www.elsevier.com/locate/ynimg

NeuroImage 26 (2005) 941 – 951

Functional MRI BOLD response to Tower of London performance of

first-episode schizophrenia patients using cortical pattern matching

Paul E. Rasser,a,b,c Patrick Johnston,a,b Jim Lagopoulos,a,c Philip B. Ward,a,c,* Ulrich Schall,a,b

Renate Thienel,a,d Stefan Bender,a,d Arthur W. Toga,e and Paul M. Thompsona,e

aNeuroscience Institute of Schizophrenia and Allied Disorders (NISAD), AustraliabCentre for Mental Health Studies, University of Newcastle and Hunter Medical Research Institute (HMRI), AustraliacSchool of Psychiatry, University of New South Wales, AustraliadClinic for Psychiatry and Psychotherapy, University of Duisburg-Essen, GermanyeLaboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90024, USA

Received 8 December 2003; revised 10 November 2004; accepted 29 November 2004

Available online 15 April 2005

Due to its three-dimensional folding pattern, the human neocortex

poses a challenge for accurate co-registration of grouped functional

brain imaging data. The present study addressed this problem by

employing three-dimensional continuum-mechanical image-warping

techniques to derive average anatomical representations for co-

registration of functional magnetic resonance brain imaging data

obtained from 10 male first-episode schizophrenia patients and 10 age-

matched male healthy volunteers while they performed a version of the

Tower of London task. This novel technique produced an equivalent

representation of blood oxygenation level dependent (BOLD) response

across hemispheres, cortical regions, and groups, respectively, when

compared to intensity average co-registration, using a deformable

Brodmann area atlas as anatomical reference. Somewhat closer

association of Brodmann area boundaries with primary visual and

auditory areas was evident using the gyral pattern average model.

Statistically-thresholded BOLD cluster data confirmed predominantly

bilateral prefrontal and parietal, right frontal and dorsolateral

prefrontal, and left occipital activation in healthy subjects, while

patients’ hemispheric dominance pattern was diminished or reversed,

particularly decreasing cortical BOLD response with increasing task

difficulty in the right superior temporal gyrus. Reduced regional gray

matter thickness correlated with reduced left-hemispheric prefrontal/

frontal and bilateral parietal BOLD activation in patients. This is the

first study demonstrating that reduction of regional gray matter in

first-episode schizophrenia patients is associated with impaired brain

function when performing the Tower of London task, and supports

1053-8119/$ - see front matter D 2005 Published by Elsevier Inc.

doi:10.1016/j.neuroimage.2004.11.054

* Corresponding author. Schizophrenia Research Unit, Don Everett

Building, Liverpool Hospital, Locked Bag 7103, Liverpool BC 1871,

Australia. Fax: +61 2 9828 6181.

E-mail address: p.ward@unsw.edu.au (P.B. Ward).

Available online on ScienceDirect (www.sciencedirect.com).

previous findings of impaired executive attention and working memory

in schizophrenia.

D 2005 Published by Elsevier Inc.

Keywords: Structural magnetic resonance imaging; Functional magnetic

resonance imaging; Cortex; Deformable Brodmann area atlas; Three-

dimensional continuum-mechanical image-warping; Cortical pattern

matching; First-episode schizophrenia; Tower of London; Planning;

Executive attention; Working memory

Introduction

Functional brain imaging techniques, such as functional

magnetic resonance imaging (fMRI) and positron emission

tomography (PET), provide detailed spatial information about brain

activation. This information is increasingly used to generate maps

of normal brain function as a reference for abnormal brain function

in various neuropsychiatric conditions. While co-registration of

changes in blood oxygenation levels or blood flow rates onto

structural MRI scans of individual brains can be achieved with high

levels of accuracy, grouping these data for quantitative comparisons

(e.g., between diagnostic groups) poses a major methodological

challenge due to the inter-individual variability of regional brain

morphology (Brett et al., 2002). Some cortical areas, however, such

as the primary motor, visual, and auditory cortex, are defined by

their relationship to distinct anatomical landmarks such as central

and calcarine sulci and Heschl’s gyrus which are relatively invariant

in position and configuration across individuals (Rademacher et al.,

1993), while other areas, such as the prefrontal cortex, are highly

variable across subjects thus making it difficult to choose mean-

ingful anatomical labels (Rajkowska and Goldman-Rakic, 1995).

For these regions of the neocortex, there is also little agreement on

P.E. Rasser et al. / NeuroImage 26 (2005) 941–951942

cytoarchitectonic boundaries and their relationship to sulcal and

functional anatomy (Amunts et al., 2000).

At present, most analytical approaches are based on template or

normalization techniques, which provide an approximation of

spatial information for grouped data with reference to a coordinate

system (e.g., the brain atlas of Talairach and Tournoux, 1988).

However, small changes of cortical stereotactic coordinates can, in

fact, represent a relatively large change in distance within the

cortical surface given the three-dimensional folding pattern of

cortex morphology (e.g., Fischl et al., 1999; Van Essen et al.,

2000). The same limitations apply when registering stereotactic

coordinates onto cytoarchitectonically-defined regions such as the

Brodmann areas (Brodmann, 1909). The interpretation of such data

can be further distorted by subtle brain pathology that is not

sufficiently corrected by the spatial normalization procedures,

potentially adding a systematic co-registration error to group

comparisons of brain activation.

