Neural correlates of visuospatial working memory in
the ‘at-risk mental state’
M. R. Broome1,2*, P. Fusar-Poli1,3, P. Matthiasson1, J. B. Woolley1, L. Valmaggia1,4, L. C. Johns1,
P. Tabraham1, E. Bramon1, S. C. R. Williams5, M. J. Brammer6, X. Chitnis6, F. Zelaya5and
P. K. McGuire1
1Psychosis Clinical Academic Group, Institute of Psychiatry, King’s College London, UK
2Health Sciences Research Institute, Warwick Medical School, University of Warwick, Coventry, UK
3Department of Applied and Psychobehavioural Health Sciences, University of Pavia, Italy
4Department of Psychiatry and Neuropsychology, Maastricht University, The Netherlands
5Neuroimaging Research Group, Department of Neurology, Institute of Psychiatry, King’s College London, UK
6Brain Image Analysis Unit, Department of Biostatistics and Computing, Institute of Psychiatry, King’s College London, UK
Background. Impaired spatial working memory (SWM) is a robust feature of schizophrenia and has been linked to
the risk of developing psychosis in people with an at-risk mental state (ARMS). We used functional magnetic
resonance imaging (fMRI) to examine the neural substrate of SWM in the ARMS and in patients who had just
Method. fMRI was used to study 17 patients with an ARMS, 10 patients with a first episode of psychosis and 15 age-
matched healthy comparison subjects. The blood oxygen level-dependent (BOLD) response was measured while
subjects performed an object–location paired-associate memory task, with experimental manipulation of mnemonic
Results. In all groups, increasing mnemonic load was associated with activation in the medial frontal and medial
posterior parietal cortex. Significant between-group differences in activation were evident in a cluster spanning the
medial frontal cortex and right precuneus, with the ARMS groups showing less activation than controls but greater
activation than first-episode psychosis (FEP) patients. These group differences were more evident at the most
demanding levels of the task than at the easy level. In all groups, task performance improved with repetition of the
conditions. However, there was a significant group difference in the response of the right precuneus across repeated
trials, with an attenuation of activation in controls but increased activation in FEP and little change in the ARMS.
Conclusions. Abnormal neural activity in the medial frontal cortex and posterior parietal cortex during an SWM task
may be a neural correlate of increased vulnerability to psychosis.
Received 19 January 2009; Revised 26 January 2010; Accepted 26 January 2010
Key words: ARMS, imaging, memory, prodrome, psychosis, visuospatial.
Although it is known that schizophrenia is associated
with neurocognitive dysfunction, the extent to which
this is related to the disorder, as opposed to vulner-
ability to schizophrenia, is unclear. There is also in-
creasing evidence that neuroimaging abnormalities
may change over the course of psychotic disorders
(Lieberman, 1999; Rapoport et al. 1999; Lieberman
et al. 2001; Pantelis et al. 2003) and can be affected by
treatment (Chakos et al. 2005; Dazzan et al. 2005).
Determining variables that are linked to vulnerability
to schizophrenia, rather than to the disorder itself, is
important for identifying those who may benefit from
interventions that may prevent the onset of the dis-
order, and also allows understanding of how the dis-
order develops and progresses. One way of clarifying
the relative contribution of these factors is to compare
individuals who are at very high risk of psychosis,
patients who have just developed schizophrenia and
have had minimal treatment, and healthy volunteers.
People with ‘prodromal’ symptoms of psychosis
have a 25–40% risk of developing a psychotic disorder
in the next 12 months (Yung et al. 2003) and thus have
an ‘at-risk mental state’ (ARMS). However, this rate of
transition has not remained the same in other centres
or, indeed, over time. Other groups have reported
higher rates of transition (Miller et al. 2002), and the
* Address for correspondence: Dr M. R. Broome, Warwick Medical
School, University of Warwick, Gibbet Hill, Coventry CV4 7AL, UK.
Psychological Medicine, Page 1 of 13.
f Cambridge University Press 2010
Melbourne Personal Assessment and Crisis Evalu-
ation (PACE) service has recently reported a transition
rate of less than 10% (Yung et al. 2007). Within our
own service, OASIS, current transition rates are at ap-
proximately 21% (Valmaggia et al. 2009). Knowledge
of neurocognitive function in this group is growing
rapidly. Neuropsychological studies point to an im-
pairment of executive and memory functions (Brewer
et al. 2005) with some deficits only evident when the
task demands are relatively high (Broome et al. 2007).
