Executive Function in Pediatric Bipolar Disorder
and Attention-Deficit Hyperactivity Disorder: In Search
of Distinct Phenotypic Profiles
Patricia D. Walshaw & Lauren B. Alloy & Fred W. Sabb
Received: 4 September 2009 /Accepted: 21 December 2009 /Published online: 18 February 2010
# The Author(s) 2010. This article is published with open access at Springerlink.com
Abstract Often, there is diagnostic confusion between
bipolar disorder (BD) and attention-deficit hyperactivity
disorder (ADHD) in youth due to similar behavioral pre-
sentations. Both disorders have been implicated as having
abnormal functioning in the prefrontal cortex; however,
there may be subtle differences in the manner in which the
prefrontal cortex functions in each disorder that could assist
in their differentiation. Executive function is a construct
thought to be a behavioral analogy to prefrontal cortex
functioning. We provide a qualitative review of the
literature on performance on executive function tasks for
BD and ADHD in order to determine differences in task
performance and neurocognitive profile. Our review found
primary differences in executive function in the areas of
interference control, working memory, planning, cognitive
flexibility, and fluency. These differences may begin to
establish a pediatric BD profile that provides a more
objective means of differential diagnosis between BD and
ADHD when they are not reliably distinguished by clinical
In 2001, the National Institute of Mental Health (NIMH)
Roundtable on Prepubertal Bipolar Disorder proposed the
diagnosis of BD in children (NIMH Roundtable 2001). The
diagnosis, however, still remains somewhat controversial
and often misused because of a lack of research in the
heterogeneity of the disorder in youth (e.g., Geller et al.
2000, 2002; Wozniak et al. 1995). The clinical presentation
of BD in adults often has an episodic course, with
individuals switching from distinct affective episodes of
depression, mania or hypomania, and euthymia. In children,
however, agreement on the clinical presentation of BD is
less clear, with some studies indicating a more chronic
course of symptoms with ultra-rapid shifting of mood states
from euphoria to irritability (Geller et al. 2004) or a more
irritable and violent presentation during manic states
(Wozniak et al. 1995). Perhaps unsurprisingly, more recent
studies have indicated that narrowly defining the presenta-
tion to adult DSM-IV criteria yields different results in
cognitive deficits and brain activation patterns than when
the criteria are more loosely defined (Leibenluft et al. 2007;
Rich et al. 2007). Despite the heterogeneity of the clinical
presentation in children, BD is still considered a valid
diagnosis in pediatric populations (see Youngstrom et al.
2008, for a review).
An added complication in the diagnosis of bipolar
disorder in pediatric populations is the considerable overlap
of symptoms with Attention-Deficit Hyperactivity Disorder
(ADHD). Hypomania and mania in BD share with ADHD
the symptoms of excessive talking, increased activity,
inappropriate actions and verbal responses in social
situations, lack of inhibition, and distractibility (Geller et
al. 2002; see Kent and Craddock 2003). Additionally, the
hallmark feature of chronic irritability in childhood mania
P. D. Walshaw (*):F. W. Sabb
Department of Psychiatry and Biobehavioral Science,
University of California Los Angeles,
Los Angeles, CA, USA
L. B. Alloy
Department of Psychology, Temple University,
Philadelphia, PA, USA
Neuropsychol Rev (2010) 20:103–120
can often mimic the chronic low frustration tolerance and
emotional lability of ADHD (Geller et al. 2002; Wozniak et
al. 1995). It is estimated that the comorbidity between BD
and ADHD in youth ranges from 60–93% (Axelson et al.
2006; Faraone et al. 1997; Geller et al. 2000, 2004;
Wozniak et al. 1995). Although it has been described as a
distinct diagnostic category (Geller et al. 2002, 2004;
Youngstrom et al. 2008), only a limited number of studies
have examined BD in youth without this comorbidity or
compared the two disorders directly (see Kent and
Craddock 2003; Rucklidge 2006). If pediatric BD is to be
considered a distinct diagnostic entity, further work must
examine its presentation in the absence of comorbidity with
ADHD. Given the limited understanding of BD in youth,
the differential diagnosis between BD and ADHD remains
a controversial issue.
The primary aim of this review is to directly examine the
quantitative similarities and differences in executive func-
tioning between BD and ADHD in order to determine if a
distinct neurocognitive profile exists for each. Both disor-
ders are currently diagnosed using a clinical interview and
self-report checklists completed by the individual, a parent,
or teacher. Unfortunately, the diagnostician must rely on
self-report evidence and clinical judgment to arrive at a
diagnosis, as there is no valid biological or behavioral test
for arriving at the diagnosis. It is tenuous, however, to rely
solely on self-reported characteristics to form a differential
diagnosis for these disorders given the behaviorally similar
presentation in childhood. Much of the controversy regard-
ing the diagnosis of pediatric BD lies in the Bipolar Disorder
Not Otherwise Specified (BDNOS) category. As this is a
more broad-reaching category including symptoms of BD
that do not reach the threshold for full diagnostic criteria,
there is often confusion on whether BD or a disruptive
behavior disorder, such as ADHD, should be diagnosed
when children present as chronically irritable and emotion-
ally labile (Galantar and Leibenluft 2008). While several
researchers have made attempts to define the BD phenotype
as more narrowly conforming to the adult criteria for BD
(Leibenluft and Rich 2008; Stringaris et al. 2009), there
remains no clear-cut answer for the definition of BDNOS in
The inherent problems in differential diagnosis from BD
warrant the use of more objective supporting evidence, such
as neuroimaging and cognitive testing, to assist in diagnosis
in children and adolescents, although some have questioned
this approach in ADHD (Barkley and Grodzinsky 1994).