The present study addresses some of these limitations by

employing three-dimensional continuum-mechanical image-

warping techniques to derive well-resolved average representa-

tions of anatomy for the co-registration of functional brain

imaging data. A key element of this strategy is the application

of cortical pattern matching methodologies that permit aggregation

of imaging data sets in the same anatomical reference locations

across subjects, explicitly modeling and adjusting for individual

differences in the cortical folding pattern as well as in overall brain

size (Thompson et al., 1997, 2000, 2003). Many traditional spatial

mapping techniques normalize data using only linear or global

(e.g., Woods et al., 1993) or piece-wise linear transformation into

stereotactic space, using the anterior and posterior commissures,

and a small number of points on the cortical surface defined with

reference to the AC–PC line, as fixed points (Talairach and

Tournoux, 1988). Such a global transformation is highly insensi-

tive to individual differences in cortical patterning.

By contrast, the cortical pattern matching method differs from

traditional spatial normalization techniques by explicitly model-

ing major cortical landmarks, and through deforming the

individual’s cortical surface, creates the best fit to an average

cortical pattern model. When comparing measures of gray matter

(Thompson et al., 2003) and functional activation across subjects,

statistical power is increased by explicitly adjusting for cortical

patterning differences across individuals. Recent research shows

that patients with schizophrenia show greater individual differ-

ences in the locations of major cortical surface than healthy

controls (Narr et al., 2001). Thus, this method may be particularly

relevant in avoiding systematic biases when comparing gray

matter or functional measures in patients with neuropsychiatric

conditions to healthy control subjects.

Cortical pattern matching has been applied in the current study

to compare the spatial properties of brain activation of first-episode

schizophrenia patients with that of matched healthy control

subjects when performing the Tower of London (TOL) task. It

was hypothesized that the gyral pattern-averaged model of the

cortex will improve spatial co-registration of brain activation

particularly in those regions of the cortex, which have a close

association of cytoarchitecture and function (i.e., primary sensory

projection areas).

The TOL is an adaptation of the Tower of Hanoi and consists

of moving colored balls within a limited number of moves in

order to achieve a given goal configuration. Previous studies

reported poor TOL performance in patients with frontal brain

lesions (e.g., Owen et al., 1990; Pantelis et al., 1997; Shallice,

1982) or frontal lobe dementia (Carlin et al., 2000), Parkinson’s

disease (e.g., Lewis et al., 2003; Morris et al., 1988; Owen et al.,

1992; Robbins et al., 1994), depression (e.g., Purcell et al., 1997),

and schizophrenia (e.g., Morris et al., 1995; Pantelis et al., 1997;

Schall et al., 1998).

Early activation studies using single-photon emission compu-

terized tomography (SPECT) reported that TOL performance is

associated with increased activation of the frontal cortex in healthy

subjects (Morris et al., 1993). Longer planning times and fewer

moves to complete a problem were associated with significantly

higher regional cerebral blood flow (rCBF) in the left prefrontal

cortex whereas execution time was negatively correlated with both

left and right prefrontal rCBF. Subsequent studies (Baker et al.,

1996; Owen et al., 1996) reported additional task-related increase of

rCBF in pre-motor areas, the visual cortex, thalamus, and caudate

nucleus.

Dagher et al. (1999) compared rCBF dependent on task

complexity as defined by the number of moves required to solve

a TOL problem (i.e., correlational analysis) with rCBF contrasts of

Fon_ versus Foff _ task performance (i.e., categorical analysis).

Activated brain areas in which increases of rCBF did not correlate

with task complexity were regions belonging to the dorsal stream

of visual input processing (i.e., visual cortical and posterior parietal

cortical areas) and regions involved in the execution and

sequencing of arm movements (e.g., cerebellum, primary motor

cortex, and supplementary motor area). Brain regions where levels

of rCBF correlated with task complexity included the dorsolateral

prefrontal cortex, the lateral pre-motor cortex, the rostral anterior

cingulate cortex, and the dorsal caudate nucleus.

A similar regression model–with number of moves required to

solve a problem as the independent variable and blood oxygenation

level-dependent (BOLD) signal changes as the dependent variable–

served as the functional MR measure in the present study (e.g.,

Schall et al., 2003; Van den Heuvel et al., 2003). So far, however,

only a limited number of reports have been published with TOL as

an activation task in schizophrenia. For instance, Andreasen et al.

(1992) reported decreased rCBF (when using [133Xe]) in the left

mesiofrontal cortex and cingulate in drug-naıve and neuroleptic

withdrawn schizophrenia patients that was associated with the

severity of frontal brain dysfunction as expressed by negative

symptoms.

While neuropsychological data suggest impaired TOL perform-

ance already at an early stage of the disorder (Thienel et al., 2000),

corresponding functional brain imaging studies are lacking. Such

data are of particular interest since subtle structural decline of gray

matter in those cortical areas–which are also subserving TOL

processing–have been reported at very early stages of the disease

(Pantelis et al., 2003). In early onset cases, the chronologically

earliest deficits were found in parietal brain regions concerned with

visuo-spatial and associative thinking, where adult deficits are

known to be mediated by environmental (non-genetic) factors

(Cannon et al., 2002). Over 5 years, these deficits progressed

anteriorly into temporal lobes, engulfing sensorimotor cortices,

executive and cognitive function associated dorsolateral prefrontal

cortices, and into the frontal eye fields. Faster loss rates of gray

matter in the frontal cortex were strongly correlated with the

severity of negative symptoms. Statistical maps on the cortical

surface further revealed regionally specific linkages between gray

matter losses and several IQ sub-tests on information processing,

comprehension, and vocabulary. These findings suggest an overall

P.E. Rasser et al. / NeuroImage 26 (2005) 941–951 943

deterioration of global functioning and cognitive decline, consis-

tent with progressive structural deterioration. These emerging

dynamic patterns were controlled for medication and IQ effects,

replicated in independent groups of males and females, and charted

in individuals and groups (Thompson et al., 2001).