In general, neuropsychological performance in ARMS
subjects has been found to be at an intermediate level
relative to patients with schizophrenia and controls
(Wood et al. 2003; Brewer et al. 2005; Lencz et al. 2006;
Wagner et al. 2006; Pukrop et al. 2007), with evidence
suggesting that spatial working memory (SWM) is
impaired. Structural magnetic resonance imaging
(MRI) studies suggest that the ARMS is associated
with reduced grey matter volumes in the prefrontal,
cingulate and temporal cortex (Pantelis et al. 2003)
whereas functional MRI (fMRI) studies have reported
differential prefrontal activation in ARMS subjects
relative to controls and patients with schizophrenia
during a visual oddball paradigm (Morey et al. 2005)
and during verbal fluency and the N-back verbal
working memory tasks (Broome et al. 2009). In both
these studies, the clinical high-risk group demon-
strated activations intermediate between those with
schizophrenia and healthy controls, with the control
subjects typically showing greatest activation and
those with psychosis, the least.
Working memory refers to the retention of infor-
mation in conscious awareness when it is not present
in the environment. Working memory has been im-
plicated as an important contributor to language pro-
cessing, learning, planning, reasoning and general
fluid intelligence (Postle, 2006). It can be subdivided
into a memory component (holding information
‘online’) and a manipulation component (working
on the information being held). It has been further
subdivided according to the form of the information
involved (verbal versus non-verbal; spatial versus non-
spatial; verbal versus object memory) (Pollmann &
von Cramon, 2000). In our previous imaging work
with the ARMS groups we studied verbal working
memory (Broome et al. 2009). In the present study our
focus is on SWM. SWM impairments have been well
documented in schizophrenia (Park & Holzman, 1992;
Fleming et al. 1997) and have been highlighted as a
neuropsychological dysfunction that is core to the
disorder (Silver et al. 2003; Joyce & Huddy, 2004).
Impairments in visuospatial working memory are
evident early in the course of schizophrenia (Wood
et al. 2002, 2003; Smith et al. 2006; Vance et al. 2006),
but it is unclear whether impairments in SWM predate
the onset of psychosis. Studies of monozygotic and
dizygotic twins pairs discordant for schizophrenia
(Cannon et al. 2000; Glahn et al. 2005) indicate that
SWM deficits are associated with increased genetic
risk for schizophrenia, and it has been suggested that a
higher genetic loading for disease-related traits is
linked to greater cognitive impairment (Saperstein
et al. 2006). Impaired spatial memory performance has
also been reported in subjects with high levels of
schizotypy (Park et al. 1995) or schizotypal personality
disorder (Farmer et al. 2000), and in those with a his-
tory of very preterm birth (Narberhaus et al. 2009).
Several studies have reported impaired memory
performance in the ARMS (Wood et al. 2003; Brewer
et al. 2005; Francey et al. 2005; Lencz et al. 2006; Pukrop
et al. 2007). Brewer et al. (2005) found that ARMS sub-
jects showed impairments on measures of visual re-
production and verbal memory, and that this deficit
was specific to the subgroup that went on to develop
psychosis. Brewer and colleagues performed a paired-
associate task, but one that assessed verbal, rather than
spatial, memory. To date, functional neuroimaging
studies of working memory in the ARMS have been
limited to the verbal domain (Broome et al. 2009).
However, SWM has been studied in the offspring of
people with schizophrenia using a memory-guided
saccade task; this genetically high-risk group showed
decreased activation in the dorsolateral prefrontal
and inferior parietal cortex while performing the task
relative to controls (Keshavan et al. 2002).
In the present study, we used fMRI to assess cortical
activation during an object–location paired-associate
memory task. This task is complex, comprising el-
ements of encoding, recognition, learning and dis-
crimination (Narberhaus et al. 2009). Interpretation of
data from non-verbal associative learning tests can be
compromised if the stimuli are easy to verbalize
(Goldstein et al. 1988). Paired-associate learning (PAL)
tasks attempt to overcome this problem by pairing
abstract designs with spatial locations (Brewer et al.
