Frontal and temporal volumes in children with epilepsy
Melita Daleya,*, Jennifer Levitta, Prabha Siddartha, Elizabeth Morminoa,
Cornelius Hojatkashania, Suresh Gurbanib,c, W. Donald Shieldsd,e,
Raman Sankard,e, Arthur Togad, Rochelle Caplana
aDepartment of Psychiatry, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
bDepartment of Pediatrics, University of California at Irvine, Irvine, CA, USA
cDepartment of Neurology, Kaiser-Permanente, Los Angeles, USA
dDepartment of Neurology, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
eDepartment of Pediatrics, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
Received 26 September 2006; revised 14 January 2007; accepted 14 February 2007
Available online 26 March 2007
This study examined if children with cryptogenic epilepsy and complex partial seizures (CPS) have smaller total brain, frontal, and
temporal lobe volumes than normal children and how this is related to seizure, cognitive, psychiatric, and demographic variables. Forty-
four children with CPS and 38 normal children, aged 5–16 years, underwent brain MRI scans at 1.5 T. Tissue was segmented, and total
brain, frontal lobe, frontal parcellation, and temporal lobe volumes were computed. Other than significantly larger temporal lobe white
matter volumes in the CPS group, there were no significant differences in brain volumes between the CPS and normal groups. Earlier
onset, longer duration of illness, younger chronological age, and presence of a psychiatric diagnosis were significantly related to smaller
frontotemporal volumes in subjects with CPS. Although these findings suggest that CPS might affect development of the temporal and
frontal regions, we are unable to rule out the possibility that smaller frontotemporal volumes might predispose children to CPS. These
findings highlight the need to control for seizure, cognitive, psychiatric, and demographic variables in studies of frontotemporal volumes
in pediatric CPS.
? 2007 Elsevier Inc. All rights reserved.
Keywords: Childhood; Complex partial seizures; Frontal lobe; Temporal lobe; Magnetic resonance imaging
Volumetric studies in adults with temporal lobe epilepsy
demonstrate reduced total brain volumes [1–4], total gray
matter and white matter volumes [5,6], bilateral frontopa-
rietal volumes , and white matter volumes of frontal,
temporal, and parietal lobes [3,8]. Although lateralization
of the seizure focus is unrelated to the severity of white
matter volume reduction in temporal, frontal, and parietal
regions , there is a more widespread decrease in neocor-
tical gray matter concentration in frontal, parietal, and
occipital regions in patients with left compared with right
adult temporal lobe epilepsy . Earlier onset and longer
duration of temporal lobe epilepsy are also related to smal-
ler total brain [3,10], white matter [3,11], and gray matter
 volumes, as well as to smaller gray matter volumes of
frontoparietal regions .
The few volumetric studies conducted in childhood epi-
lepsy describe significantly reduced total volume in children
with intractable and medically controlled epilepsy, com-
pared with normal children, and in children with frontal
lobe epilepsy contrasted to those with temporal lobe epi-
lepsy [12,13]. Age at onset, duration of illness, prior status
epilepticus but not simple febrile convulsions, and antiepi-
leptic drug (AED) therapy (e.g., number, type) were related
1525-5050/$ - see front matter ? 2007 Elsevier Inc. All rights reserved.
*Corresponding author. Address: Semel Institute for Neuroscience and
Human Behavior, UCLA, Child Division, Room 48-263, 760 Westwood
Plaza, Los Angeles, CA 90095-1759, USA.
E-mail address: email@example.com (M. Daley).
Epilepsy & Behavior 10 (2007) 470–476
to the severity of cerebral volume reduction in these chil-
dren . However, there was no significant reduction in
gray and white matter volumes of children with new-onset
epilepsy versus sibling controls .