The present study directly assesses function–structure relation-

ships by mapping task difficulty-dependent BOLD changes as a

function of cortical gray matter thickness. We hypothesized that the

extent of BOLD response–and, by extension, the performance on

the task– is partially dependent on the integrity of regions of gray

matter that are subserving TOL problem solving performance (i.e.,

prefrontal, frontal, and parietal cortex).

Materials and methods

The current study was conducted as part of the Brain Atlasing

Initiative of the Neuroscience Institute of Schizophrenia and

Allied Disorders (NISAD). Ethics approval was granted by the

human research ethics committees of the contributing institutions:

the University of Newcastle Human Research Ethics Committee,

the Hunter Area Health Research Ethics Committee, the Univer-

sity of New South Wales Ethics Research Committee, the South

Western Sydney Area Health Service Human Research Ethics

Committee, and the University of Duisburg-Essen Research Ethics

Committee.

Subjects and task

Schizophrenia was diagnosed according to DSM-IV criteria

with less than 2 years duration of illness and tested in remission on

maintenance antipsychotic medication (i.e., olanzapine, risperi-

done, or quetiapine). Healthy control subjects were matched for

age. All participants were right-handed males in order to avoid

gender by hemispheric dominance confounds. They were trained

on the TOL task prior to scanning in order to achieve a minimum

of 80% correct responses to ensure an equivalent level of task

performance of all participants. All subjects were also screened and

examined for general MR exclusion criteria (e.g., ferromagnetic

body objects, etc.) including a history of anxiety disorder and in

particular claustrophobia. They were also psychiatrically assessed

immediately prior to scanning to exclude individuals who were

experiencing an acute psychosis or were meeting any other of our

exclusion criteria (e.g., illicit substance use) that may have

emerged since recruitment for our study. Despite this strict

screening protocol, two patients and one control subject felt

discomfort while in the scanner and the session was aborted.

Another scan of one patient was excluded from analysis due to

movement artifacts. Data of 10 first-episode schizophrenia patients

with a mean age of 19.8 years (range 17–23 years) and 10 healthy

control subjects with a mean age of 20.1 years (range 18–21 years)

constitute the sample of the current study.

While lying in the MR scanner, each subject was presented

with TOL images using mirrors in the head coil to view a back-

projected video display. The upper half of the image contained a

goal configuration of three different colored balls on three pegs.

The subject was asked to determine the minimum number of

moves required to reach this goal configuration, given the

distribution of balls in the lower half of the image. Problems

involving 1 to 7 moves (Factive_) were presented along with a

baseline condition in which the upper and lower halves of the

image were identical (Fzero move_). After viewing the images for

30 s, the subject was asked to verbalize the required number of

moves. fMRI data were obtained for 21 problems, presented in 3

consecutive sequences consisting of 7 problems. Each sequence

commenced and ended with a Fzero move_ problem and

alternated between Fzero move_ and Factive_ problems (see Schall

et al., 2003 for further details and methodological cross

validations).

Structural and functional MRI acquisition

Structural and functional MR data were acquired using either a

Magnetom Vision 1.5-T MRI scanner (John Hunter Hospital,

Newcastle), a 1.5-T GE Signa LX scanner (St George MRI,

Kogarah), or a Siemens Sonata, 1.5-T MRI scanner (University

Clinic, Essen). Patients and control subjects were pair-wise age

matched at each site. For each subject, high-resolution structuralMR

data were collected with approximate dimensions of 164 � 256 �256 with each voxel being approximately 1.0 � 1.0 � 1.0 mm3

using a 3D MPRAGE protocol with TR = 9.7 ms, TE = 4 ms, and

flip angle = 12-. Subsequently, T2-weighted sequences were

collected during each of the 7 TOL problems using a 64 by 64

matrix to acquire 16 axial slices (TR = 0.6 s; TE = 70 ms; flip

angle = 90-; 6.25 � 6.25 � 8 mm in-plane resolution; each voxel

being 6.25 � 6.25 � 8 mm3) resulting in 70 volumes per run

(covering total brain volume). Each subject performed 3 sequen-

ces, leading to a total of 210 functional volumes per subject.

Processing of MR data

Each subject’s structural MR data were aligned with the

ICBM53 template (Collins et al., 1994) in order to reduce

individual proportional differences across subjects followed by

an intensity correction to reduce scanner inhomogeneity due to

radio frequency bias (Sled et al., 1998). A tissue classification (i.e.,

white matter, gray matter, CSF, and space surrounding the head)

for each subject was performed using a nearest neighbor Gaussian

distribution model that results in a discrete 4-parameter model of

the structure (Thompson et al., 2001).

Cortical surface modeling

To compare the BOLD activation data using two different

structural methods (i.e., affine registration and cortical pattern

matching), an intensity average (IA) model and a gyral pattern

average (GPA) model of cerebral cortex were developed. For the

IA model of cerebral cortex, the aligned individual MR images

were mean normalized and then intensity averaged for all subjects.

A three-dimensional model of the cerebral cortex was then

extracted (Thompson et al., 1997). For the GPA model, using the

masked MR data of the cerebrum, three-dimensional surface

models of the cerebral cortex were extracted for each subject.

