Neural Correlates of Response Inhibition in Pediatric
Manpreet K. Singh, M.D., M.S.,1,2Kiki D. Chang, M.D.,1Paul Mazaika, Ph.D.,2Amy Garrett, Ph.D.,2
Nancy Adleman, Ph.D.,2Ryan Kelley, B.S.,2Meghan Howe, M.S.W.,1and Allan Reiss, M.D.2
Objectives: Pediatric bipolar disorder is characterized by core deficits in mood and executive function and commonly co-
an element of executive function, which, if aberrant, may interfere with learning and information processing.
Methods: Children (9–18 years) with bipolar I or II disorder (BD, n¼26) and age, gender, and intelligence quotient (IQ)
comparable healthy children (HC, n¼22) withoutany psychopathologywere givenastandardizedGo=NoGo computerized
task measuring response inhibition. A whole-brain functional magnetic resonance imaging (MRI) group analysis was
performed using statistical parametric mapping software (SPM2) for comparing NoGo to Go epochs.
Results: There were no statistically significant group differences between groups in age, gender, or ethnicity. The BD group
had high rates of co-morbid disorders, including 81% with ADHD, 62% with oppositional defiant disorder (ODD), and 46%
group differences in response inhibition on NoGo trials (p¼0.11). In the NoGo?Go contrast, the BD group showed
increased neural activation in the right dorsolateral prefrontal cortex (DLPFC) compared to HC (T¼4.21, p<0.001).
Conclusions: During accurate NoGo but impaired Go trial performance, children with BD showed increased right DLPFC
activation versus controls, suggesting increased recruitment of executive control regions for accurate response inhibition.
Studies relating these results to mood regulation in pediatric BD are warranted.
in mood and attention and may manifest behavioral and cog-
nitive symptoms that may interfere with an ability to learn
(McClure et al. 2005) and process information (Rich et al. 2006),
which may consequently interfere with interpersonal (Geller et al.
2000) and academic functioning (Pavuluri et al. 2006). Attention-
deficit=hyperactivity disorder (ADHD) may precede (Tillman and
Geller 2006) or co-occur (Singh et al. 2006) with BD at high rates
and may be among several factors that contribute to the progressive
functional impairment and poor outcome (DelBello et al. 2007) for
BD. Frontostriatal dysfunction in ADHD is well established (Vai-
et al. 2005; Epstein et al. 2007b; Suskauer et al. 2007; Wodka et al.
2007b), but little is known about the characteristics or neural cor-
relates of cognitive dysfunction and its relationship to mood
symptoms when ADHD co-occurs with BD.
ediatric bipolar disorder (BD) is characterized by deficits
Among several elements of executive functioning originating
from frontostriatal regions of the brain, component functions of
response inhibition include the ability to withhold a preplanned
response, interrupt an already initiated process, avoid interference,
and delay a response (Tamm et al. 2002). Consequences of dys-
function in response inhibition include behavioral dyscontrol and
of psychiatric disorders. Although response inhibition improves
with maturity level (Tamm et al. 2002), deficits in response inhi-
bition have been consistently observed in adults (Blumberg et al.
2003a; Larson et al. 2005), as well as in youths with (Leibenluft
et al. 2007) and at high risk for (Singh et al. 2008) BD when
compared to age-comparable controls. In addition to being ob-
served across the lifespan, deficits in this domain of executive
function have also been observed across mood states in affected
individuals (Blumberg et al. 2003a) and their unaffected rela-
tives (Frangou et al. 2005; Giakoumaki et al. 2007), suggesting
that impaired response inhibition may represent an important
1Pediatric Bipolar Disorders Program and2Center for Interdisciplinary Brain Sciences Research, Stanford University School of Medicine, Stanford,
Portions of this manuscript were presented at the 53rd Annual Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL,
December 9–12, 2007.