Based on the previously reviewed findings [4,5,7,8,10,
11,13,15,16], the study presented here determined if
children with cryptogenic epilepsy who had complex partial
seizures (CPS), no structural brain abnormalities, and
varying degrees of seizure control have smaller total and
cerebral white and gray matter volumes, as well as smaller
frontal and temporal lobe volumes, compared with normal
children. Also examined was whether children with earlier
onset, longer duration, increased seizure frequency, more
AEDs, left lateralized EEG findings, and a history of
prolonged seizures and/or febrile convulsions have smaller
volumes than those with later onset, shorter duration,
lower seizure frequency, fewer AEDs, right lateralized
EEG findings, and no prolonged seizures or febrile
We determined if the predicted findings were related to
IQ because total gray matter volume , as well as total
and gray matter volumes in the prefrontal region , cor-
relate positively with IQ in normal children. In addition,
moderate to severe intellectual disability is associated with
reduced cerebral volume in medically intractable pediatric
From the developmental perspective, there is a signifi-
cant nonlinear decline in gray matter density that is most
rapid over dorsal frontal and parietal association cortices
between ages 7 and 60 . With maturation, the decrease
in gray matter volume progresses in a back-to-front wave
through adolescence . White matter volume and
myelination, however, increase with age in the left inferior
frontal gyrus in boys  and in the frontal lobe of 5- to 17-
year-old youths [18,19]. Irrespective of age, boys have
larger volumes than girls [22–24].
To examine how CPS are related to brain development,
we also compared the association of age, IQ, and gender
with total brain and frontotemporal volumes in the CPS
and normal groups. Because of the high rate of psychopa-
thology in pediatric epilepsy [25–30] and the association of
psychopathology with volume abnormalities in children
without epilepsy [31–33], we explored if the predicted
findings were also related to the presence of a psychiatric
diagnosis in these children.
The study included 44 children with cryptogenic epilepsy, all of whom
had CPS, and 38 children without epilepsy, aged 5–16. Table 1 summarizes
the demographics, cognitive features, and perinatal complications of the
children in the study. As evident from this table, the normal group had sig-
nificantly higher IQ scores and more children from families of higher
socioeconomic status based on the Hollingshead 2 factor index 
derived from both parent occupational and educational status. Perinatal
data on number of pregnancies and delivery complications were collected
from the children’s mothers using a questionnaire modified from the Yale
Neuropsycho-educational Assessment Scales .
Subjects were included in the study if they had a diagnosis of crypto-
genic epilepsy and CPS, as defined by the International Classification of
Epilepsy , and at least one seizure during the year prior to the child’s
participation in the study. We also included children with a clinical history
of CPS with and without EEG evidence of focal epileptic activity. The
patients did not have EEG studies at the time of the study, and the clas-
sification was based on clinical history and past EEG records. We
excluded patients with a mixed seizure disorder, a neurological disorder
other than CPS, a metabolic disorder, a hearing disorder, past epilepsy
surgery, and a structural MRI abnormality, but not those with mesial
We recruited 36% of the patients with CPS from tertiary centers (e.g.,
UCLA Pediatric Neurology Services, Children’s Hospital of Los Angeles)
and 64% from the community (e.g., Kaiser Sunset, Kaiser—Orange
County, private pediatric neurologists, Los Angeles and San Diego
branches of the Epilepsy Foundation). The primary pediatric neurologist
at each site reviewed the clinical history, EEG records, and diagnoses of
potential study subjects and referred them for the study irrespective of
their psychiatric history. Table 2 summarizes information on seizure
frequency during the past year, current AEDs, age at onset of seizures,
duration of illness, number of simple febrile convulsions, and number of
prolonged seizures (i.e., >5 minutes) obtained from the parents and the
child’s medical records.
Demographic features of study groups
CPS groupNormal group
Low (iv, v)
Full Scale IQb
av2(1) = 4.30, P < 0.04.
bt(80) = 6.93, P < 0.0001.
Seizure-related variables for the CPS group
Age at onset
Duration of epilepsy (years)
M. Daley et al. / Epilepsy & Behavior 10 (2007) 470–476
The classification for the lateralization and localization analyses was
based on a single EEG study conducted at the time of the child’s diagnosis
of epilepsy and not at the time of the study. Of the 44 patients with CPS,
10 had nonlateralized EEG findings, 11 had a left focus, 8 a right focus,
and 13 bilateral foci. EEGs were unavailable for 2 patients with CPS.
