Mapping Cortical Thickness and GrayMatter Concentration in First EpisodeSchizophrenia
Katherine L. Narr1, Robert M. Bilder2,3, Arthur W. Toga1,3,
Roger P. Woods4, David E. Rex1, Philip R. Szeszko4, Delbert
Robinson4, Serge Sevy4, Handan Gunduz-Bruce4, Yung-Ping
Wang1, Heather DeLuca1 and Paul M. Thompson1
1Laboratory of Neuro Imaging, Department of Neurology,
Geffen School of Medicine at UCLA, Los Angeles, CA, USA,2Department of Psychiatry and Biobehavioral Sciences,
Geffen School of Medicine at UCLA, Los Angeles, CA, USA,3Ahmanson-Lovelace Brain Mapping Center, Department of
Neurology, Geffen School of Medicine at UCLA,
Los Angeles, CA, USA and 4Department of Psychiatry
Research, The Zucker Hillside Hospital, North-Shore Long
Island Jewish Health Systems, Glen Oaks, NY, USA
We mapped regional changes in cortical thickness and intensity-based cortical gray matter concentration in first episode schizo-phrenia. High-resolution magnetic resonance images were obtainedfrom 72 (51 male, 21 female) first episode patients and 78 (37 male,41 female) healthy subjects similar in age. Cortical pattern match-ing methods allowed comparisons of cortical thickness and graymatter concentration at thousands of homologous cortical locationsbetween subjects in three dimensions. Principal componentsanalyses reduced measures obtained across the cortex to identifyglobal differences in cortical thickness/gray matter concentration.First principal component factor scores showed significant effectsof diagnosis, sex and age for both cortical measures. Diagnosis andage effects remained significant after brain size correction. Corticalthickness and gray matter concentration values were highlycorrelated. Statistical maps showed significant regional graymatter thinning in frontal, temporal and parietal heteromodalassociation cortices bilaterally in first episode patients. Regionalreductions in cortical gray matter concentration were similar butpronounced in the superior temporal lobe. Regional reductions incortical thickness and gray matter concentration are present atdisease onset in brain regions linked with functional disturbancesin schizophrenia. Cortical thickness and gray matter concentrationmapping produce similar results, although the concentration metricmay be influenced by diagnostic differences in extra-corticalcerebrospinal fluid and surface curvature/complexity.
Keywords: brain structure, heteromodal association cortices, imaging,prefrontal cortices, superior temporal gyrus
Introduction
A dialectic of hypotheses focusing on discrete cortical, limbic,
striatal or diencephalic regional or system abnormalities [e.g.
left superior temporal gyrus (Shenton et al., 1992), thalamus
(Andreasen et al., 1994), fronto-striatal (Robbins, 1990), fronto-
limbic (Weinberger et al., 1992; Bilder et al., 1995), cortico-
striatopallidothalamic (Braff et al., 1995), corticostriatothalamo-
cerebellar (Andreasen et al., 1999)], versus hypotheses of
widespread cortical gray matter abnormalities (Pfefferbaum
et al., 1994; Lim et al., 1996a) perhaps maximal in heteromodal
cortex (Pearlson et al., 1996), have been proposed to explain
the underlying neurobiology of schizophrenia. These hypoth-
eses are supported to degree by evidence from in vivo imaging
studies. That is, existing imaging data confirms that multiple
brain regions are affected in schizophrenia (Pearlson, 2000;
Shenton et al., 2001). However, disease effects appear subtle
(Ward et al., 1996; Lawrie and Abukmeil, 1998) and regional
inconsistencies in findings are common. Despite mixed results
that may stem from small effect sizes in the presence of large
inter-individual differences in brain structure, reductions in
tissue volumes have been reported in some cortical and sub-
cortical regions with relative consistency. Notably, gray matter
deficits in lateral and medial temporal cortices, principally the
superior temporal gyrus (and hippocampus subcortically), are
reported in the majority of studies (Lawrie and Abukmeil, 1998;
Wright et al., 1999b, 2000; Shenton et al., 2001). Gray matter
deficits in other neocortical regions, including frontal cortices,
particularly prefrontal and orbitofrontal regions, and parietal
cortices, are also observed, although less frequently replicated
(Shenton et al., 2001).
In humans, the majority of the cerebral cortex consists of
association areas that form functional circuits reciprocally
linking different cortical and subcortical centers to support
higher cognitive functions. During prenatal development, mi-
grating cells from the marginal zone of the telencephalic vesicle
cause the cortex to thicken. The thickness of the cerebral
cortex (ranging between 1.5 to 4.5 mm) thus reflects the
density and arrangement of cells (neurons and neuroglia and
nerve fibers) (Parent and Carpenter, 1995). Disturbances in
neurogenesis, neuronal migration, differentiation and synapto-
genesis and in mechanisms that involve neuronal and synaptic
pruning have been implicated in schizophrenia (Jakob and
Beckmann, 1986; Arnold, 1999). These factors may selectively
affect the lamination of specific cortical regions and may prove
a more sensitive measure by which to identify alterations in
brain structure that form the basis of functional disturbances
characterizing individuals with schizophrenia. However, to
identify regional changes in cortical gray matter, magnetic
resonance imaging (MRI) studies have traditionally compared
volumes from discrete cortical regions of interest. More re-
cently, a number of studies have also used sophisticated
computational image analysis techniques that allow voxel-wise
comparisons of gray matter distributions to be made throughout
the entire brain volume (Wright et al., 1999a; Sigmundsson
et al., 2001; Wilke et al., 2001; Ananth et al., 2002) or across the
cortex exclusively (Thompson et al., 2001b; Sowell et al., 2002;
Narr et al., 2003). Studies using voxel-based morphometry
(VBM) methods (Ashburner and Friston, 2000) and/or using
search regions exclusively at the cortex (Thompson et al.,
2001b) sometimes refer to differences observed in the pro-
portion of gray matter voxels, which are defined based on signal
intensity thresholds, compared with voxels representing other
� Oxford University Press 2004; all rights reserved Cerebral Cortex doi:10.1093/cercor/bhh172
Cerebral Cortex Advance Access published September 15, 2004
tissue types as gray matter density differences. However, to
avoid confusion with the cell packing density measured cyto-
architectonically, in this study we will refer to changes in the
proportion of gray matter voxels with respect to voxels
representing other tissue types, as differences in intensity-based
gray matter concentration. The relationships between intensity-
based gray matter concentration and cortical thickness, which
has been associated with neuronal packing density (Selemon
et al., 1995, 1998), remain to be characterized.