JOURNAL OF CHILD AND ADOLESCENT PSYCHOPHARMACOLOGY
Volume 20, Number 1, 2010
ª Mary Ann Liebert, Inc.
underlying trait of BD, particularly in the presence of co-
Like its behavioral manifestation, the neural basis of response
inhibition may be task-dependent (Mostofsky et al. 2003; Wager
et al. 2005; Simmonds et al. 2008) and developmentally dynamic
(Bunge et al. 2002; Tamm et al. 2002; Rubia et al. 2006). However,
many studies agree that successful response inhibition generally
involves interactive engagement of the ventrolateral (VLPFC) and
dorsolateral (DLPFC) prefrontal cortices to provide inhibitory con-
trol (Liddle et al. 2001), the striatum (Vink et al. 2005) to control
the execution of planned motor responses, and the anterior cingu-
late cortex (ACC) to make and monitor response-related decisions
(Braver et al. 2001; Liddle et al. 2001). Individuals with BD are at
particular risk for unsuccessful response inhibition due to fron-
of this condition (Blumberg et al. 2003a; Blumberg et al. 2003b;
Chang et al. 2004; Elliott et al. 2004; Strakowski et al. 2004; Adler
et al. 2004) and due to its common co-occurrence with ADHD
(Adler et al. 2005).
Among functional magnetic resonance imaging (fMRI) studies,
few have investigated the neural correlates of co-occurring BD and
ADHD and have shown inconsistent findings (Adler et al. 2005;
Leibenluft et al. 2007). In one study, BD adolescents with (n¼11)
and without (n¼15) co-morbid ADHD were compared. The
groups performed equally well on the single-digit continuous per-
formance task administered during fMRI. However, relative to the
group without ADHD, subjects with co-morbid BD and ADHD
showed decreased activation in the VLPFC and ACC and increased
activation in the posterior parietal and medial temporal gyrus
during the task (Adler et al. 2005). The task in this study did not
lack of a healthy control group. Another fMRI study using a stop-
signal task paradigm compared motor inhibition in bipolar ado-
lescents withandwithout ADHD andhealthyadolescents without a
personal or family history of any psychiatric disorders. The healthy
adolescents showed greater bilateral striatal and right VLPFC ac-
tivation than bipolar subjects during unsuccessful stop trials (Lei-
benluft et al. 2007). During this task, patients with BD and ADHD
did not differ in any region of interest from BD subjects without
ADHD. In addition, comparison subjects had greater activation
than BD subjects with ADHD in the striatum, bilateral anterior
cingulate, and bilateral ventral prefrontal cortex, but only showed
greater activation compared to BD without ADHD in the bilateral
accumbens and left caudate. Even with a comparison group of
bipolar adolescents without ADHD, this study illustrated the
challenges associated with trying to assess the independent con-
with respect to between-group behavioral or brain activation dif-
ferences. This study was limited by region-of-interest analyses,
which may have reduced detection of multiple regions involved in
response inhibition (Aron et al. 2007). Careful task selection, em-
ployment of a whole-brain analysis, and examination with larger
numbers of subjects with comparable heterogeneity may clarify
these inconsistent results and provide a more convergent model of
frontostriatal dysfunction in adolescents with co-occurring BD and
With these considerations in mind, we compared behavioral
variables and corresponding whole brain activation between BD
and community, age-comparable healthy adolescents (healthy
controls, HC) while performing a Go=NoGo task. To optimize
statistical power insufficient in event-related designs and to ensure
adequate performance on executive function in a pediatric popu-
lation with a clinically heterogeneous disorder, a traditional
Go=NoGo task was employed with experimental blocks comprised
of both Go and NoGo trials with half the trials in the experimental
block containing NoGo conditions.
Thus, based on our prior work and the extant literature on re-
sponse inhibition in BD, we hypothesized that, compared to HC,
BD adolescents would have high rates of co-occurring ADHD and
would exhibit lower accuracy and increased error rates while per-
forming the Go=NoGo task. We also predicted that the BD group
would manifest reduced activation in frontostriatal regions com-
pared to controls, which, in turn, would correspond to performance
during the response inhibition task. Finally, we hypothesized that
more pronounced symptoms of ADHD, but not mania or depres-
sion, would be correlated with decreased neural activation in
frontostriatal regions during response inhibition in our BD group.
Materials and Methods
Children and adolescents between the ages 9 and 18 years who
met Diagnostic and Statistical Manual of Mental Disorders, 4th
edition text revision (DSM-IV-TR) (American Psychiatric Asso-
ciation 2000) diagnostic criteria for BD I or II (n¼26) were re-
cruited by referral to academic adult and pediatric BD clinics and
the surrounding community. Age- and gender-comparable healthy
control children and adolescents (HC, n¼22) without a history of
psychiatric diagnoses or the occurrence of such diagnoses in their
first-degree relatives were recruited from the same community.
Demographic and clinical characteristics were collected for all of
subjects at the beginning of the study, including age, sex, intelli-
gence quotient (IQ), and handedness. Handedness was assessed by
the Crovitz Handedness Questionnaire (Crovitz and Zener 1962).