This objective data, however, would provide supporting
evidence for differing neural networks that occur in
pediatric BD and ADHD, despite similar behavioral
presentations. Research in magnetic resonance imaging
(MRI) and diffusion tensor imaging (DTI), indicate differ-
ences in structural abnormalities in BD versus ADHD, with
volumetric abnormalities of the limbic system and smaller
volume of the ventrolateral prefrontal cortex (VLPFC) and
rostral prefrontal cortex (PFC) implicated in pediatric BD
and smaller volume of striatal structures implicated in
ADHD but not BD (Blumberg et al. 2005; Kalmar et al.
2009; Lopez-Larson et al. 2009). Disruption in white matter
appears more diffuse across the brain regions in ADHD as
compared to BD, whereas white matter abnormalities are
more restricted to cortico-limbic connections in the PFC for
BD (Pavuluri et al. 2009b). Evidence from functional
imaging studies reveal relatively greater activation in the
bilateral VLPFC and right dorsolateral PFC (DLPFC) for
pediatric BD relative to the ADHD during response
inhibition tasks (Passarotti et al. 2009). Other tasks of
executive function indicate greater activation in left
DLPFC, bilateral ACC, and left putamen and thalamus for
children with BD (Blumberg et al. 2003; Chang et al. 2004;
Nelson et al. 2007), whereas children with ADHD exhibit
lower activation in right DLPFC and ACC, and striatal
areas (Casey et al. 1997; Konrad et al. 2007; Smith et al.
2008). Although there is evidence that individuals with
ADHD and BD differ on neuroanatomical structure and
function, such neurobiological measurements (e.g., MRI,
SPECT) remain impractical and inefficient in the typical
clinical setting. Thus, developing a neurocognitive profile
for each disorder would aide in differential diagnosis and
avoid the pitfalls of misdiagnosis in youth.
Executive Function as a Model
The PFC and its related neural circuitry are critically
involved in executing many of the components underlying
executive function. Pennington’s (1997) concept of the
“frontal metaphor” applies to the term “executive function”,
in that executive function is a latent construct born from
theory and, thus, is not an exact representation of the
activity in PFC. Measurement of executive function thus
proves difficult, as it is a latent construct composed of
several components, which are not clearly defined. Factor
analyses of test batteries of executive function do not result
in a single factor, but at least five factors: 1) inhibition, 2)
working memory, 3) planning, 4) set-shifting, and 5)
fluency. (Pennington 1997; Pennington et al. 1996; Welsh
et al. 1991) A recent review of a highly similar latent
construct, cognitive control, suggests similar dimensions
based on literature mining (Sabb et al. 2008). Although
five distinct dimensions, these components of executive
function are interrelated processes that depend on inter-
actions with the others to execute control over behavior.
Thus, here we use the term ‘executive function’ to refer to
the overarching representation of PFC function, recogniz-
ing that this latent construct is multifactorial and remains
104Neuropsychol Rev (2010) 20:103–120
Executive Function, BD, and ADHD
The present review examines BD and ADHD as disorders of
the PFC, although it is clear that many areas of the brain are
implicated. Although both BD and ADHD show both
abnormal PFC functioning and deficits in executive function,
there may be distinct signatures in the patterns of deficits that
suggest two different disorders. Pennington (1997) notes
that, in general, while two separate disorders may both
involve dysfunction of the PFC and have similar behavioral
presentations, discriminant validity may arise from deficits
in different areas of executive function. For example,
individuals with schizophrenia have been shown to have
greater impairment in some aspects of problem-solving than
individuals with BD, but not in the areas of set-shifting and
attention (see Bearden et al. 2001, for review).
Here we review five facets of executive function
through neurocognitive tasks found in both the pediatric
BD and ADHD literatures (see Table 1 for a summary of
domains of executive functioning and tasks examined in
this review). To the best of our knowledge, this is the first
review comparing the neurocognitive function of individ-
uals with pediatric BD and ADHD, and while several
studies have emerged to provide support for a neuro-
cognitive profile of pediatric BD research in this new field
remains scant. We end our review with a discussion of the
executive functioning differences in BD and ADHD and
their implications for differential diagnosis of these two
The current review was conducted following an extensive
search through the research databases PsychInfo and Med-
line. Key terms were selected based on previous factor
analyses on executive function and review papers in the
areas of BD and ADHD. Terms included, ‘bipolar’,
‘mania’, ‘manic’, ‘euthymic’, ‘ADHD’, ‘attention-deficit
disorder’, and ‘hyperactivity’, and were cross-referenced
with the terms ‘cognitive’, ‘neuropsychological’, ‘execu-
tive’, ‘prefrontal’, ‘inhibition’, ‘working memory’, ‘plan-
ning’, ‘fluency’, and ‘set-shifting’. Articles were selected
based on the following criteria: use of English language,
conducted between the years of 1989 and 2009, clear
presentation of results for variables of interest, and use of
children or adolescents. Additionally, bibliographies of the
articles selected were used to supplement citations that had
not been acquired through the database literature search.
For the purposes of consistency in measurement, we only
review tasks that have been validated in the literature and
have been studied in both pediatric BD and ADHD
Sixty-eight studies in ADHD and sixteen studies in
pediatric BD were included in the review. Given the paucity
of research conducted on pediatric BD to date with most
studies having small sample sizes themselves, we chose to
present quantitative data from these studies noting their
sample sizes and effect sizes, but not conduct a formal
meta-analytic review, which may be biased by small
numbers of studies with small sample sizes. A majority of
these studies are new, suggesting a burgeoning and
important field, which will hopefully allow for more strict
meta-analyses to be conducted in the future.
All studies selected utilized diagnostic criteria from
either DSM-III-R or DSM-IV in their methodology. Due
to the nascence of research in pediatric BD, all but one
of the BD studies used DSM-IV criteria. In the ADHD
literature, 24 studies used DSM-III-R criteria and 44
studies used DSM-IV criteria. Studies on BD were
included if subjects met criteria for bipolar I disorder,
bipolar II disorder, and bipolar disorder not otherwise
specified (BDNOS). Not all studies examined all exec-
utive function variables in this included review; 23
studies were single measure studies and 59 used more
than one task or a battery. One study included examined
cognitive performance in at-risk adolescents who later
developed bipolar disorder (Meyer et al. 2004). Eleven of
the 16 BD studies included statistics on comorbid ADHD,
the average rate of which was 54%. Effects of comorbidity
are noted where appropriate in the review. As in most
studies of BD, pediatric samples were taking one or more
medications at the time of testing. Where examined,
effects of medication were found not to produce differ-
ences in performance in four of those five studies
(Del Bello et al. 2004; Leibenluft et al. 2007; Pavuluri et
al. 2006). The remaining study found that psychotropic
medication was associated with a decrease in verbal
fluency score (Bearden et al. 2007).
