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triatal Dysfunction in Schizophreniand Unaffected Relativesatthijs Vink, Nick F. Ramsey, Mathijs Raemaekers, and René S. Kahn

ackground: Schizophrenia has been frequently associated with impaired inhibitory control. Such control is known to involve the striatum.ere, we investigate whether impaired inhibitory control is associated with abnormal striatal activation in schizophrenia. First-degree

elatives of patients were also tested to examine whether striatal abnormality is associated with schizophrenia, or with the risk for the illness.ethods: Both functional MRI and behavioral data were acquired during a task designed to invoke inhibitory control in 21 patients,

5 unaffected siblings, and 36 matched controls. Subjects must refrain from responding to designated stop cues occurring within aeries of motor cues. Subjects could anticipate the occurrence of stop cues as the likelihood of these cues increased in a linear fashionhroughout the task.esults: Control subjects showed striatal activation while responding to motor cues. This activation increased in a linear fashion when

he likelihood of having to inhibit the response was increased. Both patients siblings did not show anticipation-related increase in eithertriatal activation. However, only patients showed behavioral impairments.onclusions: Striatal abnormalities occur in schizophrenia patients and unaffected siblings. Thus striatal abnormalities may beelated to an increased (genetic) risk to develop schizophrenia.

ey Words: Functional MRI, Schizophrenia, striatum, genetics,nhibition

rom the time of Bleuler (1911), schizophrenia has beenlinked to impaired inhibitory control. For example, pa-tients make more errors during inhibition of strongly

utomated (i.e., prepotent) eye movements (Crawford et al 1995,002; Fukushima et al 1988, 1990; Raemaekers et al 2002),istractor items (Vink et al 2005), word reading during the Stroopask (Henik et al 2002), and motor responses (Kiehl et al 2000;eisbrod et al 2000). Impairments in inhibitory control have also

een reported on more basic levels of information processing,uch as P50 (Adleret al 1982; Clementz et al 1998), prepulsenhibition (Braff et al 2001; Cadenhead et al 2000), and latentnhibition (Lubow et al 1987; Swerdlow et al 1996). Impairednhibitory control in schizophrenia has been linked to thoughtisorder (McCarley et al 1999), auditory hallucinations (Waters etl 2003), and delusions (Peters et al 1994, 2000).

A typical paradigm to measure inhibitory control is thetop-signal task (Logan and Cowan 1984). This task tests thebility to block an intended movement at the last moment and asuch represents a test for function of inhibitory pathways inerebral motor systems. Compared with the GO/no go paradigm,he time between motor stimulus and the stop-signal can bearied, allowing for a manipulation of task difficulty on anndividual level. In the stop-signal task, a series of motor cuesi.e., trials that require a button press) is presented with a fixednterval to which subjects must respond by pressing a button asuickly as possible. Some of the cues are followed by a stop cueignaling the subject to cancel the button press (i.e., STOP trials).he delay between motor and stop cue is adjusted to makeancellation difficult (Logan and Cowan 1984). Schizophrenia

rom the Department of Psychiatry, Rudolf Magnus Institute of Neuro-science, University Medical Center Utrecht, Heidelberglaan, Utrecht, theNetherlands.

ddress reprints requests to Nick F. Ramsey, Rudolf Magnus Institute ofNeuroscience, University Medical Center Utrecht, Department of Psychi-atry, Heidelberglaan 100, 3584CX Utrecht, the Netherlands. E-mail:N.Ramsey@azu.nl.

eceived July 25, 2005; accepted November 17, 2005.

006-3223/06/$32.00oi:10.1016/j.biopsych.2005.11.026

patients typically fail to cancel button presses more often thanhealthy control subjects (i.e., fail at stop trials; Kiehl et al 2000;Weisbrod et al 2000). There are several possible causes for thisreduced performance, but the most likely is that patients do notanticipate the occurrence of stop cues (Heimberg et al 1999).

