences.
The present results establish that reduced P300 is associated
with higher externalizing vulnerability as defined by current
symptomatology. However, P300 response amplitude, like
externalizing vulnerability, is highly heritable (Katsanis, Iacono,
McGue, & Carlson, 1997; O’Connor, Morzorati, Christian, &
Li, 1994; van Beijsterveldt, Molenaar, de Geus, & Boomsma,
1998). This raises the possibility that reduced P300 amplitude
may represent a quantitative endophenotype of externalizing
vulnerability. An endophenotype is a biological characteristic
that arises from, and thus directly reflects, an underlying
genotypic predisposition (Gottesman & Shields, 1972; Iacono,
1998; John & Lewis, 1966).4
If reduced P300 is an endophenotype for externalizing vul-
nerability, it should also occur at higher rates among asympto-
matic individuals who are at risk for developing externalizing
problems by virtue of a positive parental history of such prob-
(2002) reported reduced P300 in the adolescent sons of fathers
who met criteria for alcohol dependence, drug abuse/depend-
ence, or antisocial personality, whether or not the offspring
reduced P300 at age 17 predicted the development of external-
izing problems of various kinds at age 20, even among individ-
uals who were free from disorder at the time of P300 assessment.
From these findings, it seems reasonable to expect that higher
levels of externalizing vulnerability in fathers would predict
smaller P300 amplitude in their offspring, and that individuals
with reduced P300 amplitude early in life would show higher
levels of externalizing symptomatology later in life. These hy-
potheses will be interesting to test in future research.
P300 and externalizing 89
P300 Amplitude (µV)
Externalizing Factor Score
r = −.25
Figure 3. Scatterplot of the association between mean P300 amplitude
and continuous scores on the externalizing factor across all study
geometric transformation, using the rotation matrix
score data in order to vertically align low scores on externalizing; the data
were normalized to unit-length axes prior to rotation and rescaled to the
original units afterward. For purposes of plotting, the minimum score on
0 now represents the minimum score, rather than the mean.
4It is conceivable that reduced P300 might reflect the toxic effects of
long-term alcohol consumption, rather than an underlying, genetically
mediatedvulnerability. The youth of subjects in this study argues against
viewing P300 amplitude reductions associated with externalizing as a
consequence of their substance use, rather than a constitutional liability.
even to the point of meeting diagnostic criteria for dependence. A meas-
ure of estimated alcohol consumption in the preceding year was, in fact,
correlated with both P300 amplitude and externalizing. Nonetheless,
partial correlations between externalizing and P300 amplitude measures,
holding estimated consumption constant, remained highly significant,
whereas correlations between estimated consumption and P300, holding
externalizing constant, were nonsignificant. These results support an in-
terpretation of P300 amplitude reduction as related to an underlying
vulnerability to externalizing problems, rather than to neurotoxic effects
of excessive alcohol consumption.
Concerning the status of P300 asan indicator ofexternalizing
vulnerability, an important question concerns its specificity, be-
cause P300 amplitude reductionhas also been found in disorders
outside the externalizing spectrumFmost notably major de-
pression and schizophrenia (e.g., Blackwood et al., 1987; Bruder
et al., 1995; Roth & Cannon, 1972). With regard to the former,
comorbid depression has been found to account for reduced
P300 amplitude in some alcoholic samples (e.g., Hill, Locke, &
of symptoms of major depression, assessed via the Structured
Clinical Interview for DSM-III-R Axis I (SCID-I; Spitzer, Will-
iams, Gibbon, & First, 1992), showed only a marginal associ-
ation with P300 amplitude, r5 ?.05, p4.14, and the relation
between externalizing and P300 remained highly significant after
controlling for depressive symptoms. Moreover, in contrast with
alcoholism, P300 amplitude shows a return to normal levels
when depressive symptoms remit (Yanai, Fujikawa, Osada,
Yamawaki, & Touhouda, 1997), and reduced P300 has not been
shown to predict the emergence of depression in persons at risk
for mood disorder. This suggests that reduced P300 may act as a
state (vs. trait) indicator of depression. On the other hand, ev-
idence does exist for P300 as a trait marker of schizophrenia (cf.