Although approximately a third of studies (21 total)
reviewed from the ADHD literature distinguished subtypes
of ADHD or included analyses on comorbid learning
disabilities (LD; 21 total), the majority did not and these
factors were combined in the overall findings. Subtype and
comorbid LD findings are noted in this review where
appropriate, but because the ADHD literature does not
always distinguish them, this is noted as a limitation to the
conclusions of the present review. For all ADHD studies
reviewed, children and adolescents were either off of
medication for >24 hours or medication naïve. For both
BD and ADHD literature, studies included were sampled
from a variety of populations, but included mostly
outpatient or community samples (97%).
To provide a more comprehensive review in compar-
ing these two groups, we have calculated average effect
size (ES), weighted by sample size, for each of the tasks
Neuropsychol Rev (2010) 20:103–120 105
for each group (ADHD and BD) using Cohen’s d
In order to reduce bias from a particular sample, only a
single contribution from each independent sample was
used; thus, if a study examined two tasks from the same
domain of executive functioning, only the larger of the two
effect sizes was used in the average weighted effect size
calculation presented in Table 2. Descriptors for effect size
are provided for relative comparison and are as defined by
Cohen (1988): small = 0.2, medium = 0.5, large > 0.8. An
absolute difference score was calculated between the average
weighted effect sizes of the two groups. This was used to
create a visual presentation of these findings in Fig. 1, which
illustrates the areas of executive function showing the largest
difference on the left to the smallest difference on the right.
Weighted effect sizes for each study are provided in Table 3
for ADHD and Table 4 for BD. As there are only two studies
to date that has directly compared executive function in pure
pediatric BD and pure ADHD (Passarotti et al. 2009;
Rucklidge 2006), all effect sizes presented are each
population as compared to control groups. It should be
noted that effect sizes for non-significant findings were
included and all findings were indicative of either worse
performance or no difference from control group.
Inhibition is a component of executive function that can be
broken into several subsystems (see Barkley 1997; Nigg
2000; Tannock 1998, for reviews; Quay 1988, 1997;
Schachar and Logan 1990). Barkley (1997) proposes a
comprehensive theory of inhibition that consists of three
interrelated processes based on both timing and situation in
which stimuli are presented including inhibition in regard to
an initial response to a stimulus or an ongoing response
(Response Inhibition), and inhibition of interfering stimuli
Response inhibition is the process of physically inhibiting a
response to a stimulus. Several behavioral tasks have been
developed to measure response inhibition; two of which have
been examined in the pediatric BD and ADHD literatures:
go/no-go style variants of the Continuous Performance Test
Table 1 Tasks of executive function across pediatric BD and ADHD literature
Executive function domainTasks DescriptionKey scores
Response inhibition Continuous Performance
Stop-Signal Task (SST)
Inhibit response when target stimulus shown;
rapid response when other stimuli are shown
Inhibit prepotent response when tone is heard
Rapidly naming colors (e.g., “green”) of ink
in which color words (e.g., “red”) are printed
Errors of commission on CPT
(CPT-EC) or Stop-signal
reaction time (SSRT)
Interference scoreInterference control
Verbal working memory Digit-Span Total (DS-T)
Digit-Span Backward (DS-B)
Repeat a series of numbers in forward or
reverse order from which they are presented;
Total score includes both forward and
Maintain spatial memory of already
Mentally rearrange spatial information and
output a behavioral response
Move 3+ rings/balls to match a particular
arrangement, while adhering to specific
rules of how they can be moved
Sort cards according to shifting rules
# of series of digits correct
Spatial working memoryCANTAB SWM Task Between search errors
Spatial Span (SSp) # of series of blocks/squares
Total score (ToL-T)Planning Tower of London (ToL)
Set-shifting Wisconsin Card Sort TaskPerseverative errors
Phonemic fluencyF-A-S Test Rapidly name words that begin with
‘F’ (or ‘A’ or ‘S’)
Rapidly name words that belong to a category
# of words
Semantic fluencyCategories # of words
106 Neuropsychol Rev (2010) 20:103–120
(CPT; Conners 1985, 1992; Gordon 1983; Rosvold et al.
1956), and the Stop-Signal Task (SST; Logan et al. 1984).
These tasks may putatively engage two separate processes
activated either by inhibition of an initial response or
deactivation of an ongoing response to a stimulus. The
primary response inhibition variables (or indicators—as we
define the independent variables of interest) for these tasks
are errors of commission (EC) and stop-signal reaction time
CPTs are widely used measures of response inhibition in
the ADHD literature. Of the 68 child ADHD studies re-
viewed here, 21 examined EC on the CPT. Overall, ADHD
samples showed ES=.56 on CPT-EC as compared to
controls, indicating a moderate effect for ADHD to exhibit
a more impulsive response style on the CPT (see Table 2).
In comparison, thirteen studies found no deficits in
inhibition in children with ADHD, with effect sizes ranging
from .07 to 1.27 for EC. Only two studies examined the
effects of ADHD subtype on CPT-EC. Tsal et al. (2005)
found that inattentive-type was associated with more EC
than combined-type, while Willcutt et al. (2005) found no
differences between subtypes in EC.