2005). The paradigm we used also incorporated dif-
ferent levels of mnemonic load, which allowed us to
examine whether functional deficits were related to
the demands on working memory. In addition, the
repetition of trials over the course of the study enables
us to examine whether abnormalities were related to
the ability to learn the relationship between the pairs
of stimuli and their spatial location. We studied three
groups: (1) patients with a first episode of schizo-
phrenia, (2) subjects with an ARMS, and (3) healthy
controls. We hypothesized that, relative to controls,
individuals with an ARMS would show qualitatively
similar functional abnormalities to patients with first-
episode psychosis (FEP) but that the magnitude of
these abnormalities would be less severe. More
2M. R. Broome et al.
specifically, we predicted that group differences in
activation would be evident in the frontal and parietal
cortex (Curtis, 2006), with the superior frontal cortex
implicated in the maintenance of spatial information
and the dorsolateral cortex implicated in its manipu-
lation (Postle et al. 2000), and that these differences
would become more apparent as the mnemonic de-
mands of the task were increased (Gould et al. 2003).
A further prediction was that differential frontal and
parietal activation would be evident in association
with differential learning across repeated trials of the
task (Brewer et al. 2005; Lencz et al. 2006).
Individuals meeting PACE criteria for the ARMS were
recruited from Outreach and Support in South London
(OASIS; Broome et al. 2005a). The diagnosis was based
on assessment by two experienced clinicians using the
Comprehensive Assessment for the ARMS (CAARMS;
Yung et al. 1998, 2003) and a consensus meeting with
the clinical team. None of the subjects had ever re-
ceived antipsychotic medication. An individual can
meet criteria for the ARMS in one or more of three
ways: first, a recent decline in function coupled with
either schizotypal personality disorder or a first-
degree relative with psychosis; second, ‘attenuated’
positive symptoms; and third, a brief psychotic epi-
sode of less than 1 week’s duration that resolves
without antipsychotic medication.
Patients who had recently presented with a first epi-
sode of psychosis (n=10) were recruited from
Lambeth Early Onset (LEO) Services (www.slam.nhs.
uk/services/). All met ICD-10 criteria for schizo-
phreniform psychosis at the time of scanning and met
OPCRIT criteria (McGuffin et al. 1991) for schizo-
phrenia when subsequently reassessed 12 months
after first presentation. Three of these patients were
unmedicated. The other seven had been treated with
either oral risperidone or quetiapine for a mean of
10 days [95% confidence interval (CI) 4.7–16.3] at
mean doses of 1.7 and 63.75 mg respectively.
Healthy volunteers (n=15) were recruited through
advertisements in the local media. All subjects lived
in the borough of Lambeth (London), were native
speakers of English and were right-handed. The
groups were matched on sociodemographic variables
(Table 1), including age (F=0.35, p=0.71) and hand-
edness. Subjects were excluded if there was a history
of neurological disorder or they met DSM-IV criteria
for a substance misuse disorder. General intellectual
function was estimated in all subjects using the
National Adult Reading Test (NART). The severity of
symptoms in the clinical groups was assessed with the
Positive and Negative Syndrome Scale (PANSS; Kay,
1990) on the day of scanning by a psychiatrist (M.R.B.
or P.M.) trained in its use.
Stimuli were presented in 22.5 s epochs, alternating
with 34.5 s epochs of cross-hair fixation; this cycle was
repeated 12 times (for a total of 24 epochs) so the total
duration of the experiment was 686 s or 343 images
[repetition time (TR)=2 s]. Cognitive load was ma-
nipulated by presenting trials at one of three levels
of difficulty (easy, intermediate, and hard) in a block
design, with four blocks of each level of difficulty.
Thus, there were a total of 12 blocks of trials alternat-
ing with 12 blocks of cross-hair fixation. The blocks of
trials were always presented in the same sequence
with respect to level of difficulty: easy, intermediate,
and then hard. Each block comprised seven trials.
In an easy trial, two stimuli (highly discriminable
coloured shapes) were shown either side (left and
right) of a central cross-hair, followed by the central
cross-hair alone, then the central presentation of one of
the two original stimuli. Subjects had been trained to
move a joystick with their right hand in the direction
of the location originally occupied by the central
stimulus. Intermediate and hard trials were the same
except that four and eight stimuli were presented
around the central cross-hair respectively. The speed
Table 1. Age, IQ, gender and psychopathology ratings
51. 9 (12.7)
NART, National Adult Reading Test; M, male; F, female;
PANSS, Positive and Negative Syndrome Scale; ARMS,
at-risk mental state; FEP, first-episode psychosis; N.A., not
Values given as mean (standard deviation).