Regarding focal EEG findings, 6 patients had no focal findings; 14 had
interictal spikes in the temporal lobe, 13 in the frontal and temporal lobe,
and 9 in other areas; 2 patients had secondary generalization; and 8 had
We enrolled the control subjects without epilepsy from four public and
two private schools in the Los Angeles community after screening for
neurological, psychiatric, language, and hearing disorders through a
telephone conversation with a parent. We excluded from the study
children who had manifested symptoms of these disorders in the past.
This study was conducted in accordance with the policies of the
Human Subjects Protection Committees of the University of California,
Los Angeles. Informed assents and consents were obtained from all
subjects and their parents, respectively.
2.3. Magnetic resonance imaging
All subjects completed MRI scanning on a 1.5-T GE Signa magnetic
resonance imaging scanner (GE Medical Systems, Milwaukee, WI,
USA). The imaging acquisition protocol used to obtain high-resolution
three-dimensional (3D) T1 weighted spoiled grass (SPGR) sequences
included a sagittal plane acquisition with slice thickness of 1.2 mm, repe-
tition time of 24 ms, echo time of 9 ms, flip angle of 22?, acquisition matrix
of 256 · 192, FOV 24, and two excitations.
2.3.2. Image preprocessing
Initially,potentialfluctuations in signal resulting frommagnetic field inhomo-
automated brain extraction program (BET) was used to create a brain mask
mask was manually modified to ensure accurate separation of tissues. The
automated tissue classification method of Shattuck et al.  was then used
to segment the scans by tissue types to create gray matter, white matter, and
cerebrospinal fluid masks. The total intracranial volume was then automati-
cally computed by summing the volumes of these masks.
2.3.3. Cortical object model methods
188.8.131.52. Prefrontal cortex delineation. The protocol for subparcellating the
prefrontal cortex, described in detail in Blanton et al. , can be viewed at
html. Briefly, by use of the cortical object model and all three viewing
planes on the T1 weighted slices, the prefrontal cortex is subparcellated
into the following regions of interest (Fig. 1).
184.108.40.206.1. Inferior frontal gyrus. The inferior frontal gyrus is traced
in the axial plane. This region is defined as the cortex anterior to the
precentral sulcus, inferior to the inferior frontal sulcus, and superior and
posterior to the lateral orbital sulcus.
Tracing begins on the most superior axial slice in which the inferior
frontal sulcus can be delineated or where the pars orbitalis appears. Trac-
ing ends in the most inferior axial section in which the inferior frontal
gyrus can be distinguished, using the lateral orbital sulcus (on the object
model) as the inferior boundary.
220.127.116.11.2. Dorsolateral frontal cortex/middle frontal gyrus. Traced in the
axial plane, the middle frontal gyrus is defined as cortex anterior to the
precentral sulcus, inferior and posterior to the superior frontal sulcus,
superior and anterior to the inferior frontal sulcus, and superior and pos-
terior to the frontal marginal sulcus. Tracing begins on the most superior
axial slice in which the middle frontal gyrus can be delineated. As the oper-
ator moves inferiorly, the inferior frontal sulcus replaces the precentral
sulcus as the inferior boundary, at the point where the precentral sulcus
and inferior frontal sulcus intersect on the object model. The operator
continues to move inferiorly, using the lateral orbital sulcus (on the object
model) as the inferior boundary of the middle frontal gyrus.
18.104.22.168.3. Dorsolateral frontal cortex/superior frontal gyrus. The supe-
rior frontal gyrus is defined as cortex anterior to the precentral sulcus
and superior to the superior frontal sulcus. The object model is used to
establish this region’s most posterior boundary, the precentral sulcus.
Tracing begins on the most superior axial slice where the precentral sulcus
can be distinguished. The frontal marginal sulcus delineates the inferior
boundary of the superior frontal gyrus.