Table 2 Average weighted effect size by task
Executive function domainVariable BD weighted ES ADHD weighted ES
Response inhibition CPT Errors of Commission (CPT-EC)
Stop-Signal Reaction Time (SSRT)
Stroop interference (Stroop)
.38 Interference control
Verbal working memory Digit-Span Total (DS-T)
Digit-Span Backward (DS-B)
CANTAB SWM – Between Search Errors (SWM-BSE)
Spatial Span (SSp)
Tower of London – Total (ToL)
WSCT – Perseverative Errors (WCST-PE)
Spatial working memory
CPT Continuous Performance Test, CANTAB Cambridge Neuropsychological Test Automated Battery
aThese ES’s are the result of only one study and are thus not weighted averages
Fig. 1 Executive function
domains for bipolar disorder
(BD) and attention-deficit
hyperactivity disorder (ADHD)
organized from largest to small-
est absolute differences in
average weighted effect sizes
Neuropsychol Rev (2010) 20:103–120 107
Table 3 ADHD study effect sizes (d)c
Referencen CPT-ECSSRT Stroop DS-TDS-B SWM-
SSpToL WCST FASCategories
Alloway et al. (2009)ADHD=46
Assesmany et al. (2001)---
Barkley et al. (2001).07a
Barkley et al. (1992)1.29b
Barnett et al. (2001)-----
Bedard et al. (2003)-
Berlin et al. (2004)--
Borger et al. (1999).65b
Brewer et al. (2001).38b
Cairney et al. (2001)-----
Corbett et al. (2009)--.31 --.21
Dimoska et al. (2003)-
Epstein et al. (2003)
Geurts et al. (2004)-
Goldberg et al. (2005) --.12--
Grodzinsky and Diamond (1992)
Happe et al. (2006)-----
--- .63 .07
Henin et al. (2007)-- .2.2---- .27--
Horn et al. (1989)
Houghton et al. (1999)-- .17----.15 .31--
Jennings et al. (1997)-
Kempton et al. (1999)-----
Kerns et al. (2001).23a
Klorman et al. (1999)--------.07--
Konrad et al. (2000)-
Lawrence et al. (2004)-- .12-----
Loge et al. (1990)
Lufi et al. (1990) --
108 Neuropsychol Rev (2010) 20:103–120
Table 3 (continued)
Referencen CPT-ECSSRT Stroop DS-T DS-BSWM-
Manassis et al. (2000)ADHD=30
Mariani and Barkley (1997).46b
Marzoochi et al. (2008)- .19-----
Mataró et al. (1997).39b
- .21----- .35
McInerney and Kerns (2003)-
McInnes et al. (2003)----
Nigg et al. (2002)-
Overtoom et al. (2002)-
Passarotti et al. (2009)-.43---------
Pennington et al. (1993)
Pineda et al. (1999)--------
Pliszka et al. (1997)-
Pliszka et al. (2000)-.75---------
Purvis and Tannock (2000)
Rubia et al. (2001)- .5---------
Rucklidge and Tannock (2002)-
Rucklidge (2006) .32a
Sartory et al. (2002)
Schachar et al. (2000)-
Schachar and Tannock (1995)-
Schachar et al. (1995)-
Scheres et al. (2001)- .39---------
Schmitz et al. (2002)--------.14--
Seidman et al. (1997a)--.15
Seidman et al. (1997b)--
Shue and Douglas (1992) --------
Solanto et al. (2001)-
Neuropsychol Rev (2010) 20:103–120109
Similarly, four studies in the pediatric BD literature have
explored EC on the CPT with an overall ES=.40, which is
somewhat less than in the ADHD literature, but also indicates
a moderate effect for response inhibition difficulties. One of
these studies found significant differences from control
groups on CPT-EC (d=.69; Pavuluri et al. 2006), while the
other three did not (DelBello et al. 2004; Robertson et al.
2003; Rucklidge 2006). Two of these studies examined
medication effects on EC and found no associated changes
in performance (DelBello et al. 2004; Pavuluri et al. 2006).
One issue notedwhenreviewingthe literatureinbothgroups
for the CPT, however, is that there is a difference in effect size
for deficits on EC depending on whether the CPT involves
inhibiting a prepotent response (i.e., inhibiting to a target
stimulus; e.g., Conners 1985, 1992) or responding to a target
(i.e., inhibiting to non-target stimuli; e.g., Gordon 1983;
Rosvold et al. 1956), the latter of which some might classify
as more a task of vigilance and sustained attention. In the
ADHD literature, the average weighted effect size is much
larger (ES=.39 versus .67) for inhibiting to target versus non-
target. The same holds true for the BD literature (ES=.23
versus .60). Thus, differences observed in these two diagnostic
groups depend on CPT version (see Tables 3 and 4 for
clarification on which CPT version was used in each study).
Unfortunately, these versions are often combined in reviews.
The SST is also consistently associated with deficits in
response inhibition in ADHD across the lifespan (Nigg
1999; Nigg et al. 2002; Rucklidge and Tannock 2002;
Schachar et al. 2000). The average weighted effect size for
studies reviewed was moderate to large (ES=.63). Nineteen
out of 25 studies reviewed (76%) found deficits in SSRT
for children and adolescents with ADHD as compared to
control groups. Those studies that did examine subtypes
separately did not find effects of subtype on SSRT
performance (Bedard et al. 2003; Geurts et al. 2004;
Willcutt et al. 2005).