Neural correlates of visuospatial working memory3
recorded during scanning. To avoid habituation of the
subject, every stimulus had a randomly varied time of
presentation, either between stimuli or before the
presentation of the probe. As the stimuli were jittered
randomly in every block, we did not need to take ac-
count of this in the block design analysis (Fig. 1).
accuracyofthe joystickmovements were
All behavioural data, response accuracy and response
latency, were recorded on a personal computer using
Visual Basic (Microsoft Corp., USA) and analysed in
SPSS version 11.0 (SPSS Inc., USA).
Images were acquired on a 1.5-T Signa (GE) system at
the Maudsley Hospital, London. T2*-weighted images
were acquired in 38r3 mm slices, with a 0.3 mm gap
in 14 axial planes, and a TR of 2 s, echo time (TE)
40 ms, and flip angle 90x. To facilitate anatomical
localization of activation, a high-resolution inversion
recovery image dataset was also acquired, with 3 mm
contiguous slices and an in-plane resolution of 3 mm
[TR 1600 ms, inversion time (TI) 180 ms, TE 80 ms].
Individual brain activation maps
The data were analysed with software developed at
the Institute of Psychiatry, using a non-parametric
approach. Data were realigned (Bullmore et al. 1999b)
and then smoothed using a Gaussian filter [full-width
at half-maximum (FWHM) 7.2 mm]. Responses to the
experimental paradigms were detected by convolving
each component of the design with each of two
gamma variate functions (peak responses at 4 and 8 s
respectively). The best fit between the weighted sum
of these convolutions and the time series at each voxel
was computed using the constrained blood oxygen
level-dependent (BOLD) effect model (Friman et al.
2003). A goodness-of-fit statistic comprising the ratio
of the sum of squares of deviations from the mean
image intensity (over the whole time series) divided
by the sum of squares of deviations due to the re-
siduals (SSQratio) was then computed at each voxel.
The data were then permuted by a wavelet-based
method (Bullmore et al. 2001) to calculate the null dis-
tribution of SSQratios under the assumption of no ex-
perimentally determined response. This was used to
calculate the critical value of SSQratio needed to
threshold the maps at a type I error rate of <1. The
detection of activated voxels was then extended from
voxel to cluster level (Bullmore et al. 1999a). To mini-
mize the potential confounding effects of between-
group and between-condition variation in task per-
formance, in the analysis of data from the task the
BOLD response in each subject was modelled using
only trials associated with correct responses. In ad-
dition to the SSQratio, the size of the BOLD response
to each experimental condition was computed for each
individual at each voxel as a percentage of the mean
resting image intensity level. To calculate the BOLD
Display array Fixation Test stimulus
Display arrayFixation Test stimulus
Display arrayFixation Test stimulus
Fig. 1. The paired-associate learning task.
4 M. R. Broome et al.
effect size, the difference between the maximum and
minimum values of the fitted model for each condition
was expressed as a percentage of the mean image in-
tensity level over the whole time series.
The SSQratio maps for each individual were trans-
formed into the standard space of Talairach &
Tournoux (1988) using a two-stage warping procedure
(Brammer et al. 1997). Group activation maps were
computed by determining the median SSQratio at
each voxel (across all individuals) in the observed
and permuted data maps. The distribution of median
SSQratios from the permuted data was used to derive
the null distribution of SSQratios and the critical
SSQratio to threshold group activation maps at a
cluster level threshold of <1 expected type I error
cluster per brain.
Linear trend analysis
Two different types of linear trend analysis were per-
formed to assess linear change in neural activation
dependent on group (analysis 1) and on mnemonic
load (analysis 2). In the first analysis, for each mne-
monic load (easy, intermediate, hard), control, ARMS
and FEP subjects were respectively coded with dum-
my variables x1, 0 and 1. A linear model was selected
to test the hypothesis that activation in the ARMS
group would be intermediate between that in the
controls and FEP subjects. In the second analysis, for
each group (ARMS, control, FEP), the easy, inter-
mediate and difficult levels of the task were respect-
ively coded with dummy variables x1, 0 and 1. In this
case a linear model was selected to test the hypothesis
that activation at the intermediate level would be in-
termediate between that during the easy and hard
levels. To minimize the potential confounding effects
of between-group and between-condition variation in
task performance, in each subject the BOLD response
was covaried with the performance score. To ensure
that we examined whether the middle group was in-
termediate in both the linear trend analyses (ARMS
group in comparison to FEP and controls; medium
mnemonic load in comparison to easy or hard load),
an additional quadratic trend analysis was performed
using the dummy variables (x1, 2, x1). Data that
failed to fit this model, but that fitted the linear model,
would hence have a middle group that was indeed
intermediate between the other groups.