BD subjects were excluded by the presence of a pervasive devel-
opmental disorder, seizure disorder, substance use disorder, IQ less
than 80, and the presence of metallic implants or braces. A total of
81% of BD subjects were offspring of parents with BD I or II.
Because a previous study has suggested that stimulants have a
direct effect on the performance of a response inhibition task
(Epstein et al. 2007b), all participants in the study were washed out
from stimulants 24 hours prior to neuroimaging. To avoid risk of
mood destabilization, BD subjects were allowed to continue any
atypical antipsychotics, or antidepressants. Subjects’ medication
history was obtained and used for exploratory and covariate ana-
lyses of neural findings.
in St. Louis Kiddie-Schedule for Affective Disorders and Schizo-
phrenia (WASH-U K-SADS) (Geller et al. 1996), administered
separately to parents and children, by raters blind to diagnostic
group, with established symptom and diagnostic reliability
(k>0.9). All diagnoses were determined by a consensus confer-
ence attended by a child and adolescent psychiatrist (K.D.C.) and
the WASH-U K-SADS interviewer, after both parent and child
interviews were completed. Mood symptom severity in BD sub-
jects was assessed using the Young Mania Rating Scale (YMRS)
(Young et al. 1978), and the Children’s Depression Rating Scale–
Revised Version (CDRS-R) (Poznanski et al. 1979) by raters with
established symptom reliabilities (ICC>0.9). An independent
parent assessment of symptoms of inattention and hyperactivity
(ADHD) was obtained using the 10-item abbreviated Conners’
Rating Scale (Rowe and Rowe 1997; Tillman and Geller 2005).
Parent psychiatric assessments in both groups were confirmed with
16SINGH ET AL.
the Structured Clinical Interview forDSM-IV (SCID-P) (First et al.
1996) by raters who were blind to diagnostic group and who had
established diagnostic interrater reliability (k>0.9).
Behavioral assessment and analysis
Subjects were administered the Wechsler Abbreviated Scale of
Intelligence (WASI) (Psychological Corporation 1999) and a
computerized and standardized neuropsychological task which
measures response inhibition. The experimental task consisted of
two alternating conditions: Go and NoGo=Go (Fig. 1). Throughout
both conditions, subjects viewed a series of letters once every
2 seconds (500msec stimulus 1,500msec interstimulus interval
[ISI]) and responded with a key press, using the forefinger of the
right hand, to every letter except the letter ‘‘X,’’ to which they were
instructed to withhold response. In the Go (control) condition,
subjects were presented a random sequence of letters other than the
letter ‘‘X.’’ In the NoGo=Go (experimental) condition, subjects
were presented with the letter ‘‘X’’ 50% of the time. The entire task
lasted a total of 372 seconds and consisted of 12 alternating
26-second epochs of Go and NoGo=Go conditions flanked at the
beginning and end by 30-second rest epochs during which the
subject passively viewed a blank screen. Each epoch consisted of a
2-second instruction alerting the subject to the present task condi-
tion followed by 12 trials per epoch. Responses and reaction times
For the in-scanner task, the proportion of trials to which subjects
correctly responded in a Go trial (Go% correct) and correctly in-
hibited in a NoGo trial (NoGo% correct) was calculated. Partici-
the scanner task fell at or below chance on both Go% correct and
in Go trials (GoRT) and mistakenly pressing the key in NoGo trials
(NoGoRT) were also calculated. Accuracies to NoGo trials (false
this paradigm. However, to take into account target hits as well as
false alarms, d-prime was calculated by subtracting z-transformed
proportions of false alarms from proportions of positively re-
sponded Go trials (hits). d-Prime provides a measure of sensitivity
in the discrimination and ultimate detection of target stimuli rela-
tive to nontarget stimuli (Wickens 2002), a key component of
cognitive control (Nigg and Casey 2005) (i.e., how well the subject
can discriminate and appropriately respond to targets and nontar-
gets). Each behavioral measure was subjected to t-test or Wilcoxon
Rank Sum Test, for parametric and nonparametric data, respec-
tively, to assess for significant differences in performance between
the two groups.
Functional MRI procedures
Image Acquisition, Motion Correction, and Processing.
Images were acquired with a 3T GE Signa scanner (General
Electric, Milwaukee, WI) using a standard fMRI whole-head coil.
