ing threat. Virtually no work, however, has addressed whether behavioral inhibition may also confer heightened brain activation in
anticipated gain or loss. Alteration in neural systems underlying behavior modulated by both negative and positive contingencies may
Temperament refers to stable individual differences in psycho-
logical and physiological responsivity to stimuli (Rothbart et al.,
2001). Perhaps the best understood temperamental construct is
behavioral inhibition (Fox et al., 2005). Behaviorally inhibited
children exhibit heightened vigilance, negative affect, and reac-
gan et al., 1988a; Kagan and Snidman, 1991). Physiological pat-
electroencephalogram asymmetry (Kagan et al., 1987; Calkins et
al., 1996; Fox et al., 1996).
Although attentional aspects of behavioral inhibition tradi-
tionally have been attributed to enhanced amygdala reactivity in
response to cues that provoke withdrawal (Kagan et al., 1987;
Schwartz et al., 2003), virtually no research on behavioral inhibi-
be associated with biased responses to both rewards and punish-
ments (Reynolds and Berridge, 2002; Roitman et al., 2005). In a
preliminary study, we compared performance on the monetary
incentive delay (MID) task (Knutson et al., 2001a) in college
students categorized by shyness (Hardin et al., 2006). Results
showed faster responses to incentives in shy versus not shy stu-
dents, interpreted as enhanced reward sensitivity. Several func-
task implicate striatal circuitry in psychological processes en-
gaged by monetary incentives (Knutson et al., 2000, 2001a,b;
Bjork et al., 2004). Specifically, such work demonstrates striatal
activation to cues that elicit anticipation of monetary incentives
and enhanced motor performance (Knutson et al., 2000). Thus,
our behavioral findings suggest that neural correlates of behav-
ioral inhibition may be more widespread than previously
The present study uses fMRI and the MID task in a unique
cohort of adolescents characterized since infancy on tempera-
ment measures. Neural activation was examined in striatal com-
ponents based on regional specialization in incentive processing.
For example, nucleus accumbens and caudate are implicated in
coding cue properties, and putamen is involved in motor re-
sponse (Berns et al., 2001; Knutson et al., 2001a; Delgado et al.,
2003; O’Doherty et al., 2004; Zink et al., 2004; Daw et al., 2005;
Haruno and Kawato, 2006). Regionally parsing the striatum is
important because the MID involves processing cue salience and
based on evidence supporting the role of the amygdala in re-
sponse to rewards as well as to negative stimuli (Baxter et al.,
2000; Breiter et al., 2001; Schwartz et al., 2003; Ernst et al., 2005)
This work was supported in part by the Intramural Research Program of the National Institutes of Health–
National Institute of Mental Health and by National Institute of Child Health and Development Grant HD 17899
TheJournalofNeuroscience,June14,2006 • 26(24):6399–6405 • 6399
1988; Kagan, 1994).
We hypothesized that behaviorally inhibited adolescents
adolescents to increasing monetary incentives. This hypothesis
was based on our past behavioral work in college students (Har-
din et al., 2006) and children (Henderson, 2003). Given the pu-
tative role of the amygdala in anxiety and behavioral inhibition
non-inhibited adolescents would show enhanced amygdala acti-
vation for potential monetary loss.
Participants. Adolescents were drawn from cohorts participating in a
age, 433 subjects were screened for motoric and emotional reactivity to
novel visual and auditory stimuli (Kagan and Snidman, 1991; Calkins et
al., 1996). Of the 433 infants screened, 153 with reactivity scores at the
years, electroencephalogram data, parent-reported temperament sur-
veys, and observations of children’s reactions to unfamiliar stimuli and
peers were collected (Calkins et al., 1996; Fox et al., 2001). Previous
analyses involving these children up to 4 years of age has been described
by Fox et al. (2001) and Henderson et al. (2004).