A few studies have assessed cortical thickness in schizo-
phrenia using postmortem data. These studies, focusing mainly
on frontal regions, have shown that neuronal density is increased
and that neuronal somal sizes are smaller in patients with
schizophrenia compared with control groups (Selemon et al.,
1995, 1998, 2003; Rajkowska, 1997). Importantly, increased
neuronal packing density and smaller somal sizes appear to
correspond with small reductions in cortical thickness. In-
creased neuronal density has also been observed in the anterior
cingulate (Bouras et al., 2001) and in occipital regions (Selemon
et al., 1995), while increases in the density of microglia has
been reported in both frontal and temporal cortical regions
(Radewicz et al., 2000). Post-mortem studies, however, are
limited by the labor intensiveness of measurement methods,
rendering it impractical to measure cellular density and thick-
ness in all cortical regions. Furthermore, post-mortem speci-
mens are less commonly available and sample sizes have been
comparatively small in these investigations. Thus, at present,
post-mortem studies may not be able to adequately address the
regional specificity of cortical thickness changes in schizo-
phrenia. In contrast, in vivo imaging data togetherwith improve-
ments in computational image analysis methods may allow
differences in cortical thickness across the cortex to be esti-
mated at high resolution using automated or semi-automated
procedures.
To our knowledge, only three prior studies have examined
cortical thickness in schizophrenia using imaging data. Of these,
only one has assessed cortical thinning across the entire cortex
at relatively high spatial resolution (Kuperberg et al., 2003).
Results showed significant thinning in distributed areas of the
cortex, but most prominently in frontal and temporal regions, in
chronic schizophrenia patients relative to demographically
similar healthy comparison subjects. A second study examined
sulcal and gyral cortical thickness separately collapsed over
each lobar region in patients with childhood and adolescent
onset schizophrenia compared with age equivalent healthy
controls (White et al., 2003). Significant thinning was observed
in the cortex underlying the sulci in frontal, temporal and
parietal regions in schizophrenia patients. Significant cortical
thinning beneath the gyri was observed in the temporal lobe
only. Another study examining exclusively prefrontal regions in
first episode schizophrenia (Wiegand et al., 2004), however, did
not detect cortical thinning averaged across the entire pre-
frontal lobe. Notwithstanding, patients showed significant
reductions in prefrontal gray matter volume and cortical
thickness and volume were significantly correlated. Interest-
ingly, both age and age at first medication were negatively
correlated with prefrontal cortical thickness in first episode
patients but not in healthy control subjects, or in patients with
first episode affective psychosis.
Despite mixed findings, prior evidence suggests that the
pathophysiological mechanisms underlying schizophrenia
affect cortical regions linked by functional circuitry and may
manifest as abnormalities in cortical thickness and/or lamina-
tion. Advanced image analysis methods and large sample sizes,
however, may be necessary to isolate small and regionally
specific differences in cortical thickness, given that effect sizes
for global and regional gray matter abnormalities in volumetric
studies are reported as small (Ward et al., 1996; Lawrie and
Abukmeil, 1998). In this investigation, we therefore set out to
examine cortical thickness at sub-voxel resolution across the
entire cortex in a large sample of first episode patients, who had
received little or no prior medication exposure, compared with
demographically similar healthy subjects. To increase the likeli-
hood of isolating regional changes cortical thickness, we used
cortical pattern matching methods that control for individual
differences in anatomy by matching homologous cortical
regions between subjects (Thompson et al., 2000, 2001a). We
hypothesized that cortical thinning would occur predominantly
in association cortices (prefrontal, temporal and parietal
regions), as implicated in earlier investigations of cortical thick-
ness in schizophrenia (Selemon et al., 1998; Kuperberg et al.,
2003; White et al., 2003). The modulating influences of sex and
age were also examined, given that these variables have not
been assessed in association with cortical thickness in schizo-
phrenia. As a secondary goal, we aimed to determine whether
intensity-based cortical gray matter concentration (the distri-
bution of voxels segmenting as gray matter), as measured in
VBM (Wright et al., 1999a; Sigmundsson et al., 2001; Wilke et al.,
2001; Ananth et al., 2002) and earlier cortical pattern matching
studies (Thompson et al., 2001b; Narr et al., 2003), indexes
similar disease-related processes in schizophrenia. Principal
components analyses were used to reduce cortical thickness
and gray matter concentration values obtained at thousands
of homologous cortical locations to examine overall effects of
diagnosis and hemisphere. To identify the regional specificity of
cortical thinning and/or reduced intensity-based gray matter
concentration, statistical comparisons were performed at each
cortical location. Relationships between cortical thickness and
intensity-based gray matter concentration were compared at
both the global and regional levels.
Materials and Methods
SubjectsSubjects included 72 (51 male, 21 female) patients experiencing their
first episode of schizophrenia and 78 (37 male, 41 female) healthy
comparison subjects, similar in age (patients: mean ± SD = 25.1 ± 4.7
years; controls: 27.3 ± 6.6 years). A structured diagnostic interview, the
Schedule for Affective Disorders and Schizophrenia (Endicott and
Spitzer, 1978) and the Structured Clinical Interview for Axis I DSM-IV
Disorders (First et al., 1997) were performed to determine diagnostic
status of patients. Patients were assessed longitudinally to confirm
diagnoses made at the initial episode. Psychopathology was assessed
using the Schedule for Affective Disorders and Schizophrenia Change
Version with Psychosis and Disorganization Items rating scale and the
Scale for the Assessment of Negative Symptoms (Andreasen, 1984).
Thirty-nine patients (54%) were drug-naive at the time of the scan. The
median number of days of antipsychotic medication received by the
remaining first episode patients prior to scanning was 8 days (range =1--187 days).