To examine the neural mechanisms involved in inhibition ofmotor responses, we designed an fMRI experiment (Vink et al2005). We previously found that in healthy volunteers, thestriatum was activated when a response had to be blocked.Moreover, success of inhibiting responses was strongly corre-lated with the magnitude of activity in this region. We also foundthat the striatum was more active when subjects anticipated stopcues within a series of motor cues, compared with a series whenno stop cues occurred. Finally, the level of activation within thestriatum increased as the likelihood of a stop cue increased.These findings indicate that the striatum plays an important rolein inhibitory control—not only during inhibition of responses butalso in the anticipation of inhibition.

To investigate whether impaired inhibitory control is associ-ated with abnormal striatal activation in schizophrenia, wepresented patients with the test just described. We used themotor inhibition task (Vink et al 2005) to visualize brain activa-tion during and before response blocking (i.e., anticipation-related activity). Given that schizophrenia patients performpoorly in tasks that require inhibition of strongly automatedresponses, we expected to find decreased activation in thestriatum in these patients. Furthermore, if patients fail to antici-pate the occurrence of stop cues, activation in the striatumshould not increase with increasing stop cue likelihood.

An important question is whether any abnormality is associ-ated with the illness itself or with the risk for that illness. Toaddress this issue, we performed a second study in which weincluded unaffected siblings of schizophrenia patients. If abnor-mal activation of the striatum is related to the (genetic) risk ofdeveloping schizophrenia, then striatal activation should beabnormal in siblings as well.

Methods and Materials

SubjectsWritten informed consent was obtained from all participants

in accordance with the Declaration of Helsinki. The ethical

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ommittee of the University Medical Center Utrecht approved therotocol. Demographic characteristics are presented in Table 1.ealthy control subjects were matched to the patients or siblingsn gender, age, and years of parental education. All subjectsere right-handed as assessed by the Edinburgh Handedness

nventory (Oldfield 1971). Healthy subjects for both studies werecreened for any physical or mental disorder (Axis I or II) usinghe MINI-PLUS (Mini-International Neuropsychiatric Interview;heehan et al 1998). None of the subjects were related to eachther. All subjects were Caucasian.

Schizophrenia Study. 21 schizophrenia patients (4 inpa-ients, 17 outpatients) and 21 matched healthy control subjectsarticipated in this study. All patients fulfilled the criteria ofchizophrenia (DSM-IV), which was assessed using the Compre-ensive Assessment of Symptoms and History interview (CASH;ndreasen 1987). Patients were stable on atypical neurolepticsolanzapine, 10 patients, range 2.5–25 mg; clozapine, 6 patients,ange 250–500 mg; quetiapine, 2 patients, 50–600 mg; risperi-one, 3 patients, 1–3 mg). Average illness duration was 6.9 years� 4.8 years).

Siblings Study. Participants in the study included 15 healthyontrol subjects and 15 unrelated siblings of schizophreniaatients. None of the siblings suffered from any physical orental disorder according to the MINI-PLUS.

ask and ProcedureThe motor inhibition task is a modification of the stop-signal

aradigm (Logan and Cowan 1984; Vink et al 2005). Stimuli wereresented in five series of 120 trials, alternated with 30-sec resteriods. Each series, called GO/STOP, consisted of motor trialsGO trials: 80%) and STOP signal trials (STOP trials: 20%). TheseO/STOP series were preceded and followed by a series con-

isting of 20 GO trials (GO ONLY). Stimuli were projected ontoscreen placed across the bore of the magnetic resonanceagnet 1.8 m from the subjects’ eyes. Subjects observed the

creen through a mirror placed above their eyes. Three plus signsormed the background that was displayed continuouslyhroughout the task (see Figure 1). Each trial consisted of theeplacement by an X of either the left or the right plus sign,eaving the other two plus signs in place. Upon stimulus presen-ation a response had to be made by pressing the left or rightutton of the response box, as fast as possible using their righthumb. The stimulus was presented for 800 msec, in which timeresponse had to be made if the trial was a GO trial. Next, theisplay was cleared, leaving the background in place for 700sec. STOP trials were presented pseudo-randomly between theO-trials during a GO/STOP block, so that at least two but noore than six GO trials separated subsequent STOP trials. STOP

rials differed from GO trials in that shortly after the motor

able 1. Selected Demographic Variables

ariable

Schizophrenia Study

Patients(n � 21)

