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Neuronal Substrate of the Saccadic Inhibition Deficit in Schizophrenia Investigated With 3-Dimensional Event-Related Functional Magnetic Resonance Imaging
Mathijs Raemaekers, MSc;
Johannus M. Jansma, PhD;
Wiepke Cahn, MD;
Josef N. Van der Geest, PhD;
Jeroen A. van der Linden, MD;
René S. Kahn, MD, PhD;
Nick F. Ramsey, PhD
Arch Gen Psychiatry. 2002;59:313-320.
ABSTRACT
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Background Several studies have shown that the ability to suppress automatic saccadic
eye movements is impaired in patients with schizophrenia as well as in their
first-degree relatives, and suggest that this impairment is a potential vulnerability
marker for schizophrenia. The neurobiological mechanisms underlying normal
saccade production and inhibition, revealed in primate studies, indicate that
the impairment may result from a failure of the oculomotor system to effectively
exert inhibitory control over brainstem structures. Functional localization
of the affected brain structure(s) potentially provides a physiological measure
for the investigation of vulnerability markers in schizophrenia.
Methods The hemodynamic response to discrete visual stimuli was measured during
prosaccades (saccades toward a peripheral stimulus), antisaccades (saccades
toward a position opposite to a peripheral stimulus), and active fixation
(holding fixation and ignoring a peripheral stimulus) in 16 patients with
schizophrenia receiving atypical neuroleptics and 17 healthy control subjects
using an event-related functional magnetic resonance imaging task design.
Results Brain responses were detected in the frontal and parietal regions of
the oculomotor system in all 3 tasks. Patients made more errors during inhibition
tasks and exhibited a selective failure to activate the striatum during the
inhibition of saccades. In other regions that were active during inhibition,
specifically the supplementary and frontal eye fields, no difference was found
between patients and control subjects.
Conclusions A frontostriatal network is engaged in the suppression of automatic
eye movements. The results indicate that abnormalities in this network, rather
than the selective dysfunction of prefrontal brain regions, underlie the saccade
inhibition deficit in schizophrenia.
INTRODUCTION
SMOOTH PURSUIT eye movement1 and the
inhibition of automatic saccades2 is impaired
in patients with schizophrenia, their healthy first-degree relatives,3-4 and healthy subjects with high scores
on a measure of schizotypy.5 This suggests
that eye movement deficits are a vulnerability marker6-7
or reflect an endophenotype8 for schizophrenia.
A common feature of both smooth pursuit eye movements and antisaccade tasks
is the requirement to avoid automatic intruding saccades. The failure to effectively
inhibit saccades may explain the oculomotor impairments observed in patients
with schizophrenia.9-10 A potential
link has been reported between the antisaccade deficit and a genetic marker
on chromosome 22q.11 The neural correlate of
the antisaccade deficit in schizophrenia has not yet been identified. The
elucidation of the neural correlate could provide a physiological measure
of saccade inhibition, which could in turn prove to be a better endophenotype
marker than the behavioral measure.