Healthy comparison subjects were recruited through local newspa-
per advertisements and community word of mouth. Healthy controls
had no history of psychiatric illness as determined by clinical interview
using the Structured Clinical Interview, nonpatient edition. Exclusion
criteria for all subjects included serious neurological or endocrine
disorders, any medical condition or treatment known to affect the
brain, or meeting DSM-IV criteria for mental retardation. The North
Page 2 of 12 Cortical Thickness in First Episode Schizophrenia d Narr et al.
Shore--Long Island Jewish Health System Institute Review Board (IRB)
approved all procedures and informed written consent was obtained
from all subjects. Additional approval for image processing and analysis
was received from the UCLA IRB.
Image Acquisition and PreprocessingHigh-resolution 3-D SPGR MR images were obtained on a GE 1.5 T
scanner (General Electric, Milwaukee, WI) as a series of 124 contiguous
1.5 mm coronal brain slices (256 3 256 matrix, 0.86 mm 3 0.86 mm in-
plane resolution). Each image volume was corrected for magnetic field
inhomogeneities (Zijdenbos and Dawant, 1994; Sled and Pike, 1998) and
non-brain tissue, including the scalp, bone and meninges, was manually
removed from each brain slice (inter-rater reliability for scalp editing
procedures, rI = 0.99). Image volumes were resampled into 1 mm
isotropic voxels and corrected for head tilt and alignment using a three-
translation and three-rotation rigid-body transformation with no scaling.
For rigid body transformation, 10 standard anatomical landmarks were
identified in all three planes, and matched with a set of corresponding
point locations predefined on the ICBM-305 average brain as previously
detailed (Sowell et al., 1999; Narr et al., 2002). Each brain volume was
thus reoriented into the standard co-ordinate system of the ICBM-305
average brain (Mazziotta et al., 1995) using a trilinear interpolation and
a six parameter Procrustes fit. Scalp-edited MRI volumes were then used
to estimate brain volume and for tissue segmentation where voxels were
automatically classified as most representative of gray matter, white
matter and cerebrospinal fluid (CSF) as based on signal intensity
thresholds using a partial volume correction method (Shattuck et al.,
2001).
Cortical Pattern MatchingCortical pattern matching methods were used to spatially relate
homologous regions of cortex between subjects. These matching
algorithms are employed to ensure that gray matter measures (cortical
thickness and intensity-based gray matter concentration) are obtained
from equivalent cortical locations in each individual (Narr et al., 2001;
Thompson et al., 2001b; Sowell et al., 2002). For cortical pattern
matching, a cortical surface extractor is first used to obtain parametric
models of the cortex from each MR volume (MacDonald et al., 1994).
The cortical surface parameter space coordinates are made up of 65 536
surface points, but do not yet index the same anatomy across all
subjects. In order to match equivalent cortical regions between
subjects, the cortical surface models from each individual were used
to outline 38 primary cortical sulci and fissures employing previously
validated anatomic delineation protocols (www.loni.ucla.edu/~esowell/
new_sulcvar.html). The manually derived sulcal landmarks were then
used as anchors to drive the surrounding cortical surface anatomy of
each individual into correspondence. That is, during the surface-
warping procedures, the algorithm computes a 3-D vector deformation
field that records the amount of x, y and z coordinate shift (or
deformation), associating the same cortical surface locations in each
subject with reference to the average anatomical pattern of the entire
study group (Thompson et al., 2000, 2001a,b). In this study, the cortical
pattern matching algorithms were used only to associate the same
parameter space coordinates across subjects without actually warping
each cortical surface model to the average. Cortical models thus remain
in native space but are reparameterized such that the same anatomy
bears the same coordinate locations in each subject. Reliability for the
manual outlining of sulcal landmarks was established on six test brains,
where the 3-D root mean square distance was <2 mm for all landmarks
within and between raters as previously described (Narr et al., 2003).
Intensity-based Gray Matter ConcentrationThe 3-D deformation vector fields obtained from the cortical pattern
matching methods allow a local measurement of gray matter to be made
at spatially homologous 3-D cortical surface locations in each subject,
referencing corresponding point locations in spatially registered tissue
classified scalp-edited brain volumes. Tissue classified brain volumes
were obtained using the partial volume correction method described
above (Shattuck et al., 2001). To quantify cortical gray matter, we
measured the proportion (or concentration) of voxels segmenting as
gray matter based on signal intensity information, relative to all other
tissue types, within a sphere with a fixed radius of 15 mm at homologous
cortical surface locations in each individual. For each point on the
cortical surface, gray matter concentration ratios (ranging between 0.00
and 1.00) can be compared statistically to provide maps indexing very
local differences in tissue proportions across the entire cortex within or
across groups (Thompson et al., 2001b; Sowell et al., 2002; Narr et al.,
2003).
Cortical ThicknessTo quantify cortical gray matter thickness, the 3-D deformation fields
obtained from the cortical pattern matching algorithms were again used
to equate homologous cortical locations between individuals. Cortical
thickness was defined as the 3-D distance measured from the cortical
white--gray matter boundary in the tissue classified brain volumes
(Shattuck et al., 2001) to the cortical surface (gray--CSF boundary) in
each subject using the 3-D Eikonal equation (Sapiro, 2001). Tissue
classified brain volumes were resampled at 0.33 mm cubic voxels to
obtain distance measures indexing gray matter thickness at sub-voxel
spatial resolution. Gray matter thickness was then measured at
thousands of homologous cortical locations in each subject. Impor-
tantly, while the gray matter concentration measure estimates the ratio
of gray matter within the cortical mantle relative to other tissue types,
gray matter thickness quantifies only the distance of the cortical ribbon
across the entire cortex in millimeters. Gray matter thickness measures
may again be averaged and compared at each cortical surface location
providing spatially detailed maps of local thickness differences within or
between groups.
Statistical AnalysesTo circumvent the need to correct for statistical comparisons made at
each cortical surface location (surface points) and to examine global
effects of cortical gray matter, Principal Component Analysis (PCA) was
first used to reduce (i) intensity-based gray matter concentration
and (ii) cortical thickness values, measured at the 65 536 spatially
homologous cortical surface locations in each individual, into principal
components. PCA was performed for each hemisphere separately to
allow the examination of hemispheric asymmetries and potential
interactions between Hemisphere and Diagnosis in statistical analyses.