Control Subjects(n � 21) Test Valu

ge (years) 28 � 6.5 27 � 5.8 t(40) � .7ale/Female 11/10 12/9 �2 � .0

ducation Parents (years) 13.1 � 2.2 13.3 � 2.5 t(40) � .2

Data are given as mean � standard deviation.EHI, Edinburgh Handedness Inventory; PANSS, Positive and Negative Sy

timulus, a STOP signal appeared, which instructed the subject

not to respond to that motor stimulus. The STOP signal consistedof squares presented around the stimulus and the two remainingplus signs (see Figure 1). The delay between motor stimulus andSTOP signal was adjusted online during the task, for eachindividual subject separately, so that STOP difficulty was adaptedto actual individual performance on the STOP trials. Targetaccuracy on STOP trials was set to 50%. If accuracy fell below50%, 10 msec were subtracted from the delay time, makingstopping easier. Ten milliseconds were added if accuracy wastoo high. No change was made if accuracy was 50% (for moredetails, see Vink et al 2005). This way, differences in performanceamong the experimental groups was minimized.

Image AcquisitionBrain imaging data were collected on a 1.5-T Philips ACS-NT

MRI scanner (Philips Medical Systems, Best, the Netherlands)with fast gradients (PT6000). The head was held in place with astrap and padding. Structural and functional images were ac-quired in transverse orientation from the same section of thebrain. For functional scans, a navigated 3D-PRESTO pulse sequence(Ramsey et al 1998) was used with the following parameters: echotime/repetitiontime 35/24 msec, flip angle 10°, matrix 48 � 64 �24, field of view 192 � 256 � 96 mm, voxel size 4 mm isotropic,

Sibling Study

p ValueSiblings(n � 15)

Control Subjects(n � 15) Test Values p Value

.455 35 � 11.3 33 � 11.0 t(28) � .36 .719

.757 8/7 7/8 �2 � .133 .715

.770 11.9 � 2.2 13.9 � 2.1 t(28) � 1.77 .087

e Scale; SPQ, Schizotypal Personality Questionnaire.

Figure 1. Schematic representation of the task. (A) Sequence of events forthe GO ONLY task consisting of only motor trials. A screen with the word“PRACTICE” was presented to indicate the type of task to the subject. Fixa-tion was followed by a stimulus presented in the location of either the rightor left plus sign, requiring a right or left button press response, respectively.(B) Similar sequence of events for the GO/STOP task, which was indicated tothe subject by the word “TASK.” In 20% of the motor trials, a STOP signalconsisting of three open squares surrounding the stimulus and two plussigns, was presented after a variable delay following stimulus presentation.Subjects were instructed to respond to the motor trials but to withhold their

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can duration 1500 msec per 24-slice volume. Immediately afterunctional scans, an additional PRESTO scan of the same volumef brain tissue was acquired with a high (30°) flip angle (FA30)or the image coregistration routine. For each subject, 920unctional images were acquired.

ehavioral Data AnalysisA repeated-measures general linear model (GLM) analysis

ith task condition as within and group (2 levels) as between-ubject factors was performed to determine differences amonghe groups in overall reaction times on GO trials and accuracy onTOP trials. In addition, a repeated-measures GLM analysis withO trial condition (5 levels) as the within-subject and group (2

evels) as the between-subjects factor was performed to test forifferences in reaction time increase on GO trials preceding aTOP trial.