Of the 153 children followed longitudinally, 44 were recruited in ado-
lescence (ages 10–15 years) to participate in the present study. The 44
children were selected based on their degree of behavioral inhibition as
determined by a composite of assessments collected in childhood. The
behavioral inhibition composite included laboratory measures of social
reticence, maternal ratings of shyness from the Colorado Child Temper-
ament Inventory (Buss and Plomin, 1984), and maternal ratings of in-
ternalizing problems from the Child Behavior Checklist (Achenbach et
al., 1991). To ensure that the children selected for the current study
reflected the full distribution of behavioral inhibition in the larger co-
hort, selection began by moving inward from the two extremes and out-
ward from the median of the composite. Scale scores of these measures
posite (range, ?0.70 to 1.63; mean ? SD, 0.07 ? 0.65). To dichotomize
the behavioral inhibition composite, standardized scores of behavioral
inhibition at 14 and 24 months and social reticence at 4 and 7 years were
used in a cluster analysis (supplemental Table 1, available at www.
jneurosci.org as supplemental material). A two-cluster solution was de-
levels of behavioral inhibition and social reticence in both toddlerhood
and early childhood, respectively, were higher in cluster one and were
thus labeled “behaviorally inhibited” (BI); cluster two was labeled “be-
haviorally non-inhibited” (BN). For complete details of inhibition clas-
sification, see supplemental data 1 (available at www.jneurosci.org as
Of the 44 adolescents selected for the neuroimaging study, five de-
braces, severe psychopathology, use of psychoactive substance); for
three, technical problems prohibited data acquisition. Adolescents who
did and did not complete the scan were comparable in age (t(42)? 0.33,
NS), intelligence quotient (IQ) (t(40)? 1.61, NS), sex (?2
cents who completed the scan, 13 were classified as BI (age, mean ? SD,
13.40 ? 1.68 years; IQ, mean ? SD, 118.7 ? 10.17; sex, five male, eight
female), and 19 were classified as BN (age, mean ? SD, 13.26 ? 1.80
years; IQ, mean ? SD, 117.74 ? 8.41; sex, 9 male, 10 female). The two
NS), or sex (?2
Diagnoses of current psychiatric illness were ascertained using the
Schedule for Affective Disorders and Schizophrenia for School Aged
clinician who exhibited satisfactory reliability on the exam (? ? 0.75 for
(1,32)? 0.25, NS).
an internalizing or externalizing disorder, whereas BN adolescents only
had externalizing disorders. Analyses including and those not including
data from these seven adolescents generated identical conclusions. As a
result, we retained these subjects in the analyses reported here.
The institutional review boards at the National Institute of Mental
Health (Bethesda, MD) and the University of Maryland (College Park,
informed assent/consent to participate in the study.
MID task. The MID task has been shown in a series of fMRI studies to
consistently engage the striatum during anticipation of potential mone-
tary gain and loss (Knutson et al., 2000, 2001a,b; Bjork et al., 2004). A
parametric version of the task manipulates motivation for obtaining a
gain or for avoiding a loss by varying the amount of money at stake
(Knutson et al., 2001a). The MID task required participants to respond
with a button press as quickly as possible during the presentation of a
target. If the participants succeeded in pressing the button during target
presentation, they either won or avoided losing money.
250 ms, whereas the fixation delay (2000–2500 ms) and target (160–250
ms) each appeared at variable intervals. Circle cues (n ? 64) indicated a
potential monetary gain (reward) if the button press occurred quickly
enough at target onset; square cues (n ? 64) signified a potential mone-
tary loss (punishment) if the button press did not occur quickly enough
at target onset; and triangle cues (n ? 16) indicated no money at stake.
of a gain, loss, or no change and indicated current, cumulative dollar
Participants were told that they would receive the dollar amount won.
the scan, which served two main purposes. First, it minimized learning
of each subject’s reaction time (RT) for standardizing task difficulty,
minimizing a potential confound of large performance differences over-
was tailored to each participant’s ability by adjusting target duration on
the actual task such that participants succeeded on ?66% of their re-
sponses using mean RT and accuracy rate from the practice task (Knut-
son et al., 2001a).
fMRI acquisition. Scanning occurred in a General Electric (Waukesha,
WI) Signa 3 tesla magnet. A Cedrus (San Pedro, CA) Lumina response
box recorded behavioral data. MID stimuli were projected onto a screen
at the foot of the scanner bed and viewed with mirrors mounted on the
head coil. Head movement was constrained by the use of foam padding.