Functional images were collected with a T2*-weighted spiral pulse
sequence with parameters of repetition time (TR)¼2,000msec,
echo time (TE)¼30msec, flip angle 808, voxel size 3.12?3.12mm,
order shimming method was used before acquiring fMRI data to
reduce field inhomogeneities. Structural images were collected
to aid in localization of the functional data, using high-resolution,
T1-weighted, spoiled gradient-recalled acquisition in the steady-
state (GRASS) three-dimensional MRI sequences with the fol-
lowing parameters: TR¼35msec, TE¼6msec, flip angle¼458,
field of view¼24cm, 124 slices in the coronal plane, and a
256?192 matrix. Functional images were processed withstatistical
parametric mapping software (SPM2), including realignment,
transformation to Montreal Neurological Institute (MNI)-space,
followed by smoothing with full width at half-maximum
Custom motion-processing methods were applied to maximize
of them had high motion during the scan (7=22 HC and 12=26 BD
subjects moved more than 1mm). Simply discarding high-motion
subjects could result in insufficient remaining subjects to achieve a
strong group result. Conversely, including subjects with large
motion can influence group results by motion-induced errors from
the large motion subjects. Thus, artifact repair was used to detect
caused image reconstruction and spin history errors (Mazaika et al.
2007) (http:= =cibsr.stanford.edu=tools=). This was followed by
series of letters presented for 500msec each, with a 1,500-msec interstimulus interval (ISI). In the experimental epoch, subjects were
instructed to respond with a key press for every letter except ‘‘X.’’ In the control epoch, subjects were presented a random sequence of
letters other than the letter ‘‘X’’ and instructed to respond for every letter.
The Go=NoGo task sequence consisting of 12 alternating experimental and control epochs. In each epoch, subjects viewing a
RESPONSE INHIBITION IN PEDIATRIC BIPOLAR DISORDER 17
motion adjustment, which corrected for residual signal variation
errors after image realignment (Mazaika et al. 2007). The estima-
tion accuracy for each subject after repairs was assessed using a
Global Quality metric of the dispersion of estimates over the entire
brain (Mazaika et al. 2007), and subjects with outlying Global
Quality scores were excluded from the selected groups.
Of the originally recruited 27 HC and 34 BD subjects, 13 were
excluded due to poor scan quality, poor behavioral data, motion
greater than 5mm, or poor global quality scores, leaving 22 HC
and 26 BD subjects available for group analysis. A combination
of these methods recovered many large-motion fMRI data sets
and indicated which data sets were not recoverable. In this
way, we were able to maximize the number of usable subjects in
our clinical group study to 79% (48=61) of all fMRI data sets
Chi-squared analysis, two sample t-tests, and effect sizes
(Cohen d) were applied to demographic, clinical, and behavioral
data. Statistical analysis was performed for individual and group
data using the general linear model and the theory of Gaussian
random fields as implemented in SPM2. Activation foci were su-
perimposed on high-resolution, T1-weighted images, and their lo-
cations were interpreted using the Talairach atlas and known
neuroanatomical landmarks. Individual contrast images were com-
puted for conditions in which performance of Go blocks was sub-
tracted from the NoGo blocks. These contrast images were
analyzed with SPM2 using a general linear model to determine
voxelwise t-statistics. One-sample t-tests were used to determine
within-group activation and two-sample t-tests were used to de-
termine between-group differences. Between-group analyses used
a random effects model (Holmes and Friston 1998). Clusters of
activation to display were defined as those surpassing a height
threshold of p<0.001 and an extent threshold of 40 voxels for all
within- andbetween-group analyses(Fristonet al.1995),where the
height threshold provides a statistical threshold for the number
of activated regions within a given volume such as an individual
voxel (i.e., is analogous to a t-test), and an extent threshold repre-
sents the minimum size of contiguous voxels which comprise
a particular cluster (www.scholarpedia.org=article=Statistical_
parametric_mapping_(SPM)._) Within-BD group correlations
were performed between activation and YMRS, CDRS, and Con-
ners’ rating scales. Finally, functional activations were compared
within the BD group for the presence versus absence of past ex-
posure to certain psychotropic medications including lithium,
atypical antipsychotics, valproic acid, and psychostimulants.
Demographic and clinical characteristics
There werenostatistically significantgroupdifferences between
BD (n¼26) and HC (n¼22) subjects in age (15.4?2.7 vs.