Seventeen sulci were identified on each hemisphere and traced

onto each subject’s cortical surface model. Six control lines (three-

dimensional curves) mapping the midline hemispheric boundaries

at the interhemispheric margin were also identified and traced onto

the cortical surface model, giving 23 lines for each hemisphere for

each subject (Sowell et al., 2003; Thompson et al., 1997). Each of

the sulci and control lines identified for all subjects were then

geometrically averaged and used as the target for the alignment of

each individual set of sulci and control lines (Thompson et al.,

P.E. Rasser et al. / NeuroImage 26 (2005) 941–951944

2000). By computing the deformation that elastically transforms

one cortex into alignment with the geometrically averaged target,

the relationship between the voxels of each individual subject data

set (structural or functional) and the vertices on the average (GPA)

model is maintained (Thompson et al., 2000, 2003).

Deformable Brodmann area atlas

To localize the functional activation for both the IA and GPA

models, the Brodmann areas were used. From the right brain

hemisphere of the Montreal Neurological Institute intensity-

averaged single-subject MRI atlas (MNI colin27; http://

www.mrc-cbu.cam.ac.uk/Imaging/mnispace.html), an sMRI was

generated with two identical hemispheres (FcolinRR_). This

enabled the mapping of the Brodmann areas described on one

hemisphere to be reflected onto the other. (The classical Brodmann

maps are plotted on only one hemisphere as they are thought to

have a consistent relation to the gyral anatomy of each hemi-

sphere.) From the colinRR sMRI, a three-dimensional model of the

cerebral cortex was extracted (Thompson et al., 1997) and the

Brodmann areas, as described by the Caret package (http://

brainmap.wustl.edu/caret), represented onto its surface. As the

colinRR cerebral cortex model and the IA model were in the

same space, the Brodmann areas were applied to the surface of

Fig. 1. Functional magnetic resonance imaging data of 10 first-episode schizophren

subjects (CON; B and D). Views from top to bottom: frontal, superior, left lateral,

mapped on to the cortical surface for reference. (B–E) Task difficulty-dependen

thresholded at P < 0.05 [z = T3.88] and corrected for multiple comparisons) for con

(B and C) and the gyral pattern averaged model (GPA) of the brain surface (D an

subjects minus schizophrenia subjects indicate a reduced BOLD response in pati

gyrus, left occipital lobe, left supramarginalis gyrus and left opercularis area.

the IA model. For the GPA model however, the Brodmann areas

were deformed using cortical pattern matching to the GPA

model.

Cortical thickness

From the gray matter segmented maps, the cortical gray matter

thickness was calculated. First, the data sets were supersampled

and voxel dimensions were reduced to one-third of their original

size. Then, the cortical thickness was determined by starting from

the white matter/gray matter interface and expanding out a map of

three-dimensional distance from the white/gray interface towards

the external cortical surface. The mean values of cortical gray

matter thickness at each vertex of each subject’s cortical surface

model were determined using a kernel of radius 15 mm. This local

filtering was performed to increase the signal-to-noise ratio. Group

differences in cortical thickness were examined using the point-

biserial correlation coefficient (Welkowitz et al., 1972) with

patients = 1 and controls = 0.

Functional MR data

The 210 fMRI volumes for each subject (10 per 7 TOL

problems * 3 runs) were motion corrected in SPM99. A two-step

ia patients (SCZ; C and E) and 10 age- and gender-matched healthy control

right lateral, posterior, and inferior. (A) Deformable Brodmann boundaries

t BOLD contrasts when performing the Tower of London task (critically

trol subjects and patients co-registered on the intensity averaged (IA) model

d E). (F) BOLD subtraction z-score maps (GPA model) of healthy control

ents of the right superior frontal gyrus, right superior and middle temporal

Table 1

Clusters (N > 20 units critically thresholded at P < 0.05 and corrected for multiple comparisons) of significant positive BOLD response dependent on task

difficulty (number of moves) when performing the Tower of London task

Anatomical region Brodmann areas [% of cluster] Unit count of cluster Maximum z of cluster Mean z of cluster

CON SCZ CON SCZ CON SCZ CON SCZ

Left superior frontal gyrus 10 [100%] 6 [100%] 39 46 4.18 4.69 4.04 4.19

10 [100%] 31 4.49 4.13

Right superior frontal gyrus 6 [100%] 6 [97%]; 8 [3%] 87 73 5.12 5.12 4.42 4.25

6 [100%] 6 [71%]; 4 [29%] 49 68 4.86 4.63 4.33 4.05

Left middle frontal gyrus Ø 6 [58%]; 9 [17%];

44 [16%]; 8 [16%];

4 [2%]

Ø 827 Ø 5.11 Ø 4.29

Right middle frontal gyrus 44 [33%]; 6 [31%];

9 [24%]; 46 [12%]

6 [30%]; 44 [22%];

9 [15%]; 4 [15%];

46 [13%]; 45 [5%]

519 1236 5.55 5.52 4.50 4.37

Left inferior frontal gyrus Ø 11 [81%]; 10 [19%] Ø 37 Ø 4.77 Ø 4.21

Left opercularis region 2 [41%]; 40 [30%];

43 [21%]; 1 [9%]

ND [100%] 81 53 4.48 4.36 4.12 4.07

Right opercularis region 38 [44%]; ND [25%];

44 [20%]; 22 [10%];

6 [1%]

ND [100%] 211 89 5.78 4.5 4.68 4.06

Left superior parietal lobule 7 [65%]; 5 [35%] 7 [57%]; 40 [37%];

5 [5%]

292 115 6.59 4.90 5.02 4.26

5 [51%]; 7 [49%] 89 5.69 4.56

Right superior parietal lobule 5 [75%]; 7 [24%] Ø 291 Ø 7.28 Ø 5.24 Ø

Left inferior occipital lobe 19 [47%]; 18 [27%];

37 [14%]; 17 [12%]

Ø 322 Ø 5.51 Ø 4.33 Ø

SCZ: first-episode schizophrenia patients; CON: age- and gender-matched healthy control subjects; ND: non-defined area by warped Brodmann atlas; Ø: <

statistical threshold; [%]: percent of cluster of significant BOLD activation falling into the boundaries of the respective Brodmann area.