In the pediatric BD literature, three studies have
examined deficits on SSRT and indicate a small effect
(ES=.31). None of these studies found their BD groups to
be significantly different than control groups (Leibenluft et
al. 2007; McClure et al. 2005; Passarotti et al. 2009). The
Passarotti study (2009), however, also directly compared
Table 3 (continued)
Referencen CPT-EC SSRT StroopDS-T DS-BSWM-
Stevens et al. (2002) ADHD=76
Toplak et al. (2003)----
Toplak et al. (2009)-
Tripp and Alsop (1999).48b
Tripp et al. (2002).15b
Tsal et al. (2005).7b
et al. (1998)
Wiers et al. (1998)
Willcutt et al. (2005)
Wu et al. (2002)---- .55-- .13---
Mean weighted effect size .56.63 .35.67 .63 .77.94.38 .36 .68.38
ADHD Attention Deficit Hyperactivity Disorder, C Control group
CPT Continuous Performance Test, SSRT Stop Signal Reaction Time, DS-T Digit Span Total score, DS-B Digit Span Backwards, SWM-BSE
Between-Search Errors on the CANTAB spatial working memory task, SSp Spatial Span, ToL Tower of London total score, WCST Wisconsin
Card Sorting Task - perseverative errors, FAS F-A-S fluency task
aCPT - Inhibit to target
bCPT – Inhibit to non-target
cAll effect sizes presented as Cohen’s d (Cohen 1988), with positive effect sizes indicating ADHD performed worse on the task. Unbolded effect
sizes = ADHD group was not significantly different from controls. Bolded effect sizes = ADHD group performed significantly worse than control
110 Neuropsychol Rev (2010) 20:103–120
the BD group to an ADHD group and found the ADHD
group to have a faster SSRT, but this difference was not
Thus, while some research focuses on the variable of
errors of commission on the CPT as a neuropsychological
representation of deficits in response inhibition in each of
these disorders, performance on the SST is more consis-
tently different from normal on the SST for ADHD. The
two studies that directly compared pediatric BD to ADHD,
however, found no significant differences between groups
for CPT-EC (Rucklidge 2006) or SST (Passarotti et al.
2009). In sum, the evidence indicates the deficit in response
inhibition to be present to some degree in both the ADHD
and pediatric BD neurocognitive profiles.
The Stroop task (Stroop 1935) is a widely used measure of
interference control that has been studied in both pediatric
BD and ADHD samples, with the primary indicator being
the interference score. Overall, Stroop interference in
individuals with ADHD produces an overall small weighted
effect size of .35. Ten out of 15 studies found no significant
difference in Stroop interference performance for ADHD
Table 4 BD study effect sizes (d)c
Referencen CPT-EC SSRTStroop DS-TDS-B SWM-BSE SSpToLWCST FASCategories
Bearden et al. (2007) BD=31
Blumberg et al. (2003)-- .7--------
Castillo et al. (2000)-------.89---
DelBello et al. (2004).48b
Dickstein et al. (2004)-----.35-----
Doyle et al. (2005) --
Leibenluft et al. (2007)- .28---------
McClure et al. (2005)-.49---------
Meyer et al. (2004)--------
Olvera et al. (2005) -------
Passarotti et al. (2009)- .11---------
Pavuluri et al. (2006)
Pavuluri et al. (2009a)---
Robertson et al. (2003) .2a
Rucklidge (2006) .35a
Voelbel et al. (2006)--.69----- .58 .34.16
Mean weighted effect size.40 .31.60.67 .38.35.80 .96 .73.34.38
BD Bipolar Disorder, C Control group
CPT Continuous Performance Test, SSRT Stop Signal Reaction Time, DS-T Digit Span Total score, DS-B Digit Span Backwards, SWM-BSE
Between-Search Errors on the CANTAB spatial working memory task, SSp Spatial Span, ToL Tower of London total score, WCST Wisconsin
Card Sorting Task - perseverative errors, FAS F-A-S fluency task
aCPT - Inhibit to target
bCPT – Inhibit to non-target
cAll effect sizes presented as Cohen’s d (Cohen 1988), with positive effect sizes indicating BD performed worse on the task. Unbolded effect
sizes = BD group was not significantly different from controls. Bolded effect sizes = BD group performed significantly worse than control.
Neuropsychol Rev (2010) 20:103–120 111
groups, with effect sizes ranging from .07 to .45. The five
studies that did find a significant difference in Stroop
interference revealed medium to large effect sizes (ES=.31
to 1.49; Barkley et al. 1992; Berlin et al. 2004; Grodzinsky
and Diamond 1992; Lufi et al. 1990; Seidman et al. 1997b).
Three studies of pediatric BD literature have examined
performance on the Stroop task, with a weighted effect size
of .60. One study found children with BD trended towards
difference on interference (p=.07, ES=.57; t-scores = 49.0
for BD and 52.9 for NC; Doyle et al. 2005). The
remaining two studies in adolescents with BD, however,
did not find significant differences between BD and
control groups on interference, although effect sizes were
.7 and .69 (Blumberg et al. 2003; Voelbel et al. 2006).
Based on the data available to date, there is stronger
evidence for interference control deficits on the Stroop task
for individuals with BD than for those with ADHD. This
may seem surprising given anecdotal evidence that indi-
viduals with ADHD are less able to inhibit distraction from
external stimuli; however, these studies suggest that
individuals with BD may have more difficulty ignoring
unimportant stimuli during a task.
Overall, it appears that it is important to examine the
subcomponents of inhibition when comparing BD and
ADHD. These disorders show a similar pattern of deficits
in response inhibition, which are either minor for CPTs
requiring inhibition of a prepotent response or extensive for
the SST. Difficulties with interference control, however,
appear to be specific to BD.
Verbal Working Memory
Verbal working memory (VWM) is a component of executive
VWM is the Digit Span (DS) subtest of the Wechsler
intelligence scales (WAIS, WISC; Wechsler 1991, 1994). It
has two presentations, DS-Forward and DS-Backward, the
latter of which is a robust indicator of executive function,
requiring the manipulation of information in memory.
There is support for impairment on the DS-Backward
for individuals with ADHD, with an average weighted
effect size of .63. Five of 7 studies reporting performance
on this subtest indicate that children with ADHD perform
significantly worse than controls, with effect sizes
ranging from .59 to 1.73. Only two studies did not find
deficits in performance on the DS-Backward task for
children with ADHD (Barkley et al. 2001; Wu et al.
2002). Literature for DS-Backward is limited, however, in
the pediatric BD area. Only one study has been conducted
using this subtest, with results reflecting a small effect size
of .38 with nonsignificant differences from the control
sample (Bearden et al. 2007).