ANOVA was carried out on the effect size maps
representing percentage change in BOLD response
in standard space by first computing the difference
in median SSQratio between groups at each voxel.
Subsequent inference of the probability of this differ-
ence under the null hypothesis was made by reference
to the null distribution obtained by repeated random
permutation of group membership and recomputation
of the difference in median SSQratios between the two
groups obtained from the resampling process. Cluster-
level maps were then obtained as described above. We
set a voxel-wise p value of 0.05 and a cluster-wise p
value of 0.01. This method ensured a total number of
false-positive clusters of <1. Corrections for multiple
comparisons were not required, as thresholds were set
on an image-wide, not a voxel-wise, basis.
Given the possible limitations of the linear trend
analysis described above, and to identify more pre-
cisely the relationship between groups (ARMS, FEP,
control), task loads (two objects, four object, eight
objects), or the effects of task repetition (comparing the
first half of the run with the latter half), post-hoc com-
parisons were made between the respective con-
ditions. Comparison of responses between groups or
experimental conditions was performed by fitting the
data at each intracerebral voxel at which all subjects
had non-zero data using a linear model of the type
Y=a+bX+e, where Y is the vector of BOLD effect
sizes for each individual, X is the contrast matrix
for the particular inter-condition/group contrasts re-
quired, a is the mean effect across all individuals in the
various conditions/groups, b is the computed group/
condition difference and e is a vector of residual errors.
The model was fitted by minimizing the sum of ab-
solute deviations rather than the sums of squares to
reduce outlier effects. The null distribution of b was
computed by permuting data between conditions/
groups (assuming the null hypothesis of no effect of
experimental condition or group membership) and
refitting the above model. Group difference maps
were computed using BOLD effect maps rather than
standardized measures such as SSQratio, F or t as
these contain explicit noise components (error SSQ or
error variance), raising the possibility that group dif-
ferences resulting from F, SSQratio or t comparisons
could reflect differences in noise rather than signal.
We have consistently adopted stringent levels of stat-
istical significance for all the hypothesis tests reported
on imaging data. For all between-group ANOVAs we
set a voxel-wise p value of 0.05 and a cluster-wise p
value of 0.01. For trend analysis conducted at cluster
level, we set a voxel-wise p value of 0.05 and a cluster-
wise probability p value of 0.01. This method ensured
Neural correlates of visuospatial working memory5
a total number of false-positive clusters of <1.
Corrections for multiple comparisons were not re-
quired, as thresholds were set on an image-wide, not a
The method of analysis we used (XBAM) makes use
of median statistics to control outlier effects and per-
mutation rather than normal theory-based inference.
The main test statistic is computed by standardizing
for individual differences in residual noise before
embarking on second-level, multi-subject testing using
using a mixed effects analysis and permutation-based
and cluster-level inference seem to be more valid than
analyses involving simple random effects and voxel-
level inference (Thirion et al. 2007).
Repeated-measures ANCOVA showed a main effect
for task difficulty with respect to accuracy (F=154.29,
p<0.00) and latency (F=229.47, p<0.00). As the
mnemonic load increased, response latency increased
and response accuracy decreased in an approximately
linear fashion (Fig. 2). No main effect for group was
observed with respect to accuracy (F=1.59, p=0.271)
or latency (F=1.7, p=0.247). However, post-hoc
analysis revealed that, compared to controls, FEP
showed impaired accuracy during the intermediate
and hardest level of the task (t tests<0.05). No sig-
nificant interactions of group by task load were ob-
served with respect to accuracy (F=0.226, p=0.013) or
latency (F=1.19, p=0.415) (Fig. 2).
To explore the effect for learning, we compared the
accuracy in the first half of the run with accuracy in
the second half of the run. During the easiest level of
the task, there were no significant differences in accu-
racy between the first and the last blocks (paired t
tests>0.05). Conversely, when performing the more
demanding levels of the task (intermediate plus hard
level), subjects performed better during the second
half of the run than the first. This effect was evident
for all three groups, FEP, ARMS and controls (all
Main effect of task (independent of group and mnemonic
load): group analysis
Across all groups and levels of task demand, relative
to baseline (cross-hair fixation), the task was asso-
ciated with activation in a wide region spanning the
cerebellum and occipital cortex bilaterally (precuneus
x=x25, y=x70, z=37). Conversely, cross-hair fix-
ation was associated with activation in the left pos-
terior cingulate gyrus (x=x7, y=x63, z=15) (voxel
p=0.05, cluster p=0.001, type I error p<1).