P.E. Rasser et al. / NeuroImage 26 (2005) 941–951 945

intensity normalization procedure was adopted. Within each

sequence, images were intensity normalized to give a mean volume

intensity of 1000. A mean image for each sequence was generated,

and subtracted from every individual volume within its associated

acquisition sequence. This resulted in (for each sequence) a mean

baseline signal of zero at every voxel, with individual volume

acquisitions representing variation around that mean. Volumes

across all sequences were then concatenated to produce a single

series. Images were subsequently co-registered into MNI space

(Collins et al., 1994) using the SPM EPI template image as the target

volume. Data were then spatially smoothed using a Gaussian filter

Table 2

Clusters (N > 20 units critically thresholded at P < 0.05 and corrected for multip

difficulty (number of moves) when performing the Tower of London task

Anatomical region Brodmann areas [% of cluste

CON SCZ

Left superior frontal gyrus 9 [79%]; ND [21%]

10 [73%]; ND [27%] 10 [7

9 [26

Right superior frontal gyrus 9 [79%]; ND [21%] Ø

10 [56]; ND [44%]

Left superior and middle temporal gyrus 22 [68%]; 21 [28%];

37 [4%]

22 [6

21 [3

Right superior temporal and supramarginal gyrus 22 [58%]; 43 [22%];

40 [15%]; 21 [3%];

37 [3%]

Ø

Right middle temporal gyrus 21 [100%] Ø

Right inferior temporal gyrus 20 [100%] Ø

SCZ: first-episode schizophrenia patients; CON: age- and gender-matched health

statistical threshold; [%]: percent of cluster of significant BOLD activation falling

with a FWHM of 15 � 15 � 9 mm3 and submitted to a parametric

general linear model analysis (SPM99; Friston et al., 1995).

The hemodynamic response related to intensity changes was

predicted by a regression model at each time step as being a linear

function of the number of moves required to solve the problem

associated with each volume acquisition. This value was assumed

to remain constant across each block of 10 volume acquisitions. To

avoid overweighting the Fzero move_ baseline condition, for each

run only the block of 10 scans associated with the third Fzeromove_ problem was included in the analysis following the PET-

validated procedure by Schall et al. (2003). Consequently, for each

le comparisons) of significant negative BOLD response dependent on task

r] Unit count of cluster Maximum z of cluster Mean z of cluster

CON SCZ CON SCZ CON SCZ

177 �4.28 �4.01

4%];

%]

78 62 �4.56 �4.32 �4.16 �4.05

279 Ø �4.56 Ø �4.16 Ø

57 �4.39 �4.09

5%];

5%]

300 117 �5.00 �4.61 �4.34 �4.21

937 Ø �6.82 Ø �5.04 Ø

21 Ø �4.53 Ø �4.20 Ø

26 Ø �4.47 Ø �4.12 Ø

y control subjects; ND: non-defined area by warped Brodmann atlas; Ø: <

into the boundaries of the respective Brodmann area.

Fig. 2. Group comparison of total number of cortical surface units and

standard deviation (critically thresholded at P < 0.05 and corrected for

multiple comparisons) for left (L) and right (R) hemispheres, respectively.

Data suggest more extended cortical areas with positive BOLD contrasts

(left) in first-episode schizophrenia patients (SCZ) with increasing task

difficulty (i.e., number of moves) when performing the Tower of London

task and compared to healthy control subjects (CON) while cortical surface

areas with negative BOLD (right) are reduced in patients (see Table 3 for

detailed statistics).

Fig. 3. BOLD unit counts by Brodmann areas (critically thresholded at P < 0.05 an

pattern averaged (GPA) model of the brain surface, for left and right hemisphere

subjects, respectively. (Fisher’s test of variance homogeneity between groups: F(

P.E. Rasser et al. / NeuroImage 26 (2005) 941–951946

run and subject, 40 volumes were submitted to the regression

analysis, including the 30 volumes associated with the Factive_condition blocks and 10 volumes associated with the third Fzeromove_ block. The resulting z-scores for each subject were then

registered to their corresponding aligned structural MR space. For

both the IA and GPA models, the z scores were group averaged,

�N corrected and thresholded at P < 0.05.

The total number of above-threshold cortical surface vertices

(i.e., indicating significant activation with increasing task difficulty

in the gray matter) was computed in each of 6 cortical regions

defined by Brodmann areas: prefrontal (BA 9; 10; 11), dorsolateral

prefrontal (BA 44; 45; 46), and frontal cortex (BA 4; 6; 8); parietal

(BA 1; 2; 3; 4; 5; 7; 19; 39; 40), temporal (BA 20; 21; 22; 37; 38),

and occipital lobe (BA 17; 18). These six measures were entered

into a repeated measurement ANOVA analysis with Greenhouse–

Geisser-adjusted degrees of freedom for the averaged statistical

model: Region by Hemisphere by Methodology (IA versus GPA)

by Group (first-episode schizophrenia patients versus healthy

control subjects).

As a measure of the dependence of function on structure,

Pearson statistical maps of the correlation between cortical gray

matter thickness and BOLD response were calculated for the GPA

model across the combined data set (i.e., patients and control

d corrected for multiple comparisons) for intensity averaged (IA) and gyral

s, and for first-episode schizophrenia patients and matched healthy control

9,9) = 1.3, not significant; see Table 3 for more detailed statistics.)