14.3?2.5 years), sex (female, 38% vs. 41%), handedness (right,
87% vs. 100%), ethnicity (Caucasian, 88% vs. 81%), or full-scale
IQ scores (109?12 vs. 111?8). (The between-group activation
differences presented below did not change significantly after
covarying for these demographic variables.) Eighteen (69%) of the
BD children met DSM-IV-TR criteria for BD I and 8 (31%) met
criteria for BD II. Consistent with previous reports (Findling et al.
2001; Biederman et al. 2004; Singh et al. 2006), 21 (81%) BD
children had ADHD, 16 (62%) BD subjects had oppositional de-
fiant disorder, and 12 (46%) met criteria for anxiety disorders
(Table 1). HC children were free of DSM-IV Axis I mood, psy-
chotic, disruptive behavioral, or anxiety disorders.
Table 1. Demographic and Clinical Variables of Children with Bipolar Disorder and Healthy Control Children
VariableBD children (n¼26)
HC children (n¼22)
Age, mean (SD), years
Male, n (%)
Right handedness, n (%)
Full scale IQ, mean (SD)
Ethnicity, n (%), white
DSM-IV-TR Axis I diagnosis, n (%)
Bipolar I disorder
Bipolar II disorder
Oppositional defiant disorder
More than one psychiatric disorder
YMRS, mean (SD)
CDRS, mean (SD)
Conners’ Rating Scale raw scores, mean (SD)
Conners’ T scores, mean (SD)
History of medication exposure, n (%)
More than one medication
Abbreviations: BD¼Bipolar disorder; HC¼healthy controls; IQ¼Intelligence quotient; SD¼standard deviation; DSM-IV, Diagnostic and Statistical
Manual of Mental Disorders, 4thedition; YMRS¼Young Mania Rating Scale; CDRS¼Children’s Depression Rating Scale; N=A¼not applicable.
18 SINGH ET AL.
The BD group had lower proportions of correct responses on Go
(84% vs. 96%, T(46)¼3.35, p¼0.002) and overall Total (85% vs.
94%, T(46)¼4.12, p¼0.0002) trials as compared to the HC group
(Table 2). This suggests significant deficits in sustained effort or
vigilance during a low cognitive load component of the task.
response inhibition as determined by percentage correct on NoGo
trials (p¼0.11), reaction times needed for correctly responding in
Go trials (Z¼0.86, p¼0.39), or reaction times for false alarms
(Z¼0.82, p¼0.41). The BD group showed lower scores on
d-prime than the HC group (3.98 [2.5] vs. 5.69 [3.2], T¼2.07,
Functional MRI results
Table 3 and Fig. 2 summarize the whole-brain functional neu-
roimaging results contrasting the NoGo minus Go (NoGo?Go)
conditions. There were no statistically significant differences be-
tween groups for the Go-NoGo, Go-Rest, NoGo-Rest contrasts.
For the NoGo?Go contrast of interest, the BD group showed
greater activation in the right DLPFC (BA 9) relative to the HC
group. The HC group did not show any regions of statistically
greater activation relative to the BD group for the NoGo?Go
Within-group analyses showed that the HC group had greater
activation in the inferior frontal gyrus (Brodmann area [BA] 9,
posteriorly) and the ACC during the NoGo condition relative to the
Go condition. Within the BD group, significant activation was seen
in the inferior frontal lobe, right ACC, and in the left occipital lobe
for the NoGo?Go contrast. For the BD group, YMRS and CDRS
symptom scores did not correlate significantly with activation in any
brain region for the NoGo?Go contrast. (Symptom scores were
Conners’ raw scores were positively correlated with greater activa-
after adjusting for age (T¼4.03, p<0.001, k¼102).
On an exploratory basis, we examined whether activations in
BD subjects for the NoGo?Go contrast were related to prolonged
(>6 months) exposure to psychotropic medication. Lithium-
exposed BD subjects (n¼8) had significantly greater activation in
the left anterior cerebellum (T¼4.96, p<0.001, cluster size,
k¼90) than those not exposed to lithium, whereas those subjects
not exposed to lithium showed relatively greater activation in the
left ACC (BA 32, T¼4.62, p<0.001, k¼90). BD subjects
exposed to atypical antipsychotics (n¼6) had significantly greater
activation in the right ACC (BA 32, T¼5.07, p<0.001,
k¼51) and right precuneus (BA 31, T¼4.71, p<0.001,
k¼242) than BD subjects unexposed to antipsychotics. Atypical
antipsychotic exposure was also associated with relatively reduced
k¼44). There were no statistically significant differences in brain
activation patterns in BD subjects exposed versus unexposed to
valproic acid (n¼13), psychostimulants (n¼14), or antidepres-
sants (n¼16) in the NoGo?Go contrast. None of the regions noted
above overlapped with the spatial location of increased DLPFC
activation in BD subjects relative to the HC group.