22.214.171.124.4. Orbital frontal cortex. The orbital frontal gyrus is defined as
the cortex inferior to the frontal marginal sulcus, inferior and anterior to
the lateral orbital sulcus, and lateral to the olfactory sulcus. The circular
insular sulcus serves as the most posterior boundary of the orbital frontal
gyrus, which is best seen in the sagittal plane.
Fig. 1. Right: Magnetic resonance image of prefrontal cortex. Left: Three-dimensional cortical object model displaying frontal lobe regions: inferior
frontal cortex in purple, middle frontal cortex in pink, superior frontal cortex in blue, and orbital frontal cortex in green.
M. Daley et al. / Epilepsy & Behavior 10 (2007) 470–476
The coronal view is used to include radial white matter for the inferior
frontal gyrus, middle frontal gyrus, and superior frontal gyrus. The sagit-
tal view is used to include radial white matter for the orbital frontal gyrus.
Deep white matter, the anterior cingulate gyrus, and gyrus rectus are not
included in these drawings.
126.96.36.199. Temporal lobe delineation. In similar fashion, using all three view-
ing planes and the cortical object model, the temporal lobe is drawn in the
sagittal plane with the following boundaries: The temporal lobe is defined
as the cortex inferior to the sylvian fissure, anterior to the lateral parieto-
temporal and temporo-occipital lines, and superior and anterior to the col-
lateral sulcus and posterior transverse collateral sulcus. The operator
includes the amygdala and the hippocampus but excludes the insular
188.8.131.52. Reliability. The drawings were performed by one rater and
checked by a second rater, both without knowledge of the children’s diag-
nosis. A consensus drawing was then determined by agreement of the two
raters about the boundaries of the regions of interest. The rater delineated
the region of interest on the left hemisphere of 10 brains, and interclass
correlation coefficients (ICCs) were calculated between these delineations
and the gold standard. A rater was deemed reliable after achieving an
ICC of 0.9 or higher. On brain regions examined in this study, the ICCs
were 0.94 for inferior frontal cortex, 0.96 for middle frontal cortex, 0.95
for orbital frontal cortex, 0.90 for superior frontal cortex, and 0.94 for
temporal lobe, with an interrater reliability of 0.9.
The Wechsler Intelligence Scale for Children III (WISC-III) ,
administered to the children, generated Full Scale, Verbal, and Perfor-
mance IQ scores.
The Schedule for Affective Disorders and Schizophrenia for School-
Age Children, Present and Lifetime Version (K-SADS-PL) , was
administered separately to each child and parent by R.C. or a research
assistant trained in the administration of the interview. Because the child
or parent often talks about the child’s seizures during the interview, these
interviewers were not blinded with respect to the child’s seizure disorder
(i.e., presence or absence, type). A second clinician reviewed videotapes
of the child interviews and audiotapes of the parent interviews, and a con-
sensus DSM-IV  diagnosis was reached. Where a diagnostic consensus
was not reached, the child was excluded from the study.
Given the large number of diagnoses relative to the number of subjects
in each diagnostic group, we grouped the diagnoses as follows: ‘‘affective/
anxiety’’ disorders included any mood or anxiety disorder, and ‘‘disrup-
tive’’ disorders included attention-deficit hyperactivity disorder (ADHD),
oppositional defiant disorder, and conduct disorder. Children with a
‘‘comorbid’’ diagnosis had both ‘‘affective/anxiety’’ and ‘‘disruptive’’
2.6. Data analysis
We compared total brain, gray matter, and white matter volumes
between the CPS and normal groups using ANCOVAs. To compare fron-
tal and temporal gray and white matter volumes in the CPS and normal
groups, we estimated mixed models using repeated measures with group
(CPS, normal) as the intersubject and hemisphere (left, right) as the intra-
subject classification variable for inferior frontal, orbital frontal, dorsolat-
eral prefrontal (sum of dorsolateral superior and middle frontal cortex),
and temporal lobes separately. Demographic (i.e., age, gender, socioeco-
nomic status, ethnicity) and cognitive (Full Scale IQ) variables were used
as covariates in all these analyses. Total brain volume was also included as
a covariate for all analyses of volumes other than total brain volume. All
tests were two-tailed, and an a level of 0.05 was adopted for all inferences.