Spatial Working Memory
Spatial working memory (SWM) also involves the mental
organization and manipulation of material but with nonver-
bal information. Several tasks are good representations of
SWM, such as the Wechsler Spatial Span tasks and the
SWM task from the Cambridge Neuropsychological Test
Automated Battery (CANTAB; Luciana and Nelson 2002).
As is the problem with DS, results of the Spatial Span task
often combine forward and backward presentations, thus
making it difficult to tease apart components of working
memory (see Table 2 and Fig. 1).
Indications of deficits on the CANTAB SWM task for
children with ADHD, however, are consistent with those on
VWM tasks (average weighted ES=.77). Five out of 7 studies
found significant deficits in SWM on the CANTAB for
children with ADHD. Two studies did not find impairment in
ADHD on this task, with effect sizes ranging from .2 to .55
(Corbett et al. 2009; Willcutt et al. 2005). Again in pediatric
BD only one study has examined SWM (CANTAB), and
consistent with the VWM literature in this group, shows no
deficits for pediatric BD (ES=.35; Dickstein et al. 2004).
Thus, overall, it appears that working memory impair-
ments in both verbal and spatial domains may be emerging as
a marker that differentiates ADHD from BD. Further research
must be done to examine working memory specifically as its
own domain and in further studies in pediatric BD.
As mentioned above, Wechsler digit and spatial span
subtests are often presented as a composite score for the
entire DS subtest. This is often the result of earlier versions
of the WISC not separating the two, which can obscure
important information regarding different components of
executive control. As indicated in Table 2, the composite
DS score (DS-Total) confounds the difference in working
memory function between the two disorders, seen in DS-
Backwards. Several of the studies reviewed used the
composite score, including 4 in the ADHD literature and
4 in the pediatric BD literature. Despite the confound result
reporting, there is emerging evidence for deficits in
working memory to be specific to ADHD.
Planning involves the ability to manipulate information into
a reliable sequence that will achieve an end goal. It requires
an individual not only to think in terms of the next step, but
also to think of the future consequences of such a step. The
task typically used to examine planning abilities across the
pediatric BD and ADHD literature is the Tower of London
(ToL; Shallice 1982).
112Neuropsychol Rev (2010) 20:103–120
Results for the ToL indicate a small weighted effect size of
.38 for deficits in ADHD. Four out of seven studies found no
significant different in ToL total score from control groups
(ESrangingfrom.13to.36).Niggetal.(2002) found children
with ADHD-Combined type to have a lower total score on
the ToL than controls. Similar findings have been reported in
2 other studies, although not classified by subtype (Kempton
et al. 1999; Marzoochi et al. 2008).
Findings in the pediatric BD literature, although limited
in number, more strongly indicate a planning deficit with a
large weighted effect size of .96. Olvera et al. (2005) found
youth with BD to perform significantly below the control
group (ES=.89). With a younger sample, Castillo et al.
(2000) found children with BD to perform below average
on the NEPSY Tower subtest (mean scaled score = 7.17).
While still preliminary based on the small number of
studies in this domain, there is evidence for deficits in
planning in pediatric BD as measured by the ToL.
Furthermore, this dysfunction may be specific to the
pediatric BD phenotype, but more research to directly
examine this hypothesis needs to be executed.
Set-shifting is a process of working memory that involves
attention to a current stimulus and the ability to maintain
that attention while shifting between stimuli. The ability to
adapt and change a response to new incoming stimuli in the
environment has long been considered a hallmark of
executive function. A measure of this dimension of
executive function that spans the pediatric BD and ADHD
literature is the perseverative errors score on the Wisconsin
Card Sorting Test (WCST; Heaton 1981).
The findings for performance on the WCST for ADHD
primarily indicate that children with ADHD do not show a
deficit in set-shifting, with a small average weighted effect size
of .36. Thirteen of 18 studies found no differences in
perseverative errors and categories achieved between children
with ADHD and controls (ES=.07 to .6). Five studies found
children with ADHD made significantly more perseverative
errors than controls, however, two studies reported a greater
number ofperseverative errors intheir ADHDgroup,butnoted
forIQ,indicatingthatIQmayplaya roleinperformance onthe
WCST (Tripp et al. 2002; Willcutt et al. 2005).
There is greater evidence for impairment on the WCST
in pediatric BD, with a large average weighted effect size of
.73. Two out of 4 studies showed significant differences on
the WCST from control groups (ES=.6 and .89), while 2
did not (ES=.58 and .7). Meyer et al. (2004) reported that
young adults diagnosed with BD showed a trend toward
more perseverative errors when the WCST was adminis-
tered during their adolescence. Results of this study are
important because early attentional problems in conjunction
with disturbances in executive function on the WCST
predicted BD onset, but not unipolar depression or no mood
disorder in young adulthood. Thus, like deficits in planning,
deficits in set-shifting appear to be specific to the pediatric
Fluency is a measure not only of vocabulary breadth and
semantic memory, but also processing speed, working
memory, inhibition, and set maintenance. Verbal fluency
is often measured in two conditions: letters (phonemic) and
categories (semantic). Perhaps the most widely used test of
phonemic verbal fluency is the Controlled Oral Word
Association Test (COWAT; Benton and Hamsher 1978),
where individuals are required to generate words beginning
with a particular letter (‘F’, ‘A’, or ‘S’). For semantic
fluency, individuals are required to generate particular items
in a category within a given time.
Individuals with ADHD appear to have greater deficits
with regard to phonemic fluency (weighted ES=.68) than
semantic fluency (weighted ES=.38). Deficits in phonemic
fluency discriminate children with ADHD from controls
better than semantic categories or designs (Barkley et al.
1992; Marzoochi et al. 2008; Mataró et al. 1997; Pineda et
al. 1999). One study has reported deficits in both phonemic
and semantic categories for children with ADHD (Geurts et
al. 2004), whereas 3 report no difference from control
groups on either domain of verbal fluency.