In the antisaccade task,12 subjects have
to suppress saccades that are triggered by a peripherally presented stimulus
(prosaccades) and instead have to generate a saccade toward a location in
the opposite direction (hence, antisaccade). Patients
with schizophrenia fail to suppress the reflexive saccades more often than
healthy controls and exhibit longer saccade onset latencies of correct responses,
whereas prosaccade performance is well within normal range.13-17
The deficit in saccade suppression in schizophrenia has been attributed to
prefrontal dysfunction, a postulated key feature of schizophrenia.18 Some reported correlations between saccade inhibition,
dorsolateral prefrontal cortex (DLPFC) function, and working memory support
this theory.19-21
However, the notion of DLPFC involvement in saccade inhibition is primarily
based on lesion studies.22-23
Alternatively, studies in nonhuman primates indicate that saccade inhibition
involves more complex hierarchical networks.24
In a recent study on the functioning of the superior colliculus (SC) in primates,
neuronal activity in the SC was reduced immediately before antisaccades but
not before prosaccades, indicating that the SC must be suppressed by this
network to prevent an automatic saccade.2 The
failure to inhibit a saccade can be caused by any one of the brain structures
forming the neural network that projects to the SC. The saccadic inhibition
deficit in schizophrenia could therefore be associated with cortical as well
as basal ganglia dysfunction, or disconnection, because both have been implicated
in schizophrenia.25-26
To our knowledge, only 2 functional imaging studies have investigated
the saccade inhibition deficit in schizophrenia. The deficit was associated
with reduced blood flow in the DLPFC and frontal eye fields (FEF) in one study27 and with reduced blood flow in the insula, anterior
cingulate cortex, and striatum in the other study.28
In both studies, single measurements of brain perfusion required sustained
periods (minutes or longer) during the task. Because the responses to stimuli
are brief, such prolonged measurements are predominantly sensitive to tonic
levels of activity. Brain regions that exhibit a change in tonic activity
may be directly involved not in saccade inhibition but rather in sustained
attention and effort.
To investigate the specific neuronal correlates of the saccadic inhibition
deficit in schizophrenia, we used a new experimental design that differs from
the previous studies in 2 ways. First, to focus on the inhibition of saccades,
an active fixation task was added to the experiment29;
subjects were required to ignore distracting visual stimuli. The antisaccade
task is not sufficient because it involves other processes in addition to
inhibition, particularly those that are required for the deliberate initiation
of a saccade toward another predetermined location.30-31
Patients with schizophrenia are more easily distracted by stimuli when the
task requires active fixation.14 Second, the
tasks were adapted for event-related functional magnetic resonance imaging
(ERfMRI). This technique has the advantage of coupling changes in the BOLD
(blood oxygenation level–dependent) signal with specific events in time,
which provides the opportunity to distinguish brain activity related to the
test saccade from that related to the returning saccade.
Brain responses for each of the tasks were assessed for both groups
with ERfMRI and were subsequently compared. To measure performance, electro-oculograms32 (EOGs) were acquired immediately after functional
magnetic resonance imaging (fMRI) scans. We hypothesized that patients with
schizophrenia would exhibit reduced brain responses specifically during the
inhibitory tasks, either in brain areas involved in the generation of an inhibitory
signal (ie, the DLPFC, FEF, and supplementary eye fields [SEF]) or in the
transmission of this signal toward brainstem structures (ie, basal ganglia
connections).33-39
SUBJECTS AND METHODS
SUBJECTS
Sixteen patients with schizophrenia (13 men and 3 women; mean ±
SD age, 27.9 ± 5.5 years) from the Department of Psychiatry at the
University Medical Center Utrecht, Utrecht, the Netherlands, participated
in this study. All patients met the criteria for schizophrenia according to
the DSM-IV,40 as assessed
with the Comprehensive Assessment of Symptoms and History41
(1 patient had disorganized schizophrenia, 11 had paranoid schizophrenia,
3 had schizophreniform disorder, and 1 was undifferentiated; mean ±
SD duration of illness, 29 ± 19 months), and were screened for severity
of present symptoms using the Positive and Negative Syndrome Scale (PANSS)
(mean ± SD sum of positive items, 13.3 ± 3.9; sum of negative
items, 15.2 ± 3.9; sum of generalized items, 29.9 ± 6.6).42 Every patient was taking a stable dose of atypical
neuroleptic medication (clozapine: n = 7, with a mean ± SD daily dose
of 200 ± 87 mg; olanzapine: n = 8, with a mean ± SD daily dose
of 11.3 ± 6.4 mg; quetiapine fumarate: n = 1, with a daily dose of
450 mg). The control group consisted of 17 healthy subjects (10 men, 7 women;
mean ± SD age, 25.9 ± 4.1 years). None of the subjects in the
control group exhibited any signs of a major psychiatric disorder according
to the Mini-International Neuropsychiatric Interview.43
All participants were right-handed according to the Edinburgh Handedness inventory44 (mean ± SD number of patients, 0.84 ±
0.14; number of controls, 0.84 ± 0.18). There was no significant difference
in educational level between the groups (mean ± SD number of patients,
12.1 ± 2.3 years; number of controls, 13.1 ± 2.0 years). A history
of substance abuse or major neurologic illness resulted in exclusion from
the experiment, as did metal implants. All subjects gave their informed consent
for participation, approved by the Human Ethics Committee of the University
Medical Center Utrecht.