Within the CPS group, we examined the relationship of volumes to sei-
zure, cognitive, and perinatal variables (i.e., delivery problems, pregnancy
problems). First, to reduce the number of seizure-related variables to
include in the analyses, a principal component analysis (PCA) of seizure
variables including CPS subjects from all our studies (N = 105) was per-
formed. This PCA revealed four components with the following loadings:
a duration (0.89)/onset (?0.88) component; an EEG localization (0.87)/
lateralization (0.87) component; a prolonged seizures (0.92)/febrile convul-
sions (0.79) component; and a seizure frequency (0.87)/number of AEDs
(0.78) component. In the EEG component, localization of epileptic activ-
ity was classified as frontal, temporal, frontotemporal, or other, and later-
alization as left, right, or bilateral focal epileptic activity. Number of
AEDs was subdivided into no AEDs, monotherapy, and polytherapy.
These four components were then used as the seizure-related variables
when investigating their relationship to volumes in the CPS group.
In investigating the association of volumes with seizure and cognitive
variables, we computed mixed linear models for gray and white matter
volumes for the temporal lobe, frontal lobe, and the following frontal lobe
parcellations: dorsolateral prefrontal cortex (sum of dorsolateral superior
and middle frontal cortex), inferior frontal cortex, and orbital frontal cor-
tex. Hemisphere (left, right) was used as the intrasubject classification var-
iable. Age, gender, ethnicity, socioeconomic status, seizure components,
Full Scale IQ, and presence of a psychiatric diagnosis (N = 19) were used
as predictors. We used the following model-building strategy to determine
which of these variables were predictive of the volumetric measures. We
first included all these variables as predictors in the general linear model.
We then used a combination of a stepwise strategy (in which the variables
are selected for either inclusion in or exclusion from the model in a sequen-
tial fashion based solely on statistical criteria) and inclusion or exclusion
of variables based on careful scrutiny of the resulting model. Thus, follow-
ing the fit of the model from stepwise selection, the importance of each
variable included in the model was verified. We also checked for variables
whose coefficients changed markedly in magnitude when other variables
were excluded. This process of deleting, refitting, and verifying was
performed until a final model was obtained that explained the data.
We also examined if the volumes in the CPS group differed between the
lateralization (left, right, bilateral, and no findings) and localization (tem-
poral, frontotemporal, other, and no findings) groups using ANCOVAs.
In addition, we determined the relationship of an additional index of
seizure severity, recruitment source (tertiary vs community), to volumes.
3.1. Between-group volume differences
Group comparisons controlling for demographic, IQ,
total brain volume, and perinatal variables revealed signif-
icantly larger temporal white matter volumes in the CPS
group than in the normal group, but no significant differ-
ences in total brain, gray matter, white matter, remaining
frontal lobe parcellation, and temporal lobe gray matter
volumes. Post hoc testing indicated that these findings were
not accounted for by the presence of slowing on EEG.
There were also no significant differences in left–right
volume asymmetry of these two groups (Table 3).
3.2. Modeling of total and frontotemporal volumes in the
3.2.1. Seizure variables
Mixed linear models with demographic and seizure-
related variables, IQ scores, psychiatric diagnosis, and
pregnancy complications as predictors demonstrated that
M. Daley et al. / Epilepsy & Behavior 10 (2007) 470–476
age at onset/duration and history of prolonged seizures or
simple febrile convulsions, as well as lateralization and
localization of epileptic activity, were differentially related
to frontotemporal volumes. Earlier onset/longer duration
of CPS was associated with decreased orbital frontal gray
(F(1,32) = 4. 58, P < 0.04) and white matter (F(1,32) = 6.