Our results show that, relative to HC subjects, children and ad-
olescents with BD demonstrate increased DLPFC activation in the
presence of comparable performance during the Go=NoGo task. At
the behavioral level, BD subjects had more inaccurate Go trials
(lower Go% correct), which may be due to impairments in sus-
may indicate difficulty discriminating and appropriately respond-
ing to targets and nontargets (Wickens 2002). Analysis of reaction
times or errors in omission or commission did not indicate signif-
icant performance differences between the groups. This suggests
that subjects from both groups were able to perform the inhibitory
control task adequately at the presented level of difficulty.
Table 2. Behavioral Task Performance for the Go=NoGo
Task by Children with Bipolar Disorder and Healthy
Go % correcta
NoGo % correct
Total % correctb
Go reaction time (msec)
NoGo reaction time (msec)
Total reaction time (msec)
False alarm rate
aT¼3.35, df¼46, p¼0.002, d¼1.27, Levene’s test: F(1,46)¼5.25,
bT¼4.12, df¼46, p¼0.0002, d¼1.31, Levene’s test: F(1,46)¼6.33,
cT¼2.07, df¼46, p¼0.045, d¼0.60.
Abbreviations: SD¼Standard deviation; BD¼bipolar disorder; HC¼
Table 3. Significant Brain Activations for the NoGo minus Go Contrast in Children with Bipolar
Disorder and Healthy Controls
cluster p value<0.001BA
of voxels T statistic
Z score, maximum
location (x, y, z)
Occipital lobe, lingual gyrus
44, 16, ?8
?14, ?102, ?10
8, 18, 42
52, 6, 30
10, 10, 46
34, 24, 34
Abbreviations: BA, Brodmann area; BD, bipolar disorder; IFG, Inferior frontal gyrus; R, right; ACC, anterior cingulate cortex; HC, healthy controls;
DLPFC, dorsolateral prefrontal cortex.
RESPONSE INHIBITION IN PEDIATRIC BIPOLAR DISORDER19
Taken together, these results are consistent with the view that
during NoGo blocks may represent a mechanism for improving
behavioral performance during response inhibition. Furthermore,
our results support previous behavioral studies, suggesting that
problems in sustained attention may represent a trait deficit of
Despite the discrepancy in Go trial behavioral performance,
there were no significant between-group activation differences for
the Go versus Rest contrast. This finding may indicate that, unlike
the increased DLPFC activation observed for NoGo blocks,
BD subjects were not able to neurally compensate for intrinsic
deficits in sustained attention. Selective increase in DLPFC acti-
the subjects’ deliberate attempt to comply with the experimental
focus on inhibiting inappropriate responses, as opposed to regu-
lating more automatized behavior such as that required for Go
Our results are partially consistent with previous fMRI investi-
gations that have reported abnormalities in prefrontal circuitry in
pediatric BD (Blumberg et al. 2003b; Chang et al. 2004; Leibenluft
et al. 2007). While performing a color-naming Stroop task, 10
adolescents with BD, relative to controls, demonstrated increased
activation in subcortical regions, including the putamen and thal-
amus, relative to prefrontal areas, suggesting a developmental
disturbance in prefrontal functioning (Blumberg et al. 2003b). In a
compared with controls. R¼Right; ACC¼anterior cingulated cortex; L¼left; Inf¼inferior; DLPFC¼dorsolateral prefrontal cortex.
Areas of greater activation during the Go=NoGo task in the NoGo?Go (NoGo?Go) contrast in subjects with bipolar disorder
20SINGH ET AL.
study of twelve 9- to 18-year-old males with BD, BD subjects
showed greater left DLPFC activation compared to controls during
a visuospatial working memory task, and greater bilateral DLPFC
activation while viewing negative relative to neutral-valenced
pictures (Chang et al. 2004). Some (n¼10) among this cohort also
performed the Go=NoGo task, and their results are presented in our
study. Taken together, these studies suggest prefrontal dysfunction
in pediatric BD across a variety of tasks, but are in contrast to the
recent finding of increased frontostriatal activation in healthy
controls relative to BD subjects during a stop signal task (Lei-
benluft et al. 2007).