MRI Data AnalysisFor data analysis of fMRI scans, in-house developed soft-

are and software developed by the Montreal Neurologicalnstitute (MNI, Canada) was used. The data were analyzedsing the following strategy. Step 1: individual data sets werereprocessed to allow statistical analysis. To correct for headovement during scanning, all functional scans were regis-

ered to the FA30 volume (Ramsey et al 1998) using aigid-body affine transformation (Thevenaz et al 1998). Next,he anatomic image (i.e., T1-weighted) was registered to theA30 using a least-squares difference routine (Thevenaz et al998), so that functional and anatomical images were spatiallyligned. The individual volumes were spatially registered to a1-weighted MNI standard brain to enable groupwise com-arisons, using transformation parameters of the MNI regis-ered anatomic volume. A three-dimensional Gaussian filter (8m full width at half maximum) was then applied to these

unctional volumes.Step 2: preprocessed individual data sets were analyzed

sing two separate multiple-regression analyses (see Figure). The first analysis was performed to obtain brain activationelated to each of the separate task conditions. For thisurpose, hemodynamic responses during all the task condi-ions that were GO trials from GO ONLY, GO trials fromO/STOP series, correct STOP trials, and incorrect STOP trialsere modeled separately (see Figure 2A). The second analysisas performed to obtain brain activation related to each of theO trials within the GO/STOP series. The analysis focused on

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the hemodynamic responses in anticipation of a STOP trial, bymodeling each of the GO trials separating two consecutiveSTOP trials separately (Figure 2B). Because at least two but nomore than six GO trials separated consecutive STOP trials, thechance that a GO trial would become a STOP trial (i.e., a STOPsignal would be presented) increased as more GO trialspreceded a STOP trial (see Figure 2B). The design matrixconsisted of five factors modeling each one of the GO trialsfrom the GO/STOP series separately (i.e., the first two GOtrials following a STOP trial were combined because STOPlikelihood is 0% in both trials). The GO ONLY series and STOPtrials were modeled using separate factors (see Figure 2B). Inboth analyses, a correction for drifts in the signal was made byincluding a high-pass filter consisting of low-frequency co-sines (not shown in the figure). Furthermore, a factor model-ing mean volume intensity was included (not shown in thefigure). Factors modeling correct and incorrect STOP trialswere based on individual performance.

Step 3: a group analysis was performed to generate groupactivation maps using the pooled standard deviation approach(Worsley 1994). Using the individual data (i.e., regressor coeffi-cients) from the first analysis (see Figure 2A), group comparisonswere made to test differences between the groups during the GOONLY versus GO/STOP task. These whole-brain group differ-ences were tested for significance (p � .05) with Bonferronicorrection for the number of voxels (approximately 16,000,resulting in a critical Z value of 4.5 for each voxel).

Step 4: brain areas that are critically involved in controlledmotor processing (i.e., regions of interest [ROIs]) were function-ally defined. To obtain these ROIs, a whole-brain group analysiswas performed contrasting activation during GO trials from theGO/STOP series with that of the GO trials from the GO ONLYseries (i.e., GO/STOP � GO/ONLY). The resulting statisticalgroup map hence contained the functionally defined ROIs forcontrolled motor processing. This ROI group map was obtainedfrom the combined data of schizophrenia patients and theircontrol subjects. Thus, there was no bias toward either of thesegroups. This also allowed comparison of the data between theschizophrenia and sibling experiments. The ROI group map wasthresholded at t � 3.09 (i.e., p � .001, not corrected for multiplecomparisons).

Step 5: the data within each of the ROIs were analyzed for allgroups separately. The effect of increasing STOP signal likeli-hood was assessed using the individual brain activation data (i.e.,

Figure 2. Samples of design matrices for image anal-ysis (first 200 scans of a total of 920 scans). (A) Factorsfor the first multiple-regression analysis, used foridentifying regions associated with motor activityand with inhibitory activity. (B) Factors for the sec-ond multiple-regression analysis, used to measureeffects of expectation on activity in specific regions.The percentages reflect the chance of an upcomingSTOP cue. In the second analysis, both correct andincorrect STOPS are combined (ALL STOPS). SeeMethods and Materials for details.