P.E. Rasser et al. / NeuroImage 26 (2005) 941–951 947

subjects) as well as separately for both groups, and thresholded at

P < 0.05.

Results

Functional activation maps of healthy subjects corresponded

with previous findings (reviewed by Schall et al., 2003) and

confirmed an increasing BOLD response with TOL task difficulty

(i.e., number of moves) in the left and right superior frontal gyrus

(BA 10 and 6), the right middle frontal gyrus (BA 6/9/44/46), the

left and right opercularis region (BA 1/2/40/43), the left and right

superior parietal lobule (BA 5 and 7), and the left inferior occipital

lobe (BA 17/18/19/37; Figs. 1B and D; Table 1) while a decreasing

BOLD response with increasing task difficulty was confirmed for

the left and right superior frontal gyrus (BA 9 and 10), the right

superior temporal and supramarginal gyrus (BA 21/22/37/40/43) as

well as the right superior, middle and inferior temporal gyrus (BA

21/22/37; Figs. 1B and D; Table 2).

While performing the TOL task in the scanner, performance of

patients and control subjects did not significantly differ at group

level (CON: 88.7% SD 9.8 versus SCZ: 83.2% SD 14.1 correct

responses). However, patients’ pattern of BOLD response clusters

differed significantly from that of the control group (Figs. 1B–D).

For instance, only patients exhibited an increase of BOLD response

in the left middle and inferior frontal gyrus while their activation of

the right superior parietal lobule and left inferior occipital lobe did

not surpass the critical threshold of P < 0.05 (corrected for multiple

Table 3

BOLD unit counts by cortical region dependent on task difficulty (number of mov

0.05 and corrected for multiple comparisons

Anatomical region Brodmann areas CON

Left Righ

Prefrontal cortex 9; 10; 11 335 42

121.6 5

Dorsolateral prefrontal cortex 44; 45; 46 49 175

59.4 14

Frontal cortex 4; 6; 8 31 18

14.2 17

Parietal lobe 1; 2; 3; 4; 5; 7; 19; 39; 40 574 62

26.9 6

Temporal lobe 20; 21; 22; 37; 38 396 84

33.9 8

Occipital lobe 17; 18 131

12.7

Total 1503 243

181.7 14

Method (IA versus GPA model)

Greenhouse–Geisser adjusted repeated measurement ANOVA statistics: Brodmann

hemisphere; means (bold); standard deviation (italic); NS: not significant.

comparisons; Table 1). However, the most significant difference

between groups was found for decreasing cortical BOLD response

with increasing task difficulty (Fig. 2). Patients’ overall negative

BOLD response was markedly diminished in both hemispheres and

reduced to two small left-hemispheric clusters above the critical

statistical threshold in the superior frontal gyrus (BA 10) and the

temporal lobe (BA 21 and 22; Table 2).

Subtraction z-score maps of healthy control subjects minus

first-episode schizophrenia subjects for unthresholded data further

indicated reduced task difficulty-dependent BOLD response in

patients in the right prefrontal cortex, the right superior and middle

temporal gyrus, the left occipital lobe, the left supramarginal gyrus

and the left opercularis area (Fig. 1F). The detailed statistical group

analysis of thresholded data by cortical region (Fig. 3 and Table 3)

confirms smaller activation clusters in patients across all cortical

regions and in particular for the prefrontal cortex (BA 9–11), the

parietal (BA 1–5; 7; 19; 39; 40), temporal (BA 20–22; 37; 38) and

occipital (BA 17; 18) lobes. However, in contrast to the

unthresholded subtraction maps, significantly larger clusters of

activation were found in the frontal (BA 4; 6; 8) and the

dorsolateral prefrontal cortex (BA 44–46) in patients as compared

to the control group when analyzing thresholded cluster data.

Statistical analysis of thresholded cluster data further confirms a

predominantly right-hemispheric activation pattern in healthy

control subjects (Table 3), particularly for the prefrontal and

frontal cortex as well as for the temporal lobe while more extensive

clusters of left-hemispheric activation was confirmed for the

occipital lobe. On the other hand, patients’ hemispheric dominance

es) when performing the Tower of London task critically thresholded at P <

SCZ ANOVA statistics F value P value

t Left Right

5 299 112 Group 8.0 0.047

8.0 35.4 103.9 Hemisphere 0.6 NS

Group by hemisphere 5.1 NS

150 577 Group 15.2 0.018

0.7 21.2 97.6 Hemisphere 18.4 0.013

Group by hemisphere 5.4 NS

4 704 677 Group 55.6 0.002

6.1 139.3 129.7 Hemisphere 0.9 NS

Group by hemisphere 1.7 NS

3 131 11 Group 355.5 <0.001

5.8 36.8 9.1 Hemisphere 2.1 NS

Group by hemisphere 10.2 0.033

9 123 13 Group 290.2 <0.001

6.3 14.9 14.1 Hemisphere 25.6 0.007

Group by hemisphere 76.3 0.001

9 5 0 Group 237.1 <0.001

2.1 1.1 0.9 Hemisphere 181.3 <0.001

Group by hemisphere 179.2 <0.001

1 1408 1369 Group 33.5 0.004

8.5 154.1 34.5 Hemisphere 19.7 0.011

Group by hemisphere 23.3 0.008

Method <0.1 NS

Method by area 0.2 NS

Method by group <0.1 NS

Method by hemisphere 0.2 NS

areas by group by hemisphere and Brodmann areas by method by group by

P.E. Rasser et al. / NeuroImage 26 (2005) 941–951948

pattern was significantly diminished or reversed in the temporal,

parietal, and occipital lobes.