Importantly, the common comorbidity of ADHD and
reading disability (RD) has been shown to have additive
effects for deficits in verbal fluency (Felton et al. 1987). Of
the studies reviewed here, 3 excluded or accounted for RD
in their analyses (Barkley et al. 1992; Loge et al. 1990;
Marzoochi et al. 2008). The average weighted effect size
for these studies continued to be large at 1.03, providing
evidence that deficits in phonemic fluency in children with
ADHD are not limited to the comorbidity with RD.
Review of the pediatric BD literature indicates a small
effect for dysfunction in either phonemic (weighted
ES=.34) or semantic fluency (weighted ES=.38). Of the
two studies that examined fluency thus far, one did not find
deficits in either domain of verbal fluency for children with
BD versus controls (Voelbel et al. 2006). The other study
found significant differences in both domains, but further
analysis indicated that medication accounted for the deficits
in fluency (Bearden et al. 2007).
Thus, deficits in phonemic verbal fluency appear to be
specific to ADHD and may be present over and above
comorbidity with RD. Semantic fluency, however, does not
appear to be associated with either ADHD or pediatric BD
in any strong regard.
Neuropsychol Rev (2010) 20:103–120113
Although there appear to be some similarities between BD
and ADHD in their neuropsychological function, subtle
differences in various areas of executive function emerge as
specific to each disorder. Overall, evidence exists for differ-
ences between neurocognitive profiles of pediatric BD and
ADHD in several areas of executive function. The primary
differences implicate impairments in interference control,
planning, and set-shifting that are specific to BD, and
impairments in verbal and spatial working memory and
inhibition does not appear to be distinctive in discriminating
BD from ADHD at this time. Thus, evidence for distinctive
profiles of executive function in these disorders exists.
There is evidence for a specific pattern of deficits in
pediatric BD. While perhaps unexpected, similar to our
findings, a meta-analysis conducted by van Mourik et al.
(2005) concluded similarly that the Stroop task does not
differentiate individuals with ADHD from controls well,
despite differences in the calculation of interference scores.
Similarly with planning and set-shifting abilities, our results
provide evidence for deficits in this area particular to BD
and markers that may be predictive of BD as opposed to
other mood disorders (Meyer et al. 2004). Thus, an
emerging profile of pediatric BD includes problems related
to inhibiting distraction from irrelevant stimuli and having
flexibility in thinking strategies.
Conversely, there is evidence for a specific profile for
ADHD. Evidence indicates support for a deficit in both verbal
Results from this review are consistent with a recent meta-
analysis on correlates of executive function in ADHD (Willcutt
et al. 2005), which supports an emerging theory of working
memory deficit as a defining feature of ADHD. There is also a
subtle difference between the two disorders within the domain
of verbal fluency, with children with ADHD exhibiting
deficits in phonemic fluency. This was found to be above
and beyond contributions of comorbid reading disorders
indicating that this may be a deficit inherent to ADHD and
not simply a reflection of the comorbidity. This deficit in
phonemic fluency is thus likely reflective of the inherent
executive function profile emerging as specific to ADHD.
For the most part, the current review confirms findings
from the adult literature in both BD and ADHD. Studies
comparing BD adults to healthy control adults indicate that
adults with BD have poorer interference scores on the
Stroop (e.g., Balanzá-Martínez et al. 2005; Thompson et al.
2005), have poorer planning skills (e.g., Clark et al. 2001;
Thompson et al. 2005), and make more perseverative errors
on the WCST (e.g., Altshuler et al. 2004; Balanzá-Martínez
et al. 2005). Studies in the adult BD literature also show
deficits in verbal working memory and category fluency (e.
g., Martínez-Arán et al. 2004; Thompson et al. 2005),
indicating that performance in these facets of executive
function may worsen during the course of the illness.
Findings from the adult ADHD literature indicate that,
similar to children, adults with ADHD show difficulty with
working memory and phonemic fluency (Jenkins et al.
1998; Murphy et al. 2001; Seidman et al. 1998). With
regard to response inhibition, one study is published
indicating deficits in SSRT with in an adult BD sample as
compared to a healthy control sample (ES=.52; Strakowski
et al. 2009). Findings for the CPT are in line with the
pediatric BD literature indicating more impulsive response
style (Altshuler et al. 2005; Tham et al. 1997; Wilder-Willis
et al. 2001). Thus, more research is needed with the SST in
BD samples before final conclusions are drawn.
The Search for Potential Biomarkers
With the advancement in neuroimaging techniques, evi-
dence now exists to support the hypothesis that the tasks
reviewed here elicit activity in the PFC. Interestingly, in
areas of executive function for which differences between
the two disorders exist, neurophysiological evidence sup-
ports the hypothesis that although the PFC is implicated in
both BD and ADHD, it functions differently in each
disorder. On tasks of interference control and set-shifting,
which are impaired in BD but not ADHD, neuroimaging
studies have revealed increases in activation of the DLPFC
for children with BD (Nelson et al. 2007), which is
confirmed in adult studies of BD (Frey et al. 2005; Gruber
et al. 2004; Michael et al. 2003). During working memory
tasks, which are impaired in ADHD but not BD, the
DLPFC and ventral PFC show blunted activation (Kobel et
al. 2008). Interestingly, however, during a SWM task,
Chang et al. (2004) found that children with BD showed
greater activation of the left DLPFC, despite no significant
difference in behavioral response. This follows the pattern
of over-activation of the DLPFC and other areas of the PFC
in BD and underactivation in ADHD during tasks of
executive function. As noted earlier in this review, this
pattern is found during response inhibition tasks (Passarotti
et al. 2009). Thus, despite similar performance deficits on
tasks of response inhibition, there are differing abnormal-
ities in underlying neural networks. Thus, differences
between BD and ADHD appear both behaviorally and
physiologically during tasks of executive function, indicat-
ing that they are indeed separate disorders and can be
measured objectively as such.
The differences in executive functioning in BD and ADHD
may help to provide discriminant validity between these
114Neuropsychol Rev (2010) 20:103–120
two disorders when they appear behaviorally similar in
childhood by creating distinct neurocognitive profiles.