24, P < 0.01) volumes, as well as decreased temporal lobe
white matter volumes (F(1,32) = 5.21, P < 0.03). The chil-
dren with a history of prolonged seizures or simple febrile
convulsions had larger inferior frontal white (F(1,34) =
6.87, P < 0.01) and gray matter (F(1,34) = 7.22, P < 0.01)
volumes than those without prolonged seizures and/or sim-
ple febrile convulsions. The children with left lateralized
epileptic activity on EEGs had significantly smaller total
white matter volumes (F(3,40) = 3.53, P < 0.02) compared
with those with bilateral (P < 0.01) or right lateralized
(P < 0.02)epilepticactivity
(P < 0.07). Recruitment source (i.e., tertiary vs community)
was unrelated to brain volumes.
and no EEG findings
3.2.2. Psychiatric diagnosis
Four children had disruptive disorders, seven had affec-
tive/anxiety disorders, seven had combined disruptive and
affective/anxiety disorders, and one had a tic disorder.
The 19 children with CPS with a psychiatric diagnosis
had significantly smaller inferior frontal white matter
volumes (F(1,33) = 4.60, P < 0.04) compared with those
without a diagnosis.
3.2.3. IQ, age, and gender
In the normal group, larger total brain (F(1,34) = 9. 37,
P < 0.004), total gray matter (F(1,34) = 5.52, P < 0.03),
and total white matter (F(1,32) = 11.53, P < 0.002) vol-
umes were positively related to higher IQ scores. Other
than a negative association with dorsolateral prefrontal
gray matter volumes (F(1,3) = 4.07, P < 0.05), age was
unrelated to total brain and frontotemporal brain volumes
in the normal group. In contrast, in the CPS group, with
seizure variables in the model, older age, not IQ, was signif-
icantly related to larger total (F(1,28) = 5.67, P < 0.03),
inferior frontal (F(1,33) = 4.39, P < 0.04), and temporal
(F(1,30) = 7.41, P < 0.01) white matter volumes and
smaller total (F(1,39) = 6.07, P < 0.02), dorsolateral pre-
frontal (F(1,39) = 7.02, P < 0.01), and orbital frontal
(F(1,39) = 10.54, P < 0.003) gray matter volumes. In both
subject groups, compared with girls, boys had significantly
larger gray and white matter volumes (P < 0.04) in all fron-
totemporal regions studied except the inferior frontal
These findings suggest that other than increased white
matter volumes of the temporal lobe, there were no signif-
icant differences in total brain and frontal volumes of chil-
dren with CPS and normal children. However, among the
subjects with CPS, those with earlier onset, longer dura-
tion, a history of prolonged seizures/febrile convulsions,
left lateralization of EEG findings, younger age, and a
psychiatric diagnosis had significantly smaller volumes
than those with later onset, shorter duration, bilateral or
right focal EEG findings, older age, and no psychiatric
From the methodological perspective, our findings
underscore the importance of including large samples of
children and controlling for these relevant variables in
studies on epilepsy and brain structure in children with
CPS. From the theoretical perspective, increased white
matter volumes of the temporal lobe can be understood
in light of recent studies on the ongoing dynamic changes
in gray and white matter volumes in normal childhood
and adolescence [19–21,42], surgically treated children with
epilepsy, animal studies, and studies on the association of
spikes, perfusion, and myelination.
As age increases in normal childhood and adolescence,
there is a reduction in gray matter density , a postero-
anterior decrease in gray matter volume , and an
increase inwhite matter
[19,21,42]. These developmental changes vary by gender
. Our cross-sectional between-group findings suggest
that myelination of the temporal as well as the frontal lobe
might be vulnerable in children with CPS, 61% of whom
had EEG evidence of temporal lobe involvement.
In support of this explanation, Andres et al. 
described increased cerebral, gray matter, and white matter
volumes in surgically treated children with epilepsy who
have cortical dysplasia. In immature rats, repeated seizures
are associated with defects in lipid metabolism and myelin
accumulation, particularly when seizures occur early
during the phase of glial proliferation [44–46].
Functional magnetic resonance imaging studies have
shown that focal interictal spikes are associated with local
hyperperfusion and distal hypoperfusion . During sei-
zures, transient local hyperperfusion is associated with
Total brain and frontotemporal volumes in the CPS and normal groups
CPS groupNormal group
Gray matter (GM)
White matter (WM)
1395.35 (141. 07)
Inferior frontal GM
Inferior frontal WM
Orbital frontal GM
Orbital frontal WM
Dorsolateral prefrontal GM
Dorsolateral prefrontal WM
bF(1,70) = 5.83, P < 0.02 with demographic and IQ variables in model.