The scree plots in Figure 1 show that the first components for gray
matter concentration explained 28 and 29% of the total variance for the
left and right hemispheres respectively. For cortical thickness, 33% of
the total variance was explained by the first PCA component for both
hemispheres. Only components falling above the elbow (or bend) of the
scree plots were examined statistically. Figure 1 shows that approxi-
mately four components fall above the elbow of the scree plots for all
measures. Figure 1 also shows the variance accounted for by additional
principal components where no factor beyond the fourth component
accounts for >4% of the total variance.
Factor scores from the first four PCA components were thus included
as dependent variables in statistical analyses using the General Linear
Model (GLM). Factor scores from the left and right hemisphere were
included as repeated measures. Diagnostic group (Schizophrenia
patients; Normal controls) was included as a categorical predictor
variable. Sex was included as a covariate, given that different ratios of
males and females were present within each diagnostic group. Inter-
actions between Diagnosis and the covariate, Sex, were also examined.
Age was included as a second covariate. All interactions with the within
subjects variable, Hemisphere, were included in the model. To confirm
that total brain size did not contribute to any observed schizophrenia
effects, statistical analyses were performed both with and without
covarying for total brain volume. A similar statistical model was used to
examine group differences in total brain volume and total gray matter,
white matter and CSF volumes, although Hemisphere was not included
as a variable.
To follow up significant omnibus results from analyses of PCA factor
scores, statistical comparisons were performed at each cortical surface
location in 3-D to reveal the regional specificity of intensity-based gray
matter concentration and cortical thickness abnormalities in first
episode schizophrenia. Main effects of Diagnosis were again examined
after covarying for Sex. Interactions between Diagnostic group and the
covariate, Sex, were also examined. Regional effects of Age were not
examined given that diagnostic groups were similar in age and showed
Cerebral Cortex Page 3 of 12
similar aging effects for the PCA factor scores as shown in Figure 2.
Finally, Diagnostic group differences were examined within male and
female groups separately to confirm that sex-related differences in
global brain size did not influence any observed disease-related effects.
The results of these tests, performed at 65 536 cortical locations in 3-D,
were mapped onto the group-averaged cortical surface model where
statistically significant results are indexed in color. For all analyses,
a two-tailed alpha level of 0.05 (uncorrected) was used as the threshold
for statistical significance.
Finally, Pearson’s correlation coefficients were used to examine
relationships between cortical intensity-based gray matter concentra-
tion and cortical thickness for the same PCA components. Correlations
between gray matter concentration and cortical thickness measures
were also performed at each cortical location in 3-D to show the extent
of statistical relationships at the regional level. The average and
variability distributions of cortical thickness and gray matter concen-
tration were examined within each group.
Results
Total Brain and Brain Tissue Volumes
Main effects of Diagnosis were absent for total brain volume
although the effect of the covariate, Sex, was highly significant
[F(1,145) = 48.13, P < 0.00001]. For total gray matter volume,
significant main effects of Diagnosis [F(1,145) = 4.81, P < 0.02],
Sex [F(1,145) = 35.20, P < 0.00001] and Age [F(1,145) = 9.14,
P < 0.002] were detected. After correcting for total brain
volume, effects of Diagnosis [F(1,144) = 14.06, P < 0.0002] and
Age [F(1,144) = 42.54, P < 0.00001] remained significant. White
matter volumes showed only main effects of Sex [F(1,145) =32.90, P < 0.00001] and Age [F(1,145) = 4.01, P < 0.05]. After
covarying for total brain volume, only main effects of Age
remained significant [F(1,144) = 12.23, P < 0.0006]. CSF volumes
showed main effects of Diagnosis [F(1,145) = 3.93, P < 0.049],
Sex [F(1,145) = 14.77, P < 0.0002] and Age [F(1,145) = 7.64,
P < 0.006]. After brain size correction, main effects of Diagnosis
[F(1,144) = 6.58, P < 0.01] and Age [F(1,144) = 10.10,
P < 0.00001] were significant. Means and standard deviations
for total brain and brain tissue volumes are provided in Table 1
in groups defined by Sex and Diagnosis. To show relative group
differences after correcting for total brain volume, tissue
volumes were residualized for brain volume and residuals were
added to the means obtained from the entire sample for each
tissue compartment.
Intensity-based Gray Matter Concentration PCA Scores
Factor scores from the first principal component, accounting
for ~28% of the variance, showed significant main effects of
Diagnosis [F(1,145) = 15.79, P < 0.0001], Sex [F(1,145) = 4.23,
P < 0.01] and Age [F(1,145) = 6.11, P < 0.01] for gray matter
concentration. No effects of Hemisphere or interactions
between the predictor variable and any of the covariates were
observed. Effects of Diagnosis [F(1,144) = 16.35, P < 0.0001] andAge [F(1,144) = 6.15, P < 0.01] remained significant after
covarying for total brain volume. Figure 2 (top panel) shows
factor scores from the first PCA component plotted by age in
groups defined by Sex and Diagnosis. Factor scores from the
second principal component (~8% of the total variance)
showed main effects of Age [F(1,145) = 4.01, P < 0.04] and
Hemisphere [F (1,145) = 11.39, P < 0.001] and a significant
interaction between Age and Hemisphere [F(1,145) = 11.94,
P < 0.001]. These results were similar after covarying total
for brain volume, showing significant Age [F(1,144) = 7.46,
P < 0.02] and Hemisphere [F(1,144) = 9.88, P < 0.002] effects, aswell as a significant Age by Hemisphere interaction [F(1,144) =12.18, P < 0.0006]. Factor scores from the third principal
component (~6% of the variance), only showed a main effect
of Sex both before [F(1,145) = 7.83, P < 0.006] and after brain
size correction [F(1,144) = 5.60, P < 0.02]. Finally, factor scores
from the fourth principal component (~4% of the variance)
Figure 1. Scree plots showing the total variance from principal components obtained from cortical gray matter concentration (top) and cortical thickness (bottom) measures foreach hemisphere.