The statistical analysis also indicates no significant difference

of activation at cluster level by group, region, or hemisphere when

comparing co-registration of BOLD activation onto the GPA model

versus co-registration onto the IA model of the cerebral cortex

(Fig. 3 and Table 3).

Fig. 4. Combined structural and functional magnetic resonance imaging data o

subjects (CON). Views from top to bottom: frontal, superior, left lateral, right later

GPA model of the brain surface. (A) Unthresholded correlation maps of cortica

matter while negative values indicate reduced gray matter in patients, particularly

and hippocampus. (B) Combined group BOLD response (z-score maps thresholde

the Tower of London task showing increasing activation in the prefrontal and pa

and middle temporal gyrus. (C) Correlation maps of cortical gray matter thickness

BOLD response with decreased cortical gray matter thickness in the left prefronta

across groups.

The assessment of cortical gray matter thickness by group

(GPA model) suggests predominantly right-hemispheric reduc-

tion of gray matter in patients in the prefrontal, frontal, and

parietal cortex as well as the anterior temporal lobe and the

hippocampus, thus confirming previous findings based on gray

matter density measures (e.g., Cannon et al., 2002; Fig. 4A).

Correlation analysis (co-varying gray matter thickness with

f first-episode schizophrenia patients (SCZ) and matched healthy control

al, posterior, and inferior. Brodmann areas are warped into the probabilistic

l gray matter thickness by group. Positive values indicate increased gray

in the right anterior temporal lobe, prefrontal, frontal and parietal cortex,

d at P < 0.05 [z = T3.88]) as a function of task difficulty when performing

rietal cortex and a negative BOLD response predominantly in the superior

by BOLD response (thresholded at P < 0.05 [r = T0.44]) suggest reduced

l, right orbitofrontal, right superior temporal, and bilateral parietal cortices

Fig. 5. Correlation maps of cortical gray matter thickness by BOLD

response of left and right hemispheres (thresholded at P < 0.05 [r = T0.63])indicate a reduction of BOLD response with decreasing gray matter thick-

ness in first-episode schizophrenia patients. By contrast, matched healthy

control subjects predominantly show an inverse relationship suggesting

proportionally less activation of gray matter with increasing task difficulty.

P.E. Rasser et al. / NeuroImage 26 (2005) 941–951 949

unthresholded BOLD response across groups) suggests reduced

BOLD activation as a function of reduced cortical gray matter

thickness predominantly in the left prefrontal, right orbitofrontal,

right superior temporal, as well as left and right parietal cortex

(Figs. 4B and C). This relationship was particularly expressed in

first-episode patients (Fig. 5), thus predominantly affecting left

prefrontal, left dorsolateral prefrontal and left frontal as well as

bilateral parietal BOLD activation. In healthy subjects however,

this relationship was partially reversed, particularly in the

prefrontal and frontal cortex.

Discussion

The current study pursued three objectives. First, to compare

BOLD responses co-registered on an intensity-averaged model

(IA) with BOLD responses deformed onto the gyral pattern-

averaged (GPA) model of the cortical surface; second, to compare

the cortical BOLD response pattern of first-episode male

schizophrenia patients with age-matched male healthy control

subjects; and third, to analyze differences of cortical gray matter

thickness between the two groups and its association with BOLD

response.

In respect of the first objective, both models produced an

equivalent representation of BOLD response across hemispheres,

cortical regions, and groups, respectively, when using Brodmann

areas as anatomical reference for the cortical surface. However, it is

important to emphasize that the functional data were obtained at a

relatively low resolution. This, together with the small sample size

and the complexity of the TOL task, may have contributed to a lack

of power to demonstrate significant differences between the two

methods.

Some differences between the two methods were observed in

certain areas of the cortex. For instance, in relation to the right-

hemisphere negative BOLD response in healthy subjects, the

cluster appears more circumscribed and limited to BA 22 in the

GPA model as compared to the IA model (Figs. 1B and D). A

similar effect is apparent for the left-occipital BOLD increase in

healthy subjects. These brain regions are closely associated with

elementary auditory and visual processing, supporting the notion

that the cytoarchitectonically derived Brodmann boundaries

provide a more appropriate reference system for primary sensory

regions of the cortex. Brodmann area boundaries are less useful in

defining association areas, notably the prefrontal, frontal, and

parietal cortex, due to lack of reference to the functional properties

of the underlying brain tissue (e.g., Owen, 2000). On the other

hand, Brodmann areas provide a broadly accepted reference

system, which allows standardized reporting of cortical functional

brain imaging data (Brett et al., 2002). This includes a precise

definition of location and description of relative cluster size (e.g.,

Tables 1 and 2), thus assisting cross-study comparisons, partic-

ularly when employing deformable Brodmann area anatomical

referencing.

On the second objective, our functional data largely confirm

previous fMRI and PET findings in healthy subjects where a

parametric functional neuroimaging with the TOL task has been

employed (e.g., Dagher et al., 1999; Schall et al., 2003; Van den

Heuvel et al., 2003); that is a regression analysis as a function of

task difficulty (i.e., number of moves). The GPA BOLD activation

group subtraction map (i.e., healthy control subjects minus first-

episode schizophrenia patients; Fig. 1F) suggests reduced right-

prefrontal BOLD response (i.e., superior frontal gyrus) in patients.

Newman et al. (2003) reported that the left and right prefrontal

cortices were equally involved during the solution of moderate and

difficult TOL problems while only right prefrontal activation was

highly correlated with individual differences in working memory

(as measured independently by the reading span task). However,

when comparing thresholded cluster data, significantly larger

clusters of activation in the dorsolateral prefrontal and frontal

cortex were identified; that is a larger area of cortical activation in

patients as compared to healthy control subjects at the same level

of performance (Fig. 1F and Table 1).