PROCEDURE
The oculomotor task consisted of 3 parts (Figure 1): prosaccade (PRO), antisaccade (ANT), and active fixation
(FIX). It was performed while in the scanner and during additional EOG recordings.
A personal computer, rear projection screen, and video projector system were
used for task display. The beginning of each trial was time-locked to the
fMRI scans. By doing this, the return saccade was delayed enough to separate
the corresponding BOLD response from that of the response of interest, namely
the first eye movement (in the image analysis, the 2 BOLD curves were mathematically
uncorrelated). A new stimulus was triggered by the scanner for every ninth
scan, thereby generating a fixed stimulus interval of 12.9 seconds and giving
the stimulus-related BOLD signal time to return to baseline.45
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Figure 1. Schematic display of tasks performed
in the scanner. Each trial consisted of 1 saccadic event. The 4 black frames
(from left to right) show the computer display changes within 1 trial, with
the timing (in milliseconds) shown at the top. A trial started with the disappearance
of the cross (1.2° visual angle) at t= 0, followed
by a white square (1.2° visual angle) after 200 milliseconds appearing
randomly 9.0° to the left or right. After 3000 milliseconds, the square
disappeared and the cross reappeared. Dotted lines show the required viewing
direction. All trials followed this scheme, but the instructions changed every
17 trials. The 3 instructions (tasks) are shown above each other: PRO, prosaccade;
ANT, antisaccade; and FIX, fixation. Note that the difference was present
only during the appearance of the square (third frame from the left).
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Instructions for all tasks were given verbally prior to the start of
the experiment and included the following: (1) PRO: "From central fixation
look toward the square as quickly as possible when it appears. Look back to
the fixation cross when the square disappears and the fixation cross reappears
in the center"; (2) ANT: "When the square appears, look in the opposite direction
as quickly as possible, without looking toward the square. Look back to the
fixation cross when the square disappears and the fixation cross reappears
in the center"; and (3) FIX: "Keep looking at the location of the fixation
cross when it disappears, and do not move toward the square." At the beginning
of each new block of 17 stimuli, the task instructions were changed. There
were 3 blocks per task making a total of 9 blocks, which were presented in
a semirandomized sequence (PRO-ANT-FIX-ANT-PRO-FIX-PRO-FIX-ANT).
A similar oculomotor task with EOGs immediately followed the fMRI session
to measure subject task performance. Stimulus visual size was slightly reduced
(0.8° visual angle), as was visual distance between central fixation and
the peripheral square (7.0° visual angle). To avoid fatigue, the interstimulus
interval was shortened to 3 seconds, of which 1.8 seconds were used for central
fixation and 1.2 seconds for peripheral square display. All 51 stimuli for
each task were presented in 1 block. Blocks were presented in a PRO-ANT-FIX
sequence. Subjects were seated in a near-dark room in front of a VGA monitor.
Electro-oculographic data for horizontal saccades were acquired using surface
electrodes at a sampling rate of 500 Hz. Data were processed offline with
the aid of a custom nonautomated EOG analysis program. Onset latencies were
determined for all saccades. Any initial movement of the eyes in the wrong
direction (depending on the task) with a latency longer than 100 ms was counted
as an error. Any stimulus-related saccades during FIX were counted as errors.