Functional scans were acquired with the following sequence parameters.
in the sagittal plane using a T2*-weighted echo-planar sequence with a
repetition time (TR) of 2500 ms, echo time (TE) of 23 ms, and flip angle
64 mm, and field of view (FOV) was 24 cm. To allow for signal stabiliza-
structural image was also acquired for each subject using a T1-weighted
standardized magnetization prepared spoiled gradient recalled echo se-
quence: 124 1 mm slices, TR of 8100 ms, TE of 32 ms, flip angle of 15°,
matrix size of 256 ? 256 mm, and FOV of 24 cm.
fMRI data analysis. Analysis of Functional and Neural Images (AFNI)
software was used to analyze fMRI data (Cox, 1996). Standard prepro-
cessing of echo-planar data included slice time correction, motion cor-
rection, and spatial smoothing with a 6 mm full-width half-maximum
a voxelwise basis to smooth out deviations in signal ?2.5 SD from the
tuations in signal that were not temporally indicative of a hemodynamic
response (either ?0.011 or ?0.15 s). Each subject’s data were converted
6400 • J.Neurosci.,June14,2006 • 26(24):6399–6405Guyeretal.•StriatalFunctionandBehavioralInhibition
to percentage signal change using each subject’s voxelwise time series
mean as a baseline.
Preprocessed time series data for each individual were analyzed by
multiple regression (Neter et al., 1996). The regression model consisted
of regressors of interest, six regressors modeling effects attributable to
residual motion (using the motion correction factors in the x, y, and z
planes and in the yaw, pitch, and roll dimensions), and two regressors
modeling baseline and linear trends for each of the two runs. Regressors
of interest included cues signaling trial type (e.g., large, medium, and
small potential gain and large, medium, and small potential loss) and
were estimated based on onset time of different event types during the
Contrasts of whole-brain blood oxygen level-dependent (BOLD) ac-
tivation were created for each subject for cues signaling potential gains
and potential losses of (1) large $ versus no $, (2) medium $ versus no $,
and (3) small $ versus no $. Based on our a priori hypothesis, we com-
pared groups on change in striatal and amygdala activity during antici-
pated gains and losses at different incentive magnitudes. Mean contrast
values were generated for all voxels within the striatum [including nu-
dala. To examine the degree to which between-group differences oc-
curred more generally throughout the brain, this method was repeated
for the primary visual cortex [Brodmann area (BA) 17] and the primary
motor cortex (BA4). BA17 is a region that may be affected by stimulus
salience, but we expected no between-group differences in BA17 activa-
stimulus salience and group status to both potentially influence moti-
vated behavior and thus engage BA4. Talairach anatomical boundaries
provided by AFNI were used to define voxels that fell within each region
of interest (ROI) after spatial normalization (Talairach and Tournoux,
performed in SPSS (SPSS, Chicago, IL) using repeated-measures
ANOVA. The model for striatal activation included group (BI, BN) as a
between-subjects factor and incentive magnitude [small ($0.20), me-
dium ($1), large ($5)], valence (gain, loss), and striatal region (nucleus
els for the amygdala, BA17, and BA4 included group, incentive magni-
calculated as the net signal difference between anticipation of a small,
hemodynamic response function peak. Interactions between group and
characteristics of the MID task were the effects of primary interest. Be-
cause all striatal regions have been implicated differently in reward pro-
significant group ? striatal region effect was detected, we would then
interpret results for each striatal component separately given regional
functional specialization (Berns et al., 2001; Knutson et al., 2001a; Del-
Haruno and Kawato, 2006).