At cluster lever, the most striking group differences were found

for the negative BOLD response (Fig. 2), particularly in the

temporal lobes (Table 2). Dagher et al. (1999) also reported a

negative correlation of rCBF with increasing TOL task complexity

for the right superior and inferior temporal gyrus in their PET

study. These findings may indicate a progressive down-regulation

of auditory information processing with increasing workload, thus

inhibiting interfering (and potentially disturbing) sensory auditory

information processing that is not directly related to performing the

TOL task. This proposed mechanism of appropriately regulating

cortical activation dependent on task requirements appears to be

impaired in first-episode schizophrenia patients, suggestive of

impaired executive attention, which is thought to be the underlying

neural mechanism to orchestrate complex cognitive processes

(Posner and Rothbart, 1998).

Since all patients of our study were on maintenance anti-

psychotic drug treatment at the time of testing, some of the here

reported group differences might reflect medication effects.

Particularly anti-dopaminergic drug action interferes with informa-

tion processing within the frontostriatal network, thus possibly

affecting working memory performance (Ellis and Nathan, 2001).

However, our patients were maintained on a group of antipsychotic

drugs that is less likely to induce a strong anti-dopaminergic effect

(i.e., parkinsonian side effects) and instead have been found to

improve TOL performance in the course of maintenance treatment

(Bender et al., 2002; Schall et al., 1998).

On the third objective, our data derived from the GPA model

suggest a reduction of gray matter thickness in the temporal lobe,

the prefrontal, frontal, and parietal cortex, and the hippocampus in

P.E. Rasser et al. / NeuroImage 26 (2005) 941–951950

first-episode schizophrenia patients (Fig. 4A). These results

support previous studies that have identified impaired gray matter

integrity in corresponding cortical areas (e.g., Pantelis et al., 2003;

Thompson et al., 2001; Wright et al., 1995).

To assess its functional relevance, a correlation map relating

local gray matter thickness to BOLD response was calculated.

Across groups, BOLD response was positively correlated with

gray matter thickness in the left prefrontal, right orbitofrontal,

right superior temporal, and bilateral parietal cortex, thus indicat-

ing a reduction of BOLD response with decreasing cortical gray

matter (Fig. 4C). This relationship was confirmed for the

prefrontal, dorsolateral prefrontal, frontal, and parietal cortex in

the first-episode schizophrenia sample whereas an inverse relation-

ship was found predominantly for the dorsolateral prefrontal and

frontal cortex in the control sample (Fig. 5). Notably, these are

those brain regions of increased activation in patients as compared

to healthy control subjects at cluster level (Table 3). First-episode

schizophrenia patients may therefore recruit these frontal areas

more extensively in order to perform at the same level as healthy

subjects in terms of calculating the correct number of moves. In

the context of behavioral data, schizophrenia patients are more

likely to spend more time on successfully mastering the TOL task

(e.g., Morris et al., 1995; Pantelis et al., 1997; Schall et al.,

1998), which was not accommodated by the fixed interval

procedure of the current study. It may also be possible that

healthy subjects do not recruit progressively larger frontal areas

above a certain level of task difficulty (i.e., in a non-linear

fashion), thus partially resulting in a cluster of negative correlation

when BOLD response is expressed as a function of cortical gray

matter thickness.

In summary, our novel approach of assessing structure–

function relationships using cortical pattern matching offers a

new direction for research since it provides the opportunity to

integrate within-subject data derived from structural and functional

MRI data of the cortex. We demonstrated the feasibility of

mapping functional BOLD data onto the GPA model of the cortex.

However, further studies are required in order to establish its utility,

for instance, by collecting BOLD data at higher spatial resolution

(e.g., in the present study, the effective BOLD voxel size after

spatial smoothing was larger than gray matter thickness). Addi-

tionally, the cognitive task used in our study was complex, which

may have masked any potential advantage of the GPA over the IA

model. Hence, future assessments of the anatomical accuracy of

BOLD co-registration using gyral pattern averaging should be

conducted at higher spatial resolution and focus on simpler tasks

with well-established functional neuroanatomy (e.g., finger tap or

visual checkerboard). In respect to our patient data, the current

results suggest impaired integrity of cortical gray matter in high

functioning (i.e., as assessed by task performance) first-episode

schizophrenia patients with relatively mild psychotic symptoms.

This gray matter reduction appears to be associated with impaired

functional activation as assessed by task difficulty-dependent

BOLD responses during task performance. Our data also show a

marked reduction of patients’ negative BOLD response in areas

subserving sensory auditory information processing when perform-

ing a demanding visual planning/working memory task. This may

indicate impaired down-regulation of neural activity in those brain

regions that are less likely to be directly involved in TOL

performance or may be a source of distraction. Within this context,

our findings support the notion of impaired executive attention

processes in schizophrenia.

Acknowledgments

We are grateful for the skilled radiographic assistance of Steve

Hudson, Gary O’Connor, Jo Donovan, and Mary Dwyer. The

Neuroscience Institute of Schizophrenia and Allied Disorders

(NISAD) and the Hunter Medical Research Institute (HMRI) are

supported by infrastructure funding from NSW Health. R.T. and

S.B were supported by the IFORES Program, Faculty of Medicine,

the University of Duisburg-Essen. Algorithm development was

supported in part by National Institute for Biomedical Imaging and

Bioengineering and the National Center for Research Resources

(R21 EB01561 and R21 RR019771, to P.T.).

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