Page 4 of 12 Cortical Thickness in First Episode Schizophrenia d Narr et al.
revealed main effects of Sex [F(1,145) = 3.87, P < 0.05] and Age
[F(1,145) = 6.90, P < 0.01] that remained significant after brain
size correction; Sex: F(1,144) = 6.99, P < 0.01; Age: F(1,144) =7.03, P < 0.009.
Cortical Thickness PCA Scores
Factor scores from the first principal component for cortical
gray matter thickness, accounting for 33% of the total variance,
showed main effects of Diagnosis [F(1,145) = 6.37, P < 0.01],
Sex [F(1,145) = 10.24, P < 0.001] and Age [F(1,145) = 6.97,
P < 0.009]. Effects of Diagnosis [F(1,144) = 7.22, P < 0.008] and
Age [F(1,144) = 7.27, P < 0.008] remained significant after
covarying for total brain volume. No interactions between the
predictor variable, Diagnosis, and any of the covariates were
observed. Figure 2 (bottom panel) shows factor scores from the
first PCA component plotted by age in groups defined by sex
and diagnosis. Factor scores from the second principal compon-
ent (~9% of the variance) showed main effects of Age only
[F(1,145) = 7.35, P < 0.008] that were also significant after brain
size correction [F(1,144) = 8.51, P < 0.004]. Third component
factor scores (~4% of the variance) showed a main effect of
Hemisphere [F(1,145) = 5.78, P < 0.02] that was no longer
significant after taking brain volume into account. Factor scores
from the fourth principal component (also ~4% of the variance)
showed main effects of Sex [F(1,145) = 9.49, P < 0.002] and Age
[F(1,145) = 4.09, P < 0.05], and a significant Hemisphere by
Diagnostic group interaction [F(1,145) = 4.37, P < 0.04]. The
Figure 2. Factor scores from the first principal components for gray matter concentration (top) and cortical thickness (bottom) plotted by age in groups defined by sex anddiagnosis.
Cerebral Cortex Page 5 of 12
same effects were significant after covarying for total brain
volume; Sex: F(1,144) = 6.06, P < 0.01; Age: F(1,144) = 4.10,
P < 0.04; Hemisphere by Diagnostic group, F(1,144) = 4.37,
P < 0.04.
Regional Effects of Intensity-based Gray MatterConcentration
To isolate regional differences in intensity-based gray matter
concentration across the cortex, we compared gray matter
concentration ratios at all cortical surface locations in 3-D.
Probability values, indexed in color, were mapped back onto an
averaged cortical surface model from the entire group at each
3-D point location. Probability values showing positive and
negative effects were mapped separately to determine
whether group differences reflect increased or decreased gray
matter concentration. Figure 3 shows statistical mapping
results for (i) comparisons between schizophrenia patients
and healthy subjects after covarying for sex (top row); (ii)
between groups defined by sex (second row); (iii) interactions
between sex and diagnosis (third row); and (ii) effects of
diagnosis mapped within male and female groups separately
(last row).
The top row of Figure 3 shows that first episode patients
possess significant decreases in intensity-based gray matter
concentration in dorsolateral prefrontal cortex, most promi-
nently in the middle frontal gyrus, and in the temporal lobe,
particularly the superior temporal gyrus bilaterally. Further
decreases are visible in inferior parietal regions, and in occipital
regions in the left hemisphere. No significant increases in
intensity-based gray matter concentration were observed in
schizophrenia patients compared with controls. The second
row shows regional increases in gray matter concentration in
superior parietal regions in females compared with males
(right). Males fail to show any significant regional increases in
gray matter concentration compared with females (left). Statis-
tical maps in the third row show that sex by diagnosis
interactions were absent for local gray matter concentration
measures as consistent with the PCA factor score comparisons.
Finally, in the last row, effects of diagnosis compared separately
within male (right) and female (left) groups show that de-
creases in intensity-based gray matter concentration are more
pronounced in the pre- and post-central gyrus in males,
although the spatial profiles possess many similarities between
males and females overall.
Regional Effects of Cortical Thickness
Statistical maps in Figure 4 show the same statistical compari-
sons described above, but include cortical thickness values
obtained at homologous cortical locations in 3-D as the de-
pendent measure. The top row of Figure 4 shows schizophrenia
effects after covarying for biological sex. Cortical thinning is
evident in dorsolateral prefrontal and lateral temporal cortices,
consistent with the pattern of results observed for gray matter
concentration (Fig. 3). Cortical thinning, however, appears
more spatially diffuse in the left hemisphere in temporal and
inferior parietal regions when compared with the regional gray
matter concentration results. No significant regional increases
in cortical thickness were observed in first episode patients (top
left). Overall, females possessed thicker cortices in parietal
regions (second row) even without brain size correction. Males,
however, exhibited thicker cortex in frontal regions proximal
to the interhemispheric fissure. The statistical maps in the third
row show interactions between sex and diagnosis: they suggest
that left anterior temporal and medial frontal regions are more
affected in female schizophrenia patients. In the last row, gray
matter thinning appears most prominent in temporal and
dorsolateral prefrontal regions in female patients compared
with female comparison subjects. Male patients, however,
appear to exhibit regional decreases in gray matter thickness
most prominently in the vicinity of the pre and postcentral
sulcus bilaterally, although some gray matter thinning is also
evident in temporal and frontal regions.
Associations between Intensity-based Gray MatterConcentration and Cortical Thickness
Pearson’s correlation coefficients showing relationships be-
tween factor scores from the first four principal components
for intensity-based cortical gray matter concentration and
thickness are presented in Table 2. Factor scores were highly
correlated for the same components in each hemisphere with
all probability values of <0.001. Figure 5 shows average cortical
gray matter thickness (top) and gray matter concentration
(middle) distributions across all subjects. Average cortical
thickness ranged between 2 and 4.5 mm, and intensity-based
gray matter concentration ratios ranged between 0.25 and 0.65
across the cortex. Average and variability profiles for both
measures were similar within each group (figures not shown).