Behavioral data analysis. Level of task difficulty (ranging from 1 to 5,
corresponding to five sets of target duration) was adjusted at the begin-
ning of the task to normalize performance to ?66% accuracy across
participants. Mean task difficulty level was compared between groups
using a t test. Dependent variables included accuracy (i.e., proportion of
successful button presses during target presentation), RT for successful
hits (i.e., length of time between target onset and button presses leading
tor and valence and incentive magnitude as within-subjects factors. To
parallel the imaging analyses, which used $0 trials as a baseline, response
small potential loss) on a scale from ?5 (dislike very much) to ?5 (like
very much) indexing cue-elicited affective response. Affective ratings
were analyzed with a similarly constructed ANOVA.
No significant group differences were found on any of the task
tive values of each cue, however, influenced participants’
incentive magnitude indicated that participants’ preference of
cues increased as gain cue magnitude increased and decreased as
salience. Specifically, paired comparisons indicated that partici-
pants preferred ?$5.00 cues over ?$1.00 and ?$0.20 cues, and
?$1.00 cues over ?$0.20 cues (all p values ?0.03). In contrast,
participants disliked ?$5.00 cues more than ?$0.20 cues ( p ?
indicate the intensity of emotional response to the cues, did not
did not differ by valence (gains vs losses) on the intensity of their
affective response to the cues.
With regard to the striatum, results from the repeated-measures
ANOVA indicated significant main effects of incentive magni-
tude (F(2,60)? 20.20; p ? 0.001) and group (F(1,30)? 5.16; p ?
striatal regions and both gain and loss trials. Importantly, this
analysis also revealed a significant group ? incentive magnitude
interaction (F(2,60)? 3.30; p ? 0.04), whereby striatal activation
changed differently for the BI group relative to the BN group as
incentive magnitude increased (Fig. 2). Specifically, striatal acti-
larger in the BI group than in the BN group. Significant main
effects of valence (F(1,30)? 6.09; p ? 0.02) and region (F(2,60)?
3.30; p ? 0.04) were also found for mean percentage signal
0.10 ? 0.02). With regard to region, significantly greater activa-
Between-group comparisons of postscan affective ratings of anticipation cues
Guyeretal.•StriatalFunctionandBehavioralInhibitionJ.Neurosci.,June14,2006 • 26(24):6399–6405 • 6401
and nucleus accumbens (mean ? SE, 0.15 ? 0.03; p ? 0.001)
than in the putamen (mean ? SE, 0.07 ? 0.01). The caudate and
cause there was not a significant group ? region effect, no addi-
tional analyses were conducted to identify specific group-related
patterns of response. As an example, Figure 3 shows the group
differences in caudate activation at each incentive magnitude on
Because the sample included prepubertal and postpubertal
subjects and because sex and age differences have been noted in
striatal dopamine receptors (Andersen et al., 1997; Becker, 1999;
Mozley et al., 2001; Andersen et al., 2002), Figure 4 presents a
scatter plot to illustrate the distribution of sex, age group, and
magnitude. Percentage signal change was averaged for gain and
loss cues within the caudate, putamen, and nucleus accumbens
and age group were not significantly associated with striatal acti-
vation at any of the incentive levels (all r values ?0.10), whereas
behavioral inhibition status correlated significantly with greater
striatal activity during anticipation of medium (r ? 0.34; p ?
0.04) and large (r ? 0.51; p ? 0.003) incentives.
the interaction of group with valence or incentive magnitude.
However, the amygdala was sensitive to the different incentive
magnitudes (F(2,60)? 6.66; p ? 0.005). Specifically, amygdala
activation was greater during anticipation of the large (mean ?
p ? 0.01) incentives relative to the small incentive (mean ? SE,
0.01 ? 0.03). Amygdala activation did not differ as a function of
The analysis involving BA17 showed no significant main or
lack of activation in BA17 in response to the MID is consistent
with our expectation of specific task-related regional activation.
A group effect (F(1,30)? 8.44; p ? 0.01) and an incentive effect
(F(2,60)? 11.06; p ? 0.001) were found on BA4 activation. Spe-
cifically, BA4 activity was greater for the BI group (mean ? SE,
0.11 ? 0.02) versus BN group (mean ? SE, 0.02 ? 0.02) and
during anticipation of the large (mean ? SE, 0.10 ? 0.02; p ?