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M. Vink et al BIOL PSYCHIATRY 2006;60:32–39 35

egressor coefficients) obtained from the second individual mul-iple-regression analysis (see Figure 2B).

esultserformance Data

Schizophrenia Study. Overall, healthy control subjects andatients did not differ in response speed to GO trials [F (1,40) �

424, p � .518]. Healthy control subjects showed a linear increasen reaction times on GO trials from the GO/STOP task as STOPikelihood increased, suggesting that healthy subjects respondedore cautiously when the chance of having to inhibit their

esponse increased [linear contrast; F (1,20) � 29.926, p � .001].chizophrenia patients did not show such a linear increase ineaction time [linear contrast; F (1,20) � 2.581, p � .124]. Thisifference between the groups was significant [repeated-mea-ures GLM, linear interaction; F (1,40) � 5.304, p � .027; seeigure 3A], suggesting that schizophrenia patients did not antic-pate the occurrence of STOP trials. Overall accuracy on STOPrials did not differ between the groups [GLM, main effect of

igure 4. Effect of STOP signal likelihood on accu-acy (percent, standard error of the mean) for schizo-hrenia patients and their control subjects (A) andiblings and their control subjects (B) plottedgainst the increasing chance of a STOP signal (%).he chance of a STOP signal increases from 20%

after two motor trials) to 100% (after six motor trials;ee also Figure 2).

group; F (1,40) � 2.632, p � .113], confirming that performancecalibration was effective. Healthy subjects became more success-ful in withholding their response as the chance of a STOP signalwas higher [linear contrast; F (1,20) � 16.912, p � .001]. Inpatients, accuracy on STOP trials was not increased when thechance on a STOP signal increased [linear contrast; F (1,20) �1.742, p � .203]. This difference was significant [repeated-measures GLM, linear interaction; F (1,40) � 6.698, p � .014; seeFigure 4A], again suggesting that patients did not anticipate theoccurrence of STOP trials.

Sibling Study. Siblings and their control subjects did notdiffer in overall response speed [F (1,28) � .596, p � .446]. Bothsiblings and their control subjects showed a linear increase inreaction time as STOP likelihood increased [linear contrast,siblings: F (1,14) � 5.776, p � .031, control subjects: F (1,14) �35.527, p � .001]. This linear increase did not differ between thegroups [repeated-measures GLM, interaction, F (1,28) � .925, p �.344; see Figure 3B], indicating that both groups anticipated theoccurrence of STOP trials. Overall accuracy on STOP trials did

Figure 3. Effect of STOP signal likelihood on reactiontimes (mean � SEM) to motor trials for schizophre-nia patients and their control subjects (A) and sib-lings and their control subjects (B) plotted againstthe increasing chance on a STOP signal (%). GOONLY is included as a baseline measure. STOP signallikelihood increased from 0% (motor trial 1 and 2) to50% (motor trial 6).

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ot significantly differ between the groups [F (1,28) � 3.372, p �077], although the data showed a trend toward a difference. Inoth groups, accuracy levels on STOP trials linearly increased ashe chance of a STOP signal increased [linear contrast, siblings:(1,14) � 16.079, p � .001, control subjects: F (1,14) � 9.864, p.008], and this increase was similar for both groups [repeated-easures GLM, linear interaction, F (1,28) � 1.347, p � .256; seeigure 4B], again indicating that both groups anticipated theccurrence of STOP trials.

MRI Data: Whole-Brain Group ComparisonsPrior to the ROI analyses described later, whole-brain group

ontrasts were calculated for controlled motor processing (i.e.,O/STOP vs. GO ONLY; see fMRI Data Analysis, step 3).

Schizophrenia Study. No differences were observed be-ween schizophrenia patients and healthy control subjects forotor activation at a threshold of p � .05 corrected for multiple

omparisons. Lowering the threshold to p � .001, uncorrectedor multiple comparisons (i.e., t � 3.09), revealed slightly stron-er motor activation in the thalamus for the patients comparedith control subjects.

Sibling Study. No differences were detected between sib-ings and control subjects for motor activation at a threshold of

� .05 corrected for multiple comparisons. Lowering thehreshold to p � .001, uncorrected for multiple comparisons (i.e.,� 3.09), revealed slightly stronger motor activation in the

halamus for the siblings compared with control subjects.