The bottom panel of Figure 5 shows the statistical relationships
between gray matter concentration and cortical thickness at
Table 1Means and standard deviations for global tissue volumes (cm3) before and after brain size correction in groups defined by sex and diagnosis
Men Women
Patients with schizophrenia(n 5 51)
Comparison subjects(n 5 37)
Patients withschizophrenia (n 5 21)
Comparison subjects(n 5 41)
Brain volumea 1255.6 ± 122.9 1245.6 ± 93.43 1107.8 ± 133.9 1137.1 ± 77.1CSF volumea,b,c 159.67 ± 27.58 150.07 ± 29.17 140.08 ± 28.87 135.64 ± 24.08Corrected CSFb,c 152.62 ± 23.80 144.30 ± 25.84 151.78 ± 22.23 143.63 ± 20.64Gray matter volumea,b,c 644.23 ± 68.48 649.06 ± 73.92 571.29 ± 60.98 601.49 ± 45.86Corrected grayb,c 617.78 ± 31.96 627.42 ± 32.06 615.17 ± 25.95 631.39 ± 20.64White matter volumea,c 451.78 ± 58.89 446.47 ± 65.10 396.49 ± 64.05 400.06 ± 40.76Corrected whitec 429.69 ± 33.67 428.38 ± 32.77 433.15 ± 24.15 425.08 ± 28.07
Corrected 5 residualized for brain volume and added to the mean volume for each tissue compartment.aSignificant effects of sex.bSignificant effects of diagnosis.cSignificant effects of age.
Page 6 of 12 Cortical Thickness in First Episode Schizophrenia d Narr et al.
each cortical location in 3-D. Cortical gray matter indices were
significantly (positively) correlated across all cortical locations
with the exception of the temporal poles.
Discussion
Total Brain and Brain Tissue Volumes
Patients experiencing their first episode of schizophrenia failed
to show significant differences in brain volume compared with
healthy comparison subjects. On average male patients pos-
sessed slightly larger mean brain volumes than male controls
(Table 1). These mean increases, however, were attributable to
the significantly larger CSF volumes observed across both male
and female schizophrenia patients. Importantly, patients ex-
hibited significant reductions in global gray matter, with respect
to comparison subjects, that were more pronounced after
taking total brain volume into account. No diagnostic differ-
ences were observed for white matter tissue volumes and no
interactions between diagnostic group and sex or age were
detected for any brain tissue compartment. The presence of
global CSF increases and gray matter decreases match many
previous observations in schizophrenia (Lawrie and Abukmeil,
1998; Harrison, 1999; Wright et al., 2000; Shenton et al., 2001).
Moreover, these abnormalities have been identified in first
episode patients (Lim et al., 1996b; Zipursky et al., 1998). Many
previous studies, however, have failed to detect significant
global differences in gray matter in schizophrenia (Ward et al.,
1996; Lawrie and Abukmeil, 1998). Our findings thus illustrate
the importance of using large sample sizes to detect small
differences in brain tissue volumes as appear present in indi-
viduals with schizophrenia. Although some evidence suggests
that gray matter loss in schizophrenia is progressive, at least in
the early stages of the illness and may influenced by anti-
psychotic medication exposure (Cahn et al., 2002), our data
supports the idea that gray matter abnormalities are present
near disease onset in patients with little or no prior medication
treatment.
PCA Analyses of Cortical Gray Matter Changes
PCA analyses of intensity-based gray matter concentration and
cortical thickness values obtained from homologous cortical
regions, confirm the presence of cortical (as opposed to whole
brain) gray matter changes in first episode schizophrenia. The
first principal components, accounting for 27--33% of the total
variance for both cortical gray matter indices (concentration
and thickness) sampled at high resolution across the entire
cortex, showed significant disease-related effects. Although
cortical thickness values represent the distance between the
cortical white--gray matter boundary and the external gray
matter--CSF boundary, and gray matter concentration measures
reflect the proportion of gray matter within the cortical mantle
with respect to other tissue types, results showed that these
measures are highly correlated. That is, intensity-based gray
matter concentration and cortical thickness values appear to
index the same or similar disease-related processes both at the
global (i.e. when measures are reduced using PCA) and at the
Figure 3. Statistical maps showing significant regional differences in cortical gray matter concentration (i) in patients with first episode schizophrenia (sz) compared with healthysubjects (nc) after covarying for sex (top row); (ii) between male and female subjects across diagnostic groups (second row); (iii) for interactions between sex and diagnosis (thirdrow); and (iv) between diagnostic groups with in males (right) and females (left). Probability values, indexed in color, show positive and negative effects.
Cerebral Cortex Page 7 of 12
regional level (Table 2, Fig. 5). Differences in cortical gray
matter concentration reduced using PCA, however, were not
detected previously in chronic schizophrenia even in the
presence of significant extra-cortical (sulcal and subarachnoid)
CSF increases (Narr et al., 2003). The sample size of the prior
investigation, however, was only one-third of the current
sample size. Thus, in the presence of small effect sizes, global
intensity-based gray matter concentration findings may have
remained undetected.
Regional Effects of Intensity-Based Gray MatterConcentration
Some cortical regions, such as lateral and medial temporal
cortices and, to a lesser extent, frontal and parietal cortices,
appear most implicated in the structural neuropathology of
schizophrenia (Lawrie and Abukmeil, 1998; Shenton et al.,
2001). Results from volumetric studies (Goldstein et al., 1999;
Gur et al., 2000; Sanfilipo et al., 2000) and investigations of gray
matter concentration throughout the brain using VBM (Wright
et al., 1999a; Sigmundsson et al., 2001; Wilke et al., 2001; Ananth
et al., 2002), however, frequently disagree concerning the
spatial localization of cortical gray matter changes. In our
investigation, cortical gray matter concentration and thickness
measures showed similar regional effects when comparisons
were performed at thousands of homologous cortical locations
in 3-D. Regional changes in intensity-based gray matter concen-
tration showed that patients exhibit decreased cortical gray
matter proportions in heteromodal association areas, particu-
larly in superior temporal and lateral prefrontal cortices (Fig. 3).
Reduced gray matter proportions were also apparent in the
inferior parietal lobules bilaterally and in left hemisphere
occipital regions. These spatial patterns appeared similar when
comparing female diagnostic groups separately. However, com-
parisons of men with schizophrenia to healthy male controls
also showed reductions of gray matter concentration in and
around the pre and postcentral gyri. In spite of some differences
in the spatial profiles of gray matter reductions within male and
female groups, significant interactions between sex and diag-
nosis were not observed at the regional (or global) level. Thus,
we do not believe the independent interpretation of these gray
matter maps among men alone merits separate interpretation,
but could serve as a focus for a replication study to determine
the generality of this finding.