IMAGE ACQUISITION
All images were obtained with a clinical scanner (ACS-NT 1.5T; Philips
Medical Systems, Best, the Netherlands) with fast gradients (PT6000). The
head was held in place with a strap and padding. Structural and functional
images were acquired in transverse orientation from the same section of the
brain (Figure 2). For functional
scans, a 3D-PRESTO pulse sequence46 was used
with following parameters: echo time, 36 milliseconds; repetition time, 24
milliseconds; flip angle, 10°; matrix, 48 x 64 x 24; field
of view, 192 x 256 x 96 mm; voxel size, 4-mm isotropic; scan duration,
1.43 seconds per 24-slice volume. Immediately after functional scans, an additional
PRESTO scan of the same volume of brain tissue was acquired with a high (30°)
flip angle (FA30) for the image registration routine. A total of 1620 functional
volumes were acquired per subject.
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Figure 2. Volume of brain scanned with functional
magnetic resonance imaging (fMRI). Typical fMRI scan volume of 24 contiguous
slices, shown on top of the midsagittal slice of the anatomical volume for
1 subject. Scans were acquired as 3-dimensional volumes in transverse orientation
and covered almost the whole brain.
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DATA ANALYSES
Data analysis of fMRI scans was done with custom-written programs in
PV-Wave using the International Mathematical and Statistical Library routines
(Visual Numerics Inc, Boulder, Colo). The last functional volume was registered
to the FA30 volume. Next, all fMRI volumes were registered to the last functional
volume using a least-squares difference criterion.47
The structural scan was also registered to the FA30 scan, thereby providing
spatial alignment between the structural scan and the functional volumes.46 Only the scans acquired during stimulus trials were
analyzed. A 3-dimensional gaussian filter (8-mm full width at half maximum;
Visual Numerics Inc) was applied to all fMRI volumes. To decrease low-frequency
noise, for each voxel the offset and linear trend were calculated for every
set of 9 scans belonging to a single stimulus, using a standard regression
procedure. The residuals were used for further analyses.
Next, 3 t values per voxel were obtained from
a standard linear multiple regression procedure with a factor matrix that
contained the 3 factors representing stimulus-related changes in BOLD signal
during PRO, ANT, and FIX, respectively. For each trial in the matrix, the
BOLD curve was modeled using a curve derived from a previous (unpublished)
study. This curve has a skewed gaussian shape (with a kernel of 6 seconds)
that peaks at 5 seconds. Thus, the 3 t values for
each voxel represented the presence and magnitude of the stimulus-contingent
BOLD response during the 3 tasks for each subject. Finally, all the now coregistered t volumes and structural scans were spatially normalized
in Talairach orientation to enable groupwise comparisons.48
To test for specific effects of inhibition and of illness on inhibition
in the brain activity maps, a multivariate repeated-measures analysis was
applied. Four independent comparisons were tested for significance for each
voxel by first calculating the within-subject contrast value and subsequently
comparing these contrast values between the groups. Four comparisons of interest
represented overall activity (activity during all conditions for both groups),
overall effect of illness (differences between groups for all conditions),
overall effect of inhibition (ANT and FIX combined vs PRO for both groups),
and effect of illness on inhibition (differences in effect of inhibition between
groups). The group effects were converted to t values49 and were subsequently tested for significance (P < .05) with Bonferroni correction for the number of
voxels (approximately 14 000, resulting in a critical t value of 4.51 for each voxel). Thus, for the assessment of significant
effects, a threshold of t = 4.51 was applied to all
of the image analysis results.
RESULTS
EOG PERFORMANCE
The EOG results indicate that patients did not perform worse than controls
on the PRO task in terms of reaction time (t29 = 0.38; P = .71) or error rate (t29 = -0.23; P = .82). However,
in the ANT task the error rate was significantly increased (Figure 3A), in the window of 100 to 180 milliseconds (t28 = 1.90; P = .03), but not in
other time windows. In addition, patients made more saccades (distraction)
during FIX (t29 = 1.70; P = .03) (Figure 3B). The
reaction time of correct antisaccade responses was increased (t29 = 1.92; P = .05) (Figure 3C). Thus, patients were moderately
impaired in inhibiting saccades. When the data were summed across all tasks,
patients made more eye movements overall, within a time window of -100
to 500 milliseconds (Mann-Whitney U test: z = 2.36; P = .02).