0.001) and medium (mean ? SE, 0.07 ? 0.02; p ? 0.03) incen-
interaction effects were found. Thus, between-group differences
in BA4 activity were not moderated by incentive salience or cue
The present study showed that adolescents previously classified
as behaviorally inhibited in early childhood demonstrated en-
hanced sensitivity to incentives relative to adolescents not classi-
fied as such. As hypothesized, enhanced sensitivity was manifest
as greater striatal activation while anticipating monetary gain or
loss. Importantly, striatal activation differed between groups as a
function of incentive magnitude. These group differences
emerged despite comparable behavioral performances.
The current findings relate evaluation of stimulus salience to
behavioral inhibition. We view salience as a quantifiable value
that influences motivation to act on a stimulus. Previous studies
show that stimulus salience influences striatal response to re-
wards (Zink et al., 2003, 2004, 2006). For example, Zink et al.
(2004) found that striatal activation depends on the salience of
rewards rather than their value. Other work associates striatal
response with performance of actions aimed at reward acquisi-
tion (Tricomi et al., 2004). The present study related between-
subject variation in behavioral inhibition to between-subject
variation in striatal activation.
Our second hypothesis regarding amygdala response was not
incentive magnitude but not based on inhibition status. To date,
the only other fMRI study to examine temperamentally based
group differences found enhanced amygdala activity in response
to novel, neutral face stimuli in adults who had been classified as
inhibited as toddlers compared with adults who were not previ-
ously classified as such (Schwartz et al., 2003). The lack of
the MID loss stimuli were not novel enough to elicit greater
amygdala activation in the behaviorally inhibited group as dem-
onstrated previously (Schwartz et al., 2003). Nonetheless, find-
ings from both studies suggest that the early temperamental dis-
position of behavioral inhibition is associated with enhanced
Behaviorally, we did not find group differences in MID per-
formance. This was expected because, by design, difficulty was
adjusted to match subject ability. In previous work, however, we
documented greater sensitivity to rewards in shy versus non-shy
college students, as indexed by reaction time (Hardin et al.,
ber of factors, including the following: (1) experimental condi-
tions, such as fMRI environment; (2) manipulation of target du-
ration in the present study but not in our behavioral study; (3)
parameterization of the present MID task; (4) smaller sample
size; (5) age of samples; and (6) a different measure of tempera-
i.e., enhanced response to reward cues in shy/behaviorally inhib-
ited subjects compared with non-shy/non-inhibited subjects.
Two exploratory findings also emerged from the present
study. First, although valence modulated striatal activity (i.e.,
greater activation in response to gain vs loss cues) across groups,
versus loss in driving striatal activity is consistent with previous
work using the MID task (Knutson et al., 2001a; Bjork et al.,
and extracted at fMRI acquisition during anticipation of large, medium, and small incentives
6402 • J.Neurosci.,June14,2006 • 26(24):6399–6405Guyeretal.•StriatalFunctionandBehavioralInhibition
2004). Second, group differences in striatal activation were not
The general prominence of caudate and nucleus accumbens ac-
tivation to incentives is consistent with studies using the present
MID task (Knutson et al., 2001a) as well as studies using other
et al., 2004). A recent study attempted to dissociate the reward-
related function of caudate/nucleus accumbens from that of the
putamen (Haruno and Kawato, 2006). The authors found that
caudate and nucleus accumbens activity correlated with reward-
prediction errors, whereas putamen activity correlated with the
degree to which reward associations were learned and realized,
i.e., stimulus–action reward (Haruno and
ity in the caudate and nucleus accumbens
istics that more specifically probe the un-
certainty of reinforcement and reward-
prediction errors than the execution of a
motivated action. Currently, data in hu-
One caveat of the present findings is
that enhanced striatal activation in the be-
haviorally inhibited group relative to the
non-inhibited group could also reflect a
nonspecific, generalized state of higher
arousal in anxiety-prone subjects. Al-
though this possibility cannot be ruled
out, the absence of group differences in
primary visual cortex activity, which is sensitive to attention
states (Astafiev et al., 2004; Kastner and Pinsk, 2004), argues
Observed striatal differences may indicate increased activa-
tion in a distributed motor circuit. Consistent with this possibil-
activity than the non-inhibited group. These findings are com-
patible with past work documenting higher muscle tension in
inhibited versus non-inhibited children (Kagan, 1994). More-
over, in both behaviorally inhibited and non-inhibited subjects,
greater motor cortex activity was also found during anticipation
of the larger incentives. This pattern is consistent with previous
2000). By inference, these data suggest that both behavioral inhi-
bition and stimulus salience influence functioning in corticos-
triatal motor circuitry (Hikosaka et al., 1989). The absence of
group ? incentive or group ? valence interactions, however,
indicates that between-group differences in motor cortex activa-
tion are not modulated by incentive magnitude or cue valence.