Uncorrected statistical maps of regional intensity-based
gray matter concentration showed similar regional effects
in our earlier study of chronic schizophrenia patients and
Figure 4. Statistical maps showing significant regional differences in cortical thickness (i) in patients with first episode schizophrenia (sz) compared with healthy subjects (nc) aftercovarying for sex (top row); (ii) between male and female subjects across diagnostic groups (second row); (iii) for interactions between sex and diagnosis (third row); and (iv)between diagnostic groups with in males (right) and females (left). Probability values, indexed in color, show positive and negative effects.
Table 2Correlations between PCA factor scores from gray matter concentration and thickness measures
Gray matter concentration factor scores
PCA 1 PCA 2 PCA 3 PCA 4
Cortical thickness factor scores Left Right Left Right Left Right Left Right
Left 0.83 0.81 0.71 0.73 0.62 0.57 0.40 0.37Right 0.81 0.84 0.72 0.75 0.63 0.64 0.26 0.46
Probability values associated with the correlation coefficients above range between P\ 0.00001
and P\ 0.001.
Page 8 of 12 Cortical Thickness in First Episode Schizophrenia d Narr et al.
demographically similar healthy comparison subjects, even
though cortical gray matter concentration values reduced using
PCA were not significant (Narr et al., 2003). Specifically, re-
gional reductions in gray matter concentration were distributed
through heteromodal association areas and within the pre- and
post-central gyrus, although they were less notable in the super-
ior temporal cortex. Extra-cortical CSF increases, however,
were pronounced surrounding temporal regions. Reciprocal
relationships between gray matter decreases and extra-cortical
CSF increases have been shown to occur during normal aging
(Jernigan et al., 1991; Coffey et al., 1998; Courchesne et al.,
2000). Thus, it is possible that regional increases in extra-
cortical CSF may serve to predict more subtle regional reduc-
tions in cortical gray matter. Our findings are also compatible
with at least two VBM studies of first episode schizophrenia (Job
et al., 2002; Kubicki et al., 2002). Specifically, Kubicki et al.
(2002) showed differences in intensity-based gray matter con-
centrations within the superior temporal gyrus and parietal
lobe. Job et al. (2002) similarly observed gray matter concen-
tration reductions in the left middle temporal and postcentral
gyri in first episode patients compared with controls.
Regional Effects of Gray Matter Thickness
Our statistical maps of cortical thickness showed similar spatial
profiles as those for intensity-based cortical gray matter con-
centration. Patients with first episode schizophrenia exhibited
cortical thinning in heteromodal lateral prefrontal and temporal
cortices, as well as in parietal and occipital regions (Fig. 4).
Comparisons between exclusively female diagnostic groups
showed similar regional effects. Males, however, showed thin-
ning within the pre and postcentral gyrus regions that were
largely above the threshold of statistical significance in female
patients, while regional effects appeared more pronounced in
temporal regions in female patients. Interactions between sex
and diagnostic group showed that female patients also possess
some cortical thinning in anterior temporal regions and adja-
cent to the interhemispheric fissure (medial frontal) that did
not appear present in male patients. Sex by diagnosis inter-
actions were not observed for cortical gray matter concentration.
Our cortical thickness findings are in line with results from an
earlier imaging study of cortical thickness in chronic schizo-
phrenia (Kuperberg et al., 2003). Using a similar methodo-
logical approach, Kuperberg et al. (2003) measured cortical
thickness in twelve cortical regions in 33 schizophrenia
patients compared with 32 demographically similar healthy
subjects. Cortical thickness was also approximated across
cerebral cortex after smoothing with a kernel of radius 60 mm.
Results showed that cortical thinning was most prominent in
prefrontal and temporal cortices. However, cortical thinning
was also observed in orbitofrontal and inferior frontal regions,
local effects that were marginal or absent in our study. Cortical
thinning was also identified in right medial frontal cortices,
a region that was not examined in our investigation. Another
study examined prefrontal cortical thickness in first episode
schizophrenia (Wiegand et al., 2004), where cortical thickness
was defined as the shortest distance from the white-gray matter
boundary to voxels on the 3-D cortical surface. Significant
reductions in prefrontal gray matter volume were observed in
first episode patients (n = 17) compared with healthy subjects
(n = 17), but reductions in cortical thickness averaged across
the region were not detected, even though thickness and
volume measures were positively correlated. These results
may suggest cortical thinning was below the threshold of
significance for the entire prefrontal lobe, and that more
regional effects may have remained undetected.
A third study used a slightly different approach to examine
differences in cortical thickness between early and adolescent
onset schizophrenia patients compared with healthy compari-
son subjects (White et al., 2003). Cortical thickness was
estimated by creating an iso-surface from the midpoint of
voxels segmenting ‘purely’ as gray matter within the cortical
ribbon. Cortical thickness was then defined as the minimum
distance from the iso-surface to voxels segmenting 50% as gray
matter and 50% as white matter and these distances were
doubled to approximate actual thickness. Cortical thickness
was then compared for gyral and sulcal regions separately
collapsed across the four lobes. Results showed that the
thickness of the cortex was reduced in sulcal regions in the
frontal, parietal and temporal lobes and reduced in gyral regions
only in the temporal lobes in patients compared with controls.
These findings are partially compatible with our results, al-
though our statistical maps did not reveal pronounced effects in
the sulcal folds.
Sex Effects
Males exhibited larger total brain volumes and individual brain
tissue volumes compared with females, as universally documen-
ted in the normative literature. Factor scores from PCA analyses
also showed main effects of sex for both cortical gray matter
indices. Sex effects, however, were no longer significant after
covarying for total brain volume, with the exception of com-
parisons between factor scores from the third and fourth
Figure 5. Maps showing average cortical thickness (top) and average gray matterconcentration distributions across all subjects (middle) as indexed by the colorbar.Relationships between cortical thickness and gray matter concentration are shown inthe bottom row, where correlation coefficients are indexed in color.