Ford, 1999). However, the association between schizophrenia
and P300 is more reliable for auditory than visual tasks (Jeon &
Polich, 2003), whereas the reverse is true for alcohol problems
P300 reduction in schizophrenia and externalizing psychopa-
thology are not identical. Nevertheless, more research would be
needed to establish the specificity of visual P300 amplitude re-
duction as a vulnerability marker for externalizing problems.
A further issue concerns the generality of our findings. The
current sample consisted of community males assessed around
age 17. Some recent research suggests that there may be a de-
velopmental transition in the association between alcohol risk
and P300: In a large-scale longitudinal study comparing indi-
viduals from families with a high density of alcohol dependence
with control participants, Hill, Shen, et al. (1999) reported a
marked reduction of P300 amplitude in high-risk individuals
during childhood and adolescence relative to age-matched con-
trols, but this group difference became less reliable in early
adulthood. There is also evidence that reduced P300 amplitude
in men, especially when using visual tasks (Hill, Muka, Stein-
hauer, & Locke, 1995). Relations between P300 and other ex-
ternalizing syndromes may also be less reliable among women
than men (Iacono et al., 1999; Justus, Finn, & Steinmetz, 2001).
In future studies of the association between externalizing vul-
nerability and P300, it will be important to examine moderating
effects of age and gender.
A final question concerns the neurobiological underpinnings
of the externalizing vulnerability factor, and the basis of its as-
sociation with P300 brain potential response. Begleiter and Po-
rjesz (1999) postulated that the inherited predisposition to
alcohol dependence entails a hyperexcitability of the central
nervous system that enhances risk for a variety of dishinhibitory
syndromes. In this model, reduced P300 amplitude is believed to
reflect a diminished capacity for neuronal inhibition. Relatedly,
Iacono, Carlson, and Malone (2000) proposedthat vulnerability
to substance abuse and antisocial deviance reflects a dysfunction
in inhibitory control associated with frontal brain regions (see
also Giancola & Tarter, 1999), and thatreduced P300 responseis
one indicator of this inhibitory deficit.
A notable feature of the current findings was that reduced
P300 amplitude among high externalizing individuals was not
accompanied by reduced performance on the visual discrimina-
tiontask. This lackof behavioral differences helpstoruleout the
engagement in the task. On the other hand, it might be argued
that the lack of behavioral differences calls into question the
functional significance of brain response differences. However,
we would assert that the presence of P300 brain response differ-
ences in the context of normal behavioral performance implies a
meaningful difference in cognitive processing associated with the
taskFfor example, reduced cognitive-evaluative processing of
the task stimuli, or a difference in ‘‘cognitive set’’ or strategy
associated with performance of the task. Although the precise
nature of this difference in cognitive processing remains to be
elucidated, the current findings are nonetheless important be-
causethey establishreducedP300 inthecontextofthistaskasan
indicator of general externalizing vulnerabilty.
the neuro-cognitive processing impairments that underlie
the vulnerability to these types of problems, the brain systems
that are involved, and the genes that contribute to these brain-
based differences. We argue on the basis of the current findings
that the primary target phenotype in this effort should be
the externalizing vulnerability that these disorders share, defin-
able as the covariance among disorders within this spectrum
(Krueger et al., 2002). This vulnerability is highly heritable
and, as we have shown, it accounts for relations between P300
and specific externalizing disorders. As such, it is a logical
referent for genetic and neurobiological studies. At the same
time, we advocate complementary research aimed at elucidating
unique etiologic factors that shape the expression of this general
vulnerability in specific ways (i.e., as alcohol dependence,
drug dependence, or antisocial behavior) and identifying
other problem behaviors and syndromes that arise from this
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(Received April 6, 2005; Accepted November 21, 2005)
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