Activation associated with mnemonic load: linear trend
Independent of group, increasing the number of
stimuli (from two to four to eight) was associated with
activation in the left medial frontal/superior frontal
and precentral gyrus, the cerebellum bilaterally and
the right cuneus (voxel p=0.05, cluster p=0.01, type I
error, p<1). After controlling for response accuracy,
the activation in the left medial frontal/superior fron-
tal gyrus and right precuneus remained significant
(voxel p=0.05, cluster p=0.01). In both these regions
the intermediate level of the task showed less acti-
vation than the most demanding level but greater ac-
tivation than the easy level (all t tests<0.05) (Fig. 3).
Error bars show 95.0% Cl of mean
Error bars show 95.0% Cl of mean
Reaction time (ms)
Fig. 2. Performance during the paired-associate learning (PAL) task. ARMS, ‘At-risk mental state’; FEP, first-episode psychosis.
6M. R. Broome et al.
Changes in activation dependent upon group: linear trend
Easy level (two objects). While performing the easiest
level of the PAL task, there was differential activation
across the three groups in a cluster spanning the
medial frontal and anterior cingulate gyrus (voxel
p<0.05, cluster p<0.01) (Fig. 4a). In this region the
magnitude of activation in the ARMS group was
similar to that in controls, whereas the FEP group
showed less activation than both other groups. Post-
hoc paired comparisons confirmed that the FEP group
showed significantly less activation than both the
ARMS and control groups (t tests<0.05), with no sig-
nificant difference between the latter two groups (t
tests>0.05) (Fig. 4a). These differences remained sig-
nificant after covarying for accuracy (voxel p<0.05,
Intermediate level (four objects). While performing the
intermediate level of the PAL task, we detected dif-
ferential activation across the three groups in the right
cerebellum, right precuneus [Brodmann area (BA) 19]
and medial frontal/superior frontal gyrus (BA 6/32)
(voxel p<0.05, cluster p<0.025; Fig. 4b). In these re-
gions the magnitude of activation in the ARMS group
was intermediate between that of the controls and FEP
subjects, with the FEP group showing less activation
than both other groups, and control subjects the
Hard level (eight objects). While subjects were perform-
ing the most demanding level of the PAL task, there
was differential activation across the three groups in
the medial frontal gyrus/superior frontal gyrus (BA
32/6) and right precuneus (19) (voxel p<0.05, cluster
p<0.01; Fig. 4c). In these regions the magnitude of
activation in the ARMS group was intermediate be-
tween that of both controls and FEP subjects, with the
FEP group showing less activation than both other
groups and the control subjects the greatest (Fig. 5).
These differences remained significant after covarying
for accuracy (voxel p<0.05, cluster p<0.01).
Main effect of task repetition (independent of group):
Across all groups, processing the most demanding
levels of the task (intermediate plus hard) was as-
sociated with a greater activation in the right pre-
cuneus (x=21, y=x59, z=36) during the second half
of the run than that in the first half (voxel p=0.01,
cluster p=0.0075). There were no brain areas that
showed greater activation in the first half of the run
compared with the second (Fig. 5).
Group differences in effect of task repetition
There was also a difference between the groups in the
effect of repetition of the most demanding levels of the
task in a region spanning the left cuneus/precuneus
(BA 7/19, x=x10, y=x74, z=31). In this region,
there was a greater response during the second half of
the run relative to the first, with the magnitude of the
within-group difference greatest in the FEP group,
smallest in the controls and intermediate in the ARMS
(all t tests<0.05).
Effects of antipsychotic medication: correlational analysis
Within the FEP group (which was the only group that
included subjects on antipsychotic medication), for
all levels of task demand, there was no correlation
Median of SSQs ratios in the MFG/SFG
Median of SSQs ratios in right precuneus
8 1624 32
Fig. 3. Main effect for task difficulty across all groups. Areas shown in yellow revealed increasing activation as task demand was
increased (high level>medium level>easy level). MFG, medial frontal gyrus; SFG, superior frontal gyrus; ARMS, ‘at-risk
mental state’; FEP, first-episode psychosis.