MRI Data: Effect of STOP LikelihoodTo investigate the effect of anticipation on brain responses

i.e., magnitude of the blood oxygen level–dependent [BOLD]esponse), activity in the ROIs from the controlled motor-rocessing map was mapped against the likelihood of a STOPignal to occur. The chance of a STOP signal increased from 0%n the first two GO trials to 50% in the sixth GO trial (see Methodsnd Materials for details). The ROIs were obtained from the

roupwise contrast between GO trials from GO/STOP and GO

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ONLY and included right striatum, right insula, thalamus, and theanterior cingulate (see Figure 5, fMRI Data Analysis, step 4).Details of the ROIs are presented in Table 2. These ROIscorrespond to those reported in our previous study with healthycontrol subjects (Vink et al 2005). Only the thalamus was notfound in that previous study.

Schizophrenia Study. A repeated-measures GLM analysiswith ROI (4 levels) and STOP likelihood (five levels, rangingfrom 0% to 50%) as within-subject factors and group as between-subject factor revealed no significant overall difference betweenthe groups (F � 1). The group by STOP likelihood by ROIinteraction was significant [F (12,29) � 2.384, p � .028], however,indicating that the effect of STOP likelihood on mean ROI activitylevels differed between the groups. We therefore conductedrepeated-measures GLM analyses with STOP likelihood (fivelevels) as within-subject factor and group as between-subjectfactor for all four ROIs separately. In the insula, thalamus, andanterior cingulate, no differences between the groups werefound. In contrast, in the striatum, the difference between groupswas significant [F (1,40) � 6.767, p � .013; see Figure 6A]. Thiswas due to overall reduced striatal activation in patients. Thecontrol subjects exhibited an effect of expectation [linear con-trast; F (1,20) � 11.105, p � .003]. More important, in patients, asopposed to the control subjects, activity in the striatum was not

Figure 5. Overview of regions of interest obtainedfrom schizophrenia patients and their control sub-jects during motor trials from the GO/STOP com-pared with GO ONLY task (see fMRI Data Analysis,step 4).

Table 2. Characteristics of the Regions of Interest

Region of Interest Side BA No. Voxels X Y Z

Controlled Motor Processing(GO ONLY � GO STOP)

Striatum R 33 �15 11 �1Insula R 13 66 �34 19 0Thalamus L/R 135 0 �4 8Anterior Cingulate L/R 32 192 �3 17 35

X Y Z coordinates: center of mass in Talairach coordinates (in millimeters)of regions with significant activity (see Methods and Materials for details).

BA, Brodmann area; L, left; R, right.

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M. Vink et al BIOL PSYCHIATRY 2006;60:32–39 37

ffected by expectation [linear contrast; F (1,20) � .002, p � .969].his group difference was significant [repeated-measures GLM,

inear interaction of group by expectation; F (1,40) � 6.057,� .018].

Sibling Study. A GLM analysis, as described earlier, waserformed on the activation data in the striatum for siblings andheir healthy control subjects. Similar to the schizophrenia data,he groups did not differ in the insula, thalamus, and anterioringulate. Overall striatal activation levels did not differ betweenhe groups [F (1,28) � 1.752, p � .196]. However, the STOPikelihood by group interaction was significant [F (1,28) � 6.492,� .017], indicating that siblings showed no anticipation-related

triatal activity (Figure 6B). Indeed, we found a significant linearffect for healthy control subjects [F (1,14) � 11.263, p � .005],ut not for siblings [linear contrast; F (1,14) � .110, p � .745].

iscussion

The main finding of this study is that a striatal dysfunction wasound in both schizophrenia patients and unaffected first-degreeelatives. This striatal dysfunction was apparent during a task inhich the likelihood of having to inhibit a motor response

ncreased. In healthy control subjects, striatal activation increasedroportionally to the likelihood of having to inhibit a response.n contrast, in both schizophrenia patients and siblings, striatalctivation was unaffected by this likelihood. In addition the levelf striatal activation was reduced in patients compared withontrol subjects. Behaviorally, only control subjects and siblingsecame more cautious in responding and consequently becameore accurate in inhibiting their response as the likelihood ofaving to inhibit the response increased. Thus, despite a normalehavioral response in the first-degree relatives, we found theirtriatal activation to be abnormal. This latter finding suggests thatunctional brain measures may be a more sensitive marker ofgenetic) risk factors for the development of schizophrenia thanre behavioral measures.