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Figure 3. Performance on the tasks, assessed
with electro-oculograms for patients (n = 15) and control subjects (n = 14).
A, Antisaccade distractibility, expressed as percentage of the number of trials
in which the first eye movement occurred, for each time window. The error
rate across all trials was 18% for control subjects and 21% for patients.
B, Distractibility rates of patients and control subjects during active fixation.
C, Reaction time of patients and control subjects on antisaccades and prosaccades
(> 100 milliseconds). Asterisks denote a significant difference between patients
and controls (P= .03, P=
.03, and P= .05 in A, B, and C, respectively). Performance
of controls is shown in the light bars; performance of patients is reflected
in the dark bars. Error bars represent the SEM.
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fMRI: SACCADE-RELATED ACTIVITY
The maps corresponding to the tested contrasts are shown in Figure 4. The overall activity pattern, including
all tasks and subjects, is extensive (Figure
4A). In addition to extensive occipital activation, the detected
regions of the oculomotor system included the PEF in Brodmann area (BA) 39
and BA 40, FEF at the intersection between the superior frontal and precentral
fissure extending dorsally into the lateral part of BA 6, and SEF in the medial
part of BA 6. Further activity was found in the anterior cingulate cortex
and anterior insula.
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Figure 4. Active voxels superimposed on
the averaged anatomical scan. The numbers displayed in the top left corner
of each slice correspond to Talairach z coordinates.
Only the most informative slices are shown. Colored voxels represent significant
effects at P < .05 (Bonferroni-corrected). A,
Response pattern for all 3 tasks combined. Red voxels are those that were
active in both groups (patients and controls, main effect of visual processing).
Yellow indicates regions where there is a difference between patients and
controls (in which controls were more active than patients). Analyses of each
group showed that patients exhibited significant activity in the yellow regions
but less than the controls. B, Response pattern for the inhibition conditions.
Red voxels are those that were selectively active during saccadic inhibition
(as opposed to prosaccades) in both patients and controls. Blue indicates
the regions where activity decreased during inhibition in both groups. Yellow
voxels represent the key finding, namely the significant difference between
patients and controls during the inhibition of saccades (in which patients
were less active than controls).
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Compared with controls, patient brain activity was significantly reduced
in the visual cortex and, to a lesser extent, in all other oculomotor regions
(PEF, FEF, and SEF) as well as the anterior cingulate cortex (Figure 4A). However, when examining the overall group t map of the patients, significant activity was found in all of these
regions, indicating that activity was relatively reduced but not absent. This
is shown for the visual cortex in Figure 5.
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Figure 5. Averaged blood oxygenation level–dependent
(BOLD) responses and corresponding t values during
prosaccades and antisaccades, averaged across the activated voxels in the
occipital lobe for control subjects (n = 17) and patients with schizophrenia
(n = 16). Because of the normalization of values in multiple regression analyses,
the BOLD response amplitude is presented in arbitrary units (AU).
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fMRI: INHIBITION-RELATED ACTIVITY
In the overall inhibition map, a significant BOLD response occurred
in the lateral occipital lobe (visual area [V] 5), FEF, and SEF (Figure 3B). Interestingly, the BOLD response
decreased in some subregions of the occipital lobe (V1 and V2). The interaction
between inhibition and illness was significant only in the striatum bilaterally.
More specifically, 4 areas were found with the following Talairach x, y, and z coordinates: left putamen (-23,
8, 7); right putamen (26, 4, -3); left caudate body (-10, 1, 10);
and right caudate body (13, 1, 10).
Further inspection revealed that in controls the striatum responded
(selectively) to the inhibition tasks but that this response was absent in
patients (Figure 6). This difference
was also present in the individual inhibition t maps.
Whereas 12 of 17 control subjects showed activated voxels (t > 3.0) in the striatum, the same was true for only 5 of 16 patients
( 21 = 3.69; P = .03).