Neural correlates of visuospatial working memory7
Median of SSQs ratios
Median of SSQs ratios
8 16 2432
Median of SSQs ratios
8 1624 32
Fig. 4. (a) Easy level: between-group difference in activation (controls>ARMS>FEP) in the medial frontal gyrus (voxel p=0.05,
cluster p=0.01). The left side of the brain is shown on the left of the picture. (b) Intermediate level: between-group differences in
activation (controls>ARMS>FEP) in the middle frontal gyrus, right precuneus and right cerebellum (voxel p=0.05, cluster
p=0.01). (c) Hard level: between-group differences in activation (controls>ARMS>FEP) in the medial frontal gyrus and right
precuneus (voxel p=0.05, cluster p=0.01). MFG, medial frontal gyrus; SFG, superior frontal gyrus; ARMS, ‘at-risk mental
state’; FEP, first-episode psychosis.
8 M. R. Broome et al.
(Pearson’s r, n=10, p>0.05) between activation in
brain areas that were differentially engaged in the FEP
group relative to the other two groups and measures
of antipsychotic treatment (daily and cumulative dose
in chlorpromazine equivalents, or exposure).
The present study used fMRI to study the neural sub-
strate of SWM in subjects with an ARMS. In line with
our hypothesis, there was a consistent pattern of dif-
ferential activation across the groups on all levels of
difficulty of the task, with an additional differential
response across the groups on the analysis to examine
the effects of learning.
The differential activation was not attributable to
impairments in task performance, as there were no
significant differences in the speed or accuracy of re-
sponses across groups, and the analysis selectively
modelled the BOLD response to those trials associated
with correct responses. Hence, any remaining differ-
ence in activation is likely to be due to the disorder of
Similarly, the findings are unlikely to be related to
effects of antipsychotic medication as both the ARMS
subjects and controls were antipsychotic medication
naive, and in the first-episode group there was no
relationship between medication exposure and acti-
vation in the regions that were differentially engaged
When quadratic trend analysis was carried out,
there were no significant clusters activated differen-
tially across the groups, indicating that there was a
predominantly linear relationship in activation across
the groups on all the tasks.
Neural network underlying object and SWM
Compared to cross-hair fixation, PAL engaged a wide
area spanning the cerebellum and visual cortex bilat-
erally. We also manipulated task difficulty by para-
metrically varying memory load in the task. We found
that the medial frontal/superior frontal gyrus and the
right precuneus showed a linear response. These brain
areas have been extensively implicated in spatial and
object working memory (McCarthy et al. 1996; LaBar
et al. 1999; Rypma et al. 1999).
A medial superior frontal gyrus region, centred on
the supplementary motor area (SMA), has been tra-
ditionally associated with motor control necessary in
the selection of action sets and in monitoring of re-
sponse conflict (Rushworth et al. 2004) and also speech
expression and memory (Chung et al. 2005). The an-
terior part of the SMA is known to interconnect with
the prefrontal cortex and to play a role in the more
complex components of movement (Exner et al. 2006).
As such, the role of the SMA is likely to be key in per-
forming the SWM task. The absence of hippocampal
activation may suggest that such activation does
not distinguish the groups or the effect of mnemonic
load. However, imaging data have demonstrated
both over- and underactivation of the hippocampus
in memory tasks in schizophrenia (Boyer et al. 2007).
Functional imaging findings in healthy subjects
evidenced a central role for the precuneus, in visuo-
spatial imagery, episodic memory retrieval (Krause
et al. 1999; Wagner et al. 2005) and self-processing
operations (Cavanna & Trimble, 2006). Nagahama
et al. (1999) showed that the precuneus may process
spatial attention and attention shift between object
features. Lesion studies suggest that the dorsal
stream of the ‘visuospatial sketchpad’ involves the
Main effect (t2>t1)Linear trend (FEP>Control>ARMS)
Median of SSQs ratios in the left precuneus
Fig. 5. Effect of learning on activation. There was a main effect across all groups in the right precuneus, with greater
activation during the second half of the experiment (voxel p=0.05, cluster p=0.01). t1=intermediate and hard level of the
paired-associate learning (PAL) task during the first half of the run; t2=intermediate and hard level of the task during the
second half of the run. ARMS, ‘At-risk mental state’; FEP, first-episode psychosis.