Cerebral Cortex Page 9 of 12
principal component for intensity-based gray matter concen-
tration values. These results suggest that there are some sex
differences in cortical gray matter that are independent of brain
size. Importantly, the removal of brain size differences may also
serve to obscure potential sex effects since sex and brain size
are strongly associated. Statistical maps of regional effects of sex
showed similar patterns as reported by other groups (Nopoulos
et al., 2000; Good et al., 2001). That is, although males possess
larger brain tissue volumes than females, females show some
focal increases in gray matter concentration compared with
males in absolute terms. These differences, measured across
both diagnostic groups, were present in posterior parietal
regions (Nopoulos et al., 2000; Good et al., 2001). Statistical
maps showing sex differences in cortical thickness were similar
to those observed for gray matter concentration values. How-
ever, small increases in cortical thickness were shown in
anterior medial frontal regions and towards the temporal poles
in male compared with female subjects whereas male subjects
showed no local increases in gray matter concentration.
Age and Hemispheric Effects
Significant effects of age were also observed for the three major
tissue compartments. Subtle gray matter decreases and white
matter and CSF increases occurred with age, as consistent with
previous findings in this age range (Coffey et al., 1998; Magnotta
et al., 1999; Symonds et al., 1999; Good et al., 2001). Diagnostic
groups showed similar age effects for all brain tissue compart-
ments and for PCA factor scores from the first principal
components of both cortical gray matter indices, irrespective
of brain size corrections. These results demonstrate that age is
a strong predictor of cortical gray matter differences between
individuals even in early adulthood. Previously, whole brain gray
matter volumes and regional changes in intensity-based gray
matter concentration were shown to occur prematurely in male
patients with chronic schizophrenia (Narr et al., 2003). That is,
male patients showed early gray matter reductions that re-
mained relatively static from disease onset into the fifth decade,
while demographically similar healthy comparison subjects and
female patients showed a gradual decline in gray matter volume
over the same time period. These results do not contradict our
current findings given that our study groups were of a relatively
narrow age range and on average a decade younger that the
chronic schizophrenia patients previously examined. Further-
more, differences in aging effects between groups were only
examined cross-sectionally in the chronic schizophrenia study,
and remain to be confirmed longitudinally. Hemispheric differ-
ences between diagnostic groups were only detected in factor
scores from the fourth PCA component cortical thickness
values. Statistical maps, however, show some small hemispheric
differences when comparisons of cortical thickness and con-
centration are made locally.
Methodological Limitations
Although intensity-based gray matter concentration and thick-
ness measures are strongly associated over the majority of the
cortex, these measures were not significantly correlated in the
temporal poles and in medial frontal regions (Fig. 5). These
small discrepancies in results illustrate some important meth-
odological differences between the two measures. Specifically,
gray matter concentration measures may be more susceptible
to artifacts stemming from differences in the curvature of the
cortical surface where increased curvature may cause less gray
matter to be sampled within the kernel of a fixed radius.
Interestingly, the temporal poles and interhemispheric folds
are among the most curved regions of the cortex perhaps
accounting for the lack of significant correlations in these
regions only. Intensity-based concentration measures may in
part also reflect differences in the surrounding tissue. For
example, prior data suggest that disease effects are larger when
CSF to whole brain ratios are examined compared with when
brain tissue volumes are examined alone (Gur et al., 1991;
Woods et al., 1996; Cannon et al., 1998). This may also apply at
the regional level. The gray matter concentration ratio may also
be influenced by sulcal widening as has been previously
documented in schizophrenia (Shenton et al., 2001). Import-
antly, none of these potential confounds are associated with
the cortical thickness measure. However, both measures may
be susceptible to partial volume effects given that gray matter
thickness and concentration are estimated from tissue seg-
mented brain volumes.
Conclusion
Cortical thickness and intensity-based gray matter concentra-
tion ratios produce similar results suggesting they index the
same pathophysiological processes in schizophrenia. Local
reductions in cortical thickness and gray matter concentration
appear to be present at disease onset implying the involvement
of disturbed neurodevelopmental mechanisms. Cortical thin-
ning and reduced intensity-based gray matter concentration are
most notable in frontal, temporal and parietal association
cortices that have been linked with functional disturbances in
schizophrenia. That is, widespread deficits, affecting the thick-
ness of the cortical mantle over broad areas of heteromodal
association cortex, may underlie complex deficits in attentional
regulation, executive deficits and deficits in learning/memory
functions that appear most prominent in schizophrenia (e.g.
Seidman et al., 1994; Baare et al., 1999; Harrison, 1999; Bilder
et al., 2000; Pearlson, 2000. Interestingly, motor deficits have
also been identified in first episode schizophrenia that appear at
least partially independent of medication treatments, perhaps
associated with gray matter thinning in primary motor areas
particularly in male patients (Bilder et al., 2000). The direct
relationships between neuropsychological measures and cor-
tical thickness in schizophrenia, however, remain to be assessed
empirically. Earlier post-mortem studies show small reductions
in cortical thickness in patients in the presence of increased
neuronal packing density and smaller neuronal somal sizes
(Selemon et al., 1995, 1998; Rajkowska, 1997). Neuropil reduc-
tions and smaller cell sizes, rather than neuronal loss, may thus
be the basis for cortical thinning in schizophrenia and account
for disturbances in neurotransmission.
Notes
This work was generously supported by research grants from the
National Center for Research Resources (2 P41 RR13642, 2 M01
RR00865 and R21 RR19771), the National Institute of Mental Health
(RO1-MH-60374) the National Library of Medicine (5 R01 LM05639),
the National Institute for Biomedical Imaging and Bioengineering (EB
001561), a NIMH NRSA Training Grant (MH14584) and a NARSAD
Young Investigator Award for which K.L.N. is the 2003 Daniel X.
Freedman recipient.
Address correspondence to Dr Arthur W. Toga, Laboratory of Neuro
Imaging, Department of Neurology, Division of Brain Mapping, UCLA
Page 10 of 12 Cortical Thickness in First Episode Schizophrenia d Narr et al.
School of Medicine, 710 Westwood Plaza, Los Angeles, CA 90095-1769,
USA. Email: [email protected].
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