In further exploring the data, we looked at lower thresholds in the inhibition
maps (t31 > 3.5) and observed additional
reduced responses in patients in the thalamus, intraparietal area, and BA
44.
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Figure 6. The scanner plot shows the mean t value in the striatum of the difference in brain activity
between antisaccades (ANT) and prosaccades (PRO) and between fixation (FIX)
and prosaccades for each subject. For these mean t
values, voxels were selected only if an interaction between illness and inhibition
was found in the group comparison. The plot shows that the patients fail to
activate the striatum during both inhibition tasks (ANT and FIX). Controls
are indicated with triangles; patients, with squares.
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CLINICAL VARIABLES
Clinical variables (positive, negative, and general PANSS scores as
well as type and dose of medication) did not correlate significantly with
measures of performance or striatal activity.
COMMENT
In accordance with other studies, patients with schizophrenia were impaired
on the ANT task, which requires the inhibition of prepotent saccades. The
imaging results suggest that this impairment is associated with a failure
to engage striatal structures. In healthy volunteers, we demonstrated significant
activation in a network of regions that are known to subserve saccadic eye
movements.24, 33-34,36-37,39
Furthermore, the inhibition of saccades was found to involve the SEF (the
anterior aspect of the supplementary motor area), FEF, and striatum, confirming
previous studies.33-37
Thus, the obtained brain activity maps for each task demonstrated that the
event-related fMRI procedure was adequate.
Although patients with schizophrenia showed activity in the same regions
as the controls during all tasks combined, overall the magnitude of activity
was smaller. Because reduced activity occurred in all oculomotor-related areas,
patients with schizophrenia generally exhibited either lower amplitudes of,
or more variability in, the BOLD response. The latter explanation is supported
by the finding that the patients made more eye movements in the period between
100 milliseconds before and 500 milliseconds after a stimulus during the EOG
test. A higher incidence of random eye movements during the fMRI experiment
may have increased variability by adding BOLD responses to the data, resulting
in increased noise. The fact that inhibition-related brain activity was present
in FEF and SEF in both patients and controls indicates that patients complied
with the tasks when undergoing scans. This further indicates that the observed
difference between patients and control subjects in the striatum does not
reflect merely a behavioral difference caused by a higher percentage of incorrect
prosaccades in patients during inhibition.
The relevance of the striatum for oculomotor functioning has been studied
extensively. The striatum represents the major input site of the subcortical
oculomotor circuit. These subcortical regions transfer input from the frontal
cortex downward to the substantia nigra pars reticulata (SNr).24, 50-51
From the SNr, ascending fibers feed back to the cortex through the thalamus,
whereas the descending efferents provide an escape route from the basal ganglia-thalamocortical
loop by projecting to the SC.29, 52-53
The striatum is capable of exerting both an inhibitory and an excitatory
influence on the SNr by means of 2 parallel pathways. The inhibitory pathway
projects to the SNr directly,54 and the excitatory
pathway passes through the external globus pallidus and subthalamic nucleus.53, 55 With these 2 connections, the striatum
can facilitate or suppress overt oculomotor behavior and does so by transiently
modulating the tonic inhibitory control that is exerted by the SNr on the
SC.29, 56 The suppressed neuronal
activity in the SC during saccadic inhibition probably reflects an effort
to avoid fast reflexive saccades triggered by the SC through afferents of
the nuclei of the optic tract or parietal regions.2
Accordingly, the inhibition of saccades requires adequate input from a network
that feeds into the SNr, which is most likely initiated in the frontal cortex.
Indirect evidence of the striatum's possible role in saccade inhibition
in human subjects is provided by the fact that distractibility rates are increased
in patients with degenerative diseases affecting the basal ganglia, such as
Huntington disease.57 This indicates that although
direct connections also exist between the frontal cortex and the SC (and the
reticular formation), providing an alternative means of inhibitory control,24 impaired striatal function does affect saccadic inhibition.