Neural correlates of visuospatial working memory9
precuneus, and this may enable spatial operations
(Muller & Knight, 2006). Hence, our finding impli-
cating differential precuneus activation may be due to
its probable role in visual imagery, spatial behaviour
and spatial attention, all functions relevant for the
Group differences in activation
Consistent with our first hypothesis, during both the
intermediate and the hard versions of the task, acti-
vation in the medial frontal cortex and precuneus in
the ARMS group was intermediate relative to that in
the FEP group and controls. The localization of the
group differences in activation in the medial frontal
cortex and precuneus is consistent with data from
previous neuroimaging studies of SWM in schizo-
phrenia (Gould et al. 2003; Curtis, 2006). A different
pattern of activation across groups was evident during
the least demanding (‘easy’) version of the task. In this
case there were no significant differences in activation
between the ARMS and the control subjects, and dif-
ferences in activation were limited to the medial fron-
tal cortex, which responded more weakly in the FEP
than the other groups. This suggests that functional
abnormalities in the ARMS group became more evi-
dent as the task demands were increased, as has been
reported in behavioural studies of other paradigms
(Broome et al. 2007).
SWM as a neurocognitive vulnerability marker for
Kuperberg et al. (2003) found significant cortical thin-
ning in the medial frontal areas of adult schizophrenic
patients, and grey matter reductions have been re-
ported in the medial premotor cortex (Honey et al.
2003). Imaging studies suggest that the medial frontal
gyrus (Stevens et al. 1998; Paillere-Martinot et al. 2001)
and the medial prefrontal cortex (Ananth et al. 2002)
are affected early in psychosis. Suzuki et al. (2005)
found the SMA to be reduced in subjects with recent-
onset schizophrenia whereas Exner et al. (2006)
showed that reduced volume of the SMA in FEP sub-
jects was related to impaired implicit learning. Medial
frontal cortex dysfunction is compatible with the hy-
pothesis of a core deficit in early stages of psychosis
involving a failure to monitor actions generated in-
ternally (Exner et al. 2006). Activation in the cuneus
and precuneus increased in the second half of the run,
during the harder versions of the task, in all three
groups. However, this increase itself was greatest in
the FEP group, least in the controls, and intermediate
in the ARMS cohort. Given that behavioural perform-
ance improved, it is likely that this differential acti-
vation of the precuneus may underpin such a learning
effect, and, furthermore, that greater activation in the
FEP group is required than in the control group (with
the ARMS group intermediate) to enable the same
degree of learning. Barnett et al. (2005) suggested that
visuospatial PAL failure may be a marker of clinical
severity, in a first-episode cohort, whereas executive
dysfunction may reflect more stable, trait-like impair-
ment. However, in our data there seems to be some
relationship between executive function and clinical
course in the at-risk sample (Fusar-Poli et al. 2009) and
we are currently undertaking longitudinal studies of
the PAL task in the at-risk cohort.
This study suggests that the ARMS is associated with a
dysfunction in the neural substrate for SWM. This is
not attributable to an effect of psychotic illness, as
none of the subjects were psychotic, nor an effect of
antipsychotic treatment, as all of the ARMS subjects
were medication naive. These observations are con-
sistent with independent neuroimaging and neu-
ropsychological evidence that the ARMS is associated
with neurofunctional abnormalities that are qualitat-
ively similar to, but less severe than, those seen in
patients with schizophrenia (Broome et al. 2005b, 2007,
2009; Fusar-Poli et al. 2007). As those in the ARMS
group had a high risk of developing a psychotic dis-
order but were not psychotic, the functional abnor-
malities they displayed can be seen as a correlate of
their increased vulnerability to psychosis.
Limitations of the study
This study reports cross-sectional data, from a mod-
estly sized sample, on ARMS, FEP and control sub-
jects. The findings in the ARMS group may be a
correlate of the subjects’ increased vulnerability to
psychosis. However, to determine this formally will
require a longitudinal study, a study informed by the
findings presented here and, in particular, whether the
pattern and degree of activation during visuospatial
working memory tasks predict transition to psychosis
in a clinical high-risk group. We hope to report longi-
tudinal fMRI data, and particularly the relationship to
clinical outcomes such as transition to psychosis, in
OASIS is supported by the Guy’s and St Thomas’
Charitable Foundation and the South London and
Maudsley National Health Service (NHS) Trust. We
thank all the clients, staff and referrers of both OASIS
10 M. R. Broome et al.
Declaration of Interest
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