In contrast to prior studies, our findings suggest an atypical
pattern of dorsal prefrontal activation in BD while achieving be-
havioral performance comparable to healthy controls. Alter-
natively, increased DLPFC activation in the BD group may be
generally associated with greater neural effort needed to perform
the cognitive task (MacDonald et al. 2000; Compton et al. 2003)
compared to the HC group. Differences in the tasks, behavioral
conditions, statistical contrasts employed, sample sizes, demo-
graphics, and clinical status across studies may all contribute to the
variable results. For example, the lack of findings in the striatum in
our current study may be attributable to the use of a simple design
that may not have featured complex cognitive processes mediated
by the striatum. Nevertheless, consistent with previous findings
alluding to abnormalities in prefrontal circuitry in BD, the pre-
frontal activation profile in the presence study may be associated
with emotional and attentional dysregulation in BD youth.
Some studies in adults with BD have suggested mood state-
dependent changes in subcortical neural activation during simple
motor tasks (Caligiuri et al. 2003; Caligiuri et al. 2006; Lohr and
Caligiuri 2006). On the basis of mood symptom ratings, our BD
group, on average, had mild severity of manic symptoms (mean
YMRS score¼15.6) and symptoms commensurate with a de-
pressed state (mean CDRS score¼44.1). However, neither mania
nor depression symptom severity was correlated with any task-
related behavioral measures or brain activation within the BD
group,suggestingthatprefrontaloveractivation observed inthe BD
group during this task may be independent of a current mood state.
This lack of correlation between mood state and fMRI activation is
of euthymia (Strakowski et al. 2004), and longitudinal studies in
which frontostriatal activations remain consistent across several
mood states (Marchand et al. 2007).
Alhough we did not observe any indication that mood state af-
fected our primary results, previous studies from our group and
others suggest that increased prefrontal activation in subjects with
a hyperactive limbic system (Mayberg 1997; Chang et al. 2004;
Phillips andVieta 2007;Pavulurietal.2008).Theremaybeseveral
possible reasons why we did not observe limbic hyperactivation in
this study. First, our task was not designed to target amygdalar
activation specifically. Nevertheless, it is possible that prefrontal
structures may have successfully suppressed any task independent
limbic hyperactivation in the BD group, even in the presence of
mild to moderate hypomanic and depressive symptomatology.
Alternatively, functional differences in limbic structures may only
be present during active (Foland et al. 2008) or prolonged symp-
toms of mania. In support of the latter hypothesis, bipolar adults
who have a longer course of manic symptoms show patterns of
limbic hyperactivity (Wessa et al. 2007) and diminished prefrontal
activity (Malhi et al. 2007) while performing both cognitively and
emotionally relevant fMRI tasks.
to interpret behavioral and neural correlates of response inhibition
in BD (Henin et al. 2007). In our study, most (81%) BD subjects
met criteria for ADHD and had high overall raw and standardized
Conners’ scores. Given the preponderance of ADHD symptoms in
our sample, it is surprising that our results did not show reductions
in frontostriatal activation during tasks of cognitive control as
demonstrated inpopulations with ADHD only(Durston et al. 2003;
Rubia et al. 2005; Vaidya et al. 2005). Other studies have also
shown increased activation in the ventrolateral prefrontal cortex
during interference control and response competition in ADHD
(Schulz et al. 2005).
To address this issue directly, we would need to have had more
equal proportions of BD subgroups with and without ADHD and
have an additional comparison group comprised of children with
just ADHD of comparable severity to our BD group. Although
there were no significant correlations between ADHD symptom
severity as measured by Conners’ scores and task-related behav-
ioral measures, brainstem activation in the level of the pons was
positively correlated with higher (more severe) Conners’ scores
after adjusting for age, suggesting activation of regions other than
frontostriatal networks previously examined in similar co-morbid
populations (Adler et al. 2005; Leibenluft et al. 2007). Increased
in the BD group to permit more accurate or control level behavioral
performance on Go and NoGo epochs. Feasibility of brainstem
fMRI activation has been demonstrated (Komisaruk et al. 2002;
Campbell et al. 2007), but further investigation of this finding in
pediatric populations is warranted. Moreover, more precise mea-
sures of ADHD symptom severity than the parent-reported Con-
ners’ rating scale may be needed to confirm the relationship
between brain activation and symptom severity.
several cognitive processes and component functions of response
inhibition, including sustained attention, target detection, and rule
examine a combination of these processes over a sustained period
of time to capitalize on a higher proportion of NoGo trials re-
presented as compared to those generated by an event-related
analysis. Although event-related designs and analyses might be
able to extract individual cognitive processes subserved by acti-
vated brain regions (e.g., differentiating neural processes occurring
during failed versus successful NoGo trials), they generate a lower
proportion of NoGo trials than a block design and are extremely
difficult for children with serious mood disorders to perform.