Tardive dyskinesia in patients with schizophrenia has been shown to enhance
distractibility, which has been ascribed to altered  -aminobutyric acid
and dopamine function in the basal ganglia.58-59
The striatum has been implicated in schizophrenia in other studies. The clinical
efficacy of neuroleptics is linked to dopamine D2 receptors, which are present
in high concentrations in the striatum, and both medicated and unmedicated
patients demonstrate abnormal striatal metabolic rates.26, 60
Alternatively, dysfunction of the frontostriatal-thalamic loops could
contribute to cognitive and psychotic symptoms of schizophrenia.61
Because the frontal regions are involved in the generation of a "stop" signal,
frontostriatal connections play an important role in the downward transmission
of this signal.22-23 A deficit
in functional connectivity between the frontal lobes and the striatum has
been demonstrated in schizophrenia in concordance with a reduction in interconnecting
white matter between these areas.62
Surprisingly, in this study there was no indication that abnormal activity
in the frontal lobes contributed to the deficit. Healthy volunteers did not
exhibit a BOLD response in the DLPFC despite of its postulated involvement
in saccade inhibition.27, 38, 63
Because the DLPFC did not respond to the stimuli in a transient manner, it
may have been constantly active during inhibition tasks, thereby remaining
unnoticed in this experiment and making the detection of abnormal activity
in patients difficult. However, the role of the DLPFC in saccadic inhibition
has not been consistently confirmed by imaging studies.27-28,37, 64
Our study is limited in several respects. For one, eye movements were
not recorded in the scanner. Performance measurements were acquired outside
the scanner immediately after the fMRI session because at the time of the
fMRI experiment, we did not have access to an MRI-compatible eye-tracking
device. Also, the task was not the same during and after scanning; the interstimulus
interval was shortened to minimize the overall length of the experimental
session. This shorter interval may have affected performance because it may
be more stimulating and alerting for subjects. However, the main reason for
the offline recording of eye movements was to determine whether all subjects
were capable of performing the task as intended and whether the patient group
would display a deficit, as was expected on the basis of reported findings
in the literature. The results indicated that all subjects were capable of
performing the tasks and that the patients made more errors. The brain activity
maps showed that most of the brain regions that were active in controls were
also active in patients during all tasks, albeit at lower levels, providing
indirect evidence that patients did perform the tasks and that the difference
in brain activity was not due to noncompliance. Another limitation is that
in maximizing sensitivity to transient brain responses to examine the dynamics
of the involved network, we did not measure sustained brain activity during
the tasks. It would be worthwhile to design studies that allow the assessment
of both types of responses simultaneously. Responsivity of one region can
conceivably depend on the tonal activity of another.65
Finally, because we tested patients who were receiving medication, one
could argue that the results are associated with medication effects. Although
we do not know whether the observed abnormalities of brain function in the
striatum in our patients are the result of medication, we do know from the
literature that the behavioral saccade inhibition abnormality observed in
patients with schizophrenia are not explained by medication.16, 66-67
Therefore, if the brain activity effect were attributed to medication, the
observed abnormality in brain function would bear no relevance to the behavioral
deficit in saccadic inhibition. However, we show that the striatum is actively
involved in saccade inhibition in healthy subjects, so any medication effects
on this region would be expected to have behavioral consequences.
In summary, we have shown that the network that subserves the inhibition
of prepotent saccades may be dysfunctional in schizophrenia at the level of
the striatum. Because saccade inhibition deficits may be regarded as biological
markers for schizophrenia,66-67
fMRI images of the neuronal circuits underlying saccade inhibition could be
a useful tool to identify those at risk for schizophrenia.8, 68
AUTHOR INFORMATION
Submitted for publication December 7, 2000; final revision received
May 31, 2001; accepted June 26, 2001.
Corresponding author and reprints: Nick F. Ramsey, PhD, Department
of Psychiatry, University Medical Center Utrecht, Heidelberglaan 100, Room
A01126, Utrecht 3584 CX, the Netherlands.
From the Department of Psychiatry, University Medical Center Utrecht,
Utrecht, the Netherlands.
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