M. Daley et al. / Epilepsy & Behavior 10 (2007) 470–476
accelerated myelination . Thus, involvement of the tem-
poral lobe in most of the children in the study and seizure-
related local blood flow increases during development may
underlie the larger white matter volume in this region. The
dissimilar relationships of IQ and age with volume in the
patient and normal groups also imply that CPS adversely
affects normal brain development.
Compared with prior volumetric studies in children with
epilepsy, like Hermann and colleagues’  findings in chil-
dren with new-onset seizures, we did not find the smaller
total brain volumes reported in the studies of Lawson
et al. [13,16]. However, Lawson and colleagues’ subjects
had more severe epilepsy suggested by longer duration of
illness, earlier age of onset (age 0–14), and higher rate of
epileptogenic lesions, as well as inclusion of 21% of chil-
dren with mild (IQ = 56–70) and 18% with moderate/
severe (IQ < 55) intellectual disability. Different morpho-
metric procedures may also underlie the variable total
brain volume findings in these studies.
Similar to adults with temporal lobe epilepsy, we found
inverse relationships for both duration of illness [1,3,9,10]
and left focal epileptic activity  with smaller volumes.
Yet, recent evidence for extensive volume reduction in
adults with temporal lobe epilepsy [2,3,6,31,50] implies a
cumulative more widespread effect of recurrent seizures
on brain volume reduction than in children. Prospective
studies are needed to determine how these structural
abnormalities evolve over time.
The inferior frontal gyrus findings are interesting given
its role in syntax , semantics , phonology , and
higher-level linguistic functions  and evidence for both
basic  and higher-level linguistic deficits in children with
CPS [55,56]. The larger gray and white matter volumes of
the inferior frontal gyrus of the children with CPS with a
history of prolonged seizures and/or febrile seizures imply
that duration of seizures negatively impacts the develop-
ment of this region and the linguistic functions it subserves.
The relationship of inferior frontal gyrus volumes to pres-
ence of a psychiatric diagnosis and the recent clinical evi-
dence of higher-level linguistic deficits and disruptive
disorder diagnoses and externalizing behaviors in children
with CPS  may reflect impaired maturation of inferior
The subjects with CPS with a psychiatric diagnosis were
quite heterogenous, with four disruptive disorder diagno-
ses, seven affective/anxiety disorder diagnoses, seven
combined disruptive and affective/anxiety disorders, and
one tic disorder. Compared with normal children, children
without epilepsy with diagnoses such as autism , gener-
alized anxiety disorder , and posttraumatic stress disor-
der  have larger volumes, whereas those with ADHD
have smaller dorsolateral prefrontal cortex volumes .
Studies on larger samples of children are needed to delin-
eate how type of psychiatric diagnosis is related to brain
volumes in pediatric CPS.
Finally, study limitations include a relatively small
sample of CPS and normal subjects, multivariate analysis
techniques to control for the several confounding factors,
lack of clinical information with respect to possible etiol-
ogy and current EEG findings, and possible memory bias
in seizure-related information collected from parents, and
emphasize the need for replication of the study’s findings.
With these limitations in mind, the findings suggest that
CPS may affect brain development, particularly in the
temporal and frontal regions in children with average intel-
ligence. They also highlight the need to control for multiple
variables, including seizure, cognitive, psychiatric, and
demographic variables, in the study of frontotemporal
volumes in pediatric CPS. Based on where the child is in
the dynamic ongoing maturation of
regions [19,20], these variables may have different effects
on these volumes (i.e., increase or decrease).
This study was supported by Grants NS32070 (R.C.)
and MH067187 (R.C.). We appreciate the technical assis-
tance of Erin Lanphier, Ph.D., Caroline Bailey, Ph.D.,
Amy Mo, Alexander Kaminski, Lorrie Shiota, and Renea
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