Moreover, in the context of high individual variances due to
complex clinical heterogeneity from psychiatric disorders co-
occurring with BD such as ADHD, a block design approach
was preferred over an event-related design. This approach has
been successfully used in typically developing children (Tamm
et al. 2002) and those with posttraumatic stress symptoms (Carrion
et al. 2008), fragile X (Hoeft et al. 2007), and ADHD (Epstein et al.
2007b). Using this method, the neural result of dorsolateral pre-
frontal overactivation in BD compared with HC is of particular
to neurodegeneration and dysfunction with progression of bipolar
illness (Chang 2007).
There are a few limitations to this study, including prior and
current history of medication exposure in the BD group and a lack
RESPONSE INHIBITION IN PEDIATRIC BIPOLAR DISORDER 21
of an ADHD-only comparison group. The generalizability of our
results and our ability to detect some functional group differences
and cognitive strategies employed to optimize task performance.
Exposure of our subjects to psychotropic medications represents
another potential confound. However, due to ethical and practical
considerations, it is difficult to perform MRI studies on unmedi-
cated children with BD. Exploratory analyses suggested that there
may be general effects of medication exposure on brain activation
in BD subjects, although the group sizes for these analyses were
quite small and the length of exposure and number of medications
variable. This suggests the possibility of type I and II errors, as has
fMRI results (Leibenluft et al. 2007).
Thus, the results of the medication analyses should be inter-
preted with caution and viewed as preliminary and hypothesis
generating. For multiple reasons, including the co-occurrence of
ADHD symptoms (Epstein et al. 2007a), the BD group had high
potential for motion, which necessitated the use of a mock scanner
training protocol prior to the scan and applying a motion correction
algorithm during postprocessing procedures. Behavioral or func-
tional subgroup analyses on BD subjects based on motion severity
were not possible due to the small sample size, but task-correlated
motion was not significantly different across the BD and HC
groups. Future studies examining larger samples would permit
additional subgroup analyses relating bipolar symptoms to cogni-
tive performance on executive functioning tasks.
In summary, the results of this study indicate that children and
adolescents with BD may need to recruit supplementary prefrontal
resources to successfully perform a response-inhibition task at
healthy control levels. These findings contribute to our current
understanding of the neurofunctional phenotype in pediatric BD
and suggest future directions for elucidating a neurobiological
explanation for the co-occurrence of pediatric BD with ADHD.
Additional assessment of neuropsychological performance coin-
cident with functional neuroimaging investigations of children,
adolescents, and adults with co-occurring BD and ADHD are
necessary to further clarify the role of brain networks underlying
response inhibition in these populations.
Drs. Singh, Mazaika, Garrett, Adleman, and Reiss, Mr. Kelley
and Ms. Howe have no financial ties or conflicts of interest to
disclose. Dr. Chang has received research grants from AstraZeneca
Pharmaceuticals, Eli Lilly and Company, Otsuka America Phar-
maceutical, Inc., and GlaxoSmithKline; is on the speakers bureau
of Abbott Laboratories, AstraZeneca Pharmaceuticals, Bristol-
Myers Squibb, and Eli Lilly and Company; is a consultant for
SmithKline, Eli Lilly and Company, and Shire Pharmaceuticals;
and is on the advisory boards of Abbott Laboratories and Eli Lilly
The authors gratefully acknowledge the support of the Helena
Anna Henzl-Gabor Young Women in Science Fund, the National
Institute of Mental Health (K23 MH064460), the National Alliance
for Research on Schizophrenia and Depression (NARSAD),
the Hahn Family, and the Klingenstein Third Generation Foun-
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Address correspondence to:
Manpreet K. Singh, M.D., M.S.
Stanford University School of Medicine
Division of Child and Adolescent Psychiatry
401 Quarry Road
Stanford, CA 94305-5719
24SINGH ET AL.