Despite the encouraging results of this review, more
research is needed in neurocognitive function in pediatric
BD to confirm the findings. While the understanding of
nosology is important, implications for correct differential
diagnosis are imperative for clinical reasons. Treatments for
these disorders differ radically, with ADHD utilizing
stimulant medication (Greenhill et al. 2002) and behavioral
parent training (Barkley 2002), and BD utilizing mood-
stabilizing medications (McClellan et al. 2007). Improper
diagnosis can result in ADHD children being given
medications, such as lithium, which are ineffective at
treating symptoms of ADHD and have the potential for
potent side effects (Giedd 2000). Additionally, a diagnosis
of BD at a young age can have stigmatizing results, as it is
a lifetime diagnosis with grave implications for functioning
across the lifespan, such as hospitalizations, inability to
retain employment, increased risk of substance abuse and
suicide, and use of multiple medications throughout the
lifespan (Birmaher and Axelson 2006; Chen and Dilsaver
1996; Goodwin and Jamison 1990). With additional
research in pediatric BD, a future goal would be to bring
these findings into the clinical realm to improve quality of
One limitation of the bipolar literature on executive
function is that the majority of studies do not follow
individuals through the course of their illness. The adult BD
literature indicates the cognitive abilities of individuals with
BD can fluctuate with the presence or absence of an
affective episode. For instance, impairments in sustained
attention and impulsivity can be amplified during manic
episodes (e.g., Sax et al. 1995), whereas Wilder-Willis et al.
(2001) found that fine motor skills and reaction time
remained impaired in a euthymic mood state. A longitudi-
nal study found that individuals had impairment in serial
learning on a verbal task while manic, but not when
euthymic (Henry et al. 1973). In this same study, however,
individuals showed no differences in impairment on short-
term free recall in various affective states. No recent
studies, however, have been completed using a within-
subject design across mood states.
Rather than being viewed as a complication in assessing
neurocognitive abilities in BD, these variations in cognitive
abilities across mood states may prove to be a marker for
differentiation between BD and ADHD. Cognition in
ADHD appears to be relatively stable across the lifespan,
with the exception of verbal working memory, which may
improve later in life (Biederman et al. 1993). Given the
number of studies conducted with youth of different ages, it
appears that over a short period of time, the neurocognitive
profile of ADHD is relatively stable. Thus, a potential
method of differentiating between BD and ADHD may be
to re-test individuals over a period of time, during which
various mood states have the potential to occur and alter the
With the high rate of comorbidity reported between BD
and ADHD in children, it is surprising that only one study
was found directly comparing the neurocognitive aspects of
these disorders in the absence of comorbidity. BD is often
compared with schizophrenia or other severe psychopa-
thology on cognitive tasks, whereas ADHD is most often
compared with learning disabilities, oppositional defiant
disorder, and conduct disorder. Clearly, if there is extensive
comorbidity between these two disorders in youth as some
of the literature has reported (Faraone et al. 1997; Geller et
al. 2000; Geller et al. 2004; Wozniak et al. 1995), there is a
need to examine not only the behavioral symptom
presentations of each, but also the neurocognitive aspects
Another limitation of this literature is the paucity of
research on cognitive function in pediatric BD (see
Tannock 1998). This field is only in its nascence, however,
and it is encouraging to see numerous studies that have
been published in the past 3 years examining neuro-
cognition in pediatric BD samples. This paper is a
preliminary examination of profiles of pediatric BD and
further research is needed to confirm the findings here.
Additionally, there is the complicating factor of reading
disorder (RD) comorbidity in ADHD. In a study conducted
by Pennington et al. (1993), children with only ADHD
exhibited deficits in executive function, but not in phono-
logical processing, whereas children with only RD
exhibited the opposite profile (deficits in phonological
processing, but not executive function). One limitation of
the current literature is that many studies did not control for
comorbid RD. Several studies reviewed here examined
phonemic fluency in ADHD in the absence of RD, with
continued evidence for phonemic fluency dysfunction.
Thus, while future studies will need to examine the F-A-S
task in ADHD while controlling for the effects of a
comorbid RD diagnosis, there is rising evidence that this
deficit may not be solely explained by RD and may be
particular to the ADHD phenotype.
Here we reviewed the literature and propose evidence for
distinct neurocognitive profiles for BD and ADHD. Reports
of comorbidity of childhood BD with ADHD range from
65–93% (Faraone et al. 1997; Geller et al. 2000, 2004;
Wozniak et al. 1995) in some studies, to 6–10% in others
Neuropsychol Rev (2010) 20:103–120 115
(Carlson 1998; Duffy et al. 2001; Kutcher et al. 1998;
Robertson et al. 2003). Given the similar presentation of
BD and ADHD, it is often difficult to distinguish them from
a purely clinical standpoint. Although more research needs
to be conducted in the area of executive function, especially
with regard to pediatric BD, objective cognitive tasks in the
context of a distinctive neurocognitive profile may provide
insight into subtle differences between BD and ADHD
when they are clinically indistinguishable.
(MH073517:01A1; McCracken and Piacentini, PIs) and was previ-
ously supported by a F31 (MH075292-01; Walshaw, PI). Research
supported by the Center for Intervention and Development of Applied
Research: Translational Research to Enhance Cognitive Control (P50
MH 077248-02; McCracken, PI). F. W. Sabb is supported by the
Consortium for Neuropsychiatric Phenomics (UL1RR024911,
RL1LM009833) and a NARSAD Young Investigator Award. L. B.
Alloy's work on this article was supported by the National Institute of
Mental Health Grants MH52617 and MH77908.
P. D. Walshaw is currently supported by a T32
sponsoredthis research. Asthisis areviewpapertheauthors donothave
access to the primary data of studies reviewed; access to the meta-data
(e.g., effect sizes and calculations), however, can be provided.
No author has a financial relationship with the NIH, which
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medium, provided the original author(s) and source are credited.
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