Thus, group ? incentive interactions are limited to the striatum.
ple size. Although the groups did not differ significantly in sex
and age, our sample size did not permit a full test of whether
temperamentally based group differences in striatal response to
incentives are further influenced by sex and age/pubertal status.
We also note that, although sex- and age-related differences in
dopamine levels may influence striatal function (Andersen et al.,
direction of these influences is not well known in human adoles-
cent samples. Thus, future studies using larger adolescent sam-
ples are necessary to tease apart these potential influences on the
relationship between striatal function and behavioral inhibition.
Both behavioral [e.g., reticence with peers (Rubin et al.,
et al., 1995)] response profiles documented in inhibited children
early in life suggest that this form of temperament is character-
that has typically been understood in terms of enhanced reactiv-
current study extends this characterization by demonstrating
that an inhibited temperament is associated with enhanced neu-
ral sensitivity in brain regions that facilitate motivated behavior
in response to nonsocial reward stimuli. One interpretation of
by inhibition status, sex, and age group (before or after 13 years of age). Percentage signal
bens separately at small, medium, and large incentive magnitudes. Average signal change
Guyeretal.•StriatalFunctionandBehavioralInhibitionJ.Neurosci.,June14,2006 • 26(24):6399–6405 • 6403
may have heightened striatal activation because they are con-
cerned about making errors, particularly as the stakes increase
with larger incentives. The greater incentive-related increase in
striatal activation in the behaviorally inhibited group may indi-
exhibit increased motivation and enhanced vigilance in response
to highly salient stimuli, perhaps energized by a strong desire to
avoid failure (Eysenck and Calvo, 1992). Previous work demon-
strating enhanced error monitoring in behaviorally inhibited
children supports this possibility (Henderson, 2003). Based on
gan et al., 1988b; Rubin et al., 2002), future work might consider
whether this sensitivity to nonsocial rewards extends to social
rewards as well.
The current findings may signify a developing vulnerability
for later psychopathology associated with behavioral inhibition
that is characterized by functional anomalies in incentive pro-
thology has emphasized a relationship with both anxiety disor-
ders (Hirshfeld et al., 1992; Biederman et al., 1993, 2001;
Schwartz et al., 1999) and depression (Caspi et al., 1996; Rosen-
baum et al., 2000). Documenting between-group differences in
behavioral tendencies, such as temperament and personality
traits, as predictors of neural response is important for identify-
ing individuals who may be at risk for developing psychopathol-
ogy (Canli et al., 2002). A recent study using the MID found
reduced striatal activity during reward anticipation in adoles-
pared with healthy adolescents (Scheres et al., 2006). These data
implicate diminished salience of anticipated rewards in ADHD,
findings opposite to those from our study revealing enhanced
sensitivity in behaviorally inhibited adolescents. Such data are
consistent with other work examining the relationship between
behavioral disinhibition and ADHD (Hirshfeld-Becker et al.,
2002). Together, these studies suggest that research on between-
group differences in neural response to incentives may elucidate
underlying substrates of specific adolescent psychopathologies
(Ernst et al., 2006). Thus, the present findings offer a possible
ies on individual differences associated with risk for specific
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