Our results are consistent with the idea that schizophreniaatients suffer from impaired inhibitory control (Ford et al 2004;iehl et al 2000; Weisbrod et al 2000). Indeed, patients madeore errors compared with healthy control subjects on trials

equiring the inhibition of a strongly automated response (i.e.,

STOP cues) when STOP likelihood was high. Underlying thispoor performance may be the lack of expectation of such STOPcues in patients. Whereas healthy control subjects became morecautious in responding, response speed in patients was unaf-fected by an increasing chance of a STOP cue. Unaffectedsiblings, like healthy control subjects, showed increased reactiontimes in response to an increasing chance of a STOP cue. Inaddition, accuracy on STOP trials was similar to that of healthycontrol subjects. These results suggest that unaffected siblings, incontrast to patients, did anticipate STOP trials. Despite this nearto normal performance, we found abnormalities in striatal acti-vation in siblings. Siblings, like patients, showed no anticipation-related increase in brain activation (i.e., magnitude of the BOLDresponse amplitude). However, in contrast to the patients,overall striatal activation level in siblings did not differ from theircontrol subjects, whereas it was reduced in patients.

The question arises what the abnormal striatal function insiblings of schizophrenia patients signifies if performance isnormal. We argue that it may well mean that two mechanismscould be at play in schizophrenia with regard to inhibitorycontrol. The primary mechanism concerns a predisposition toabnormal function of striatum with regard to expectation, andthis is supported by the data presented here. The secondarymechanism would involve compensation for the striatal mal-function. Many systems in the brain consist of multiple paralleland overlapping circuits that can serve as backup systems(Vink et al 2005). It may well be that the striatal abnormality iscompensated for by other brain systems in siblings. The factthat schizophrenia patients exhibit poor performance wouldindeed indicate that compensatory mechanisms are no longeravailable as a consequence of the illness or, alternatively, ofmedication. Further research is needed to identify such com-pensatory mechanisms.

A large body of research exists on the role of the striatum inschizophrenia (for a recent review, see Tekin and Cummings2002), mainly because dopaminergic abnormalities have been amajor focus of schizophrenia research. Besides animal models(Lipska 2004; Swerdlow et al 2000) and postmortem studies(Joyce et al 1997), recent structural MRI (voxel-based morphom-

Figure 6. Effect of STOP signal likelihood on striatalactivation (arbitrary units (i.e. regression-coefficients)� standard error of the mean) for schizophrenia andtheir control subjects (A), and siblings and their controlsubjects (B) plotted against the increasing chance on aSTOP signal (%). GO ONLY is included as a baselinemeasure (see also figures 2 and 3).

etry) and functional MRI studies have shown striatal abnormali-

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ies. These data indicate changes in both gray matter (a.o., Ha etl 2004; McDonald et al 2004) and white matter density (a.o.akase et al 2004). Functional striatal abnormalities in schizo-hrenia have been reported by Raemaekers et al (2002), whohowed reduced striatal activation in schizophrenia patientsuring the inhibition of prepotent eye movements. Kumari et al2002) found reduced striatal activation during procedural learn-ng. Menon et al (2001) found reduced striatal activation duringmotor sequencing task. The striatum plays a role in controlling

he initiation and preparation of movements. It is the mainubcortical input region for the basal ganglia, receiving inputrom both the cortex as well as the thalamus (e.g., Alexander etl 1986). Projections from the striatum to the thalamus, and inurn the cortex, can be either excitatory or inhibitory, so thatngoing movements can be executed or inhibited when requiredy the context (Kaji 2001; Vink et al 2005). Our results indicatehat during the baseline motor task, the striatum functionsormally; however, when the task demands increase (i.e., whenTOP trials are intermixed with motor trials), striatal functioningecreases in both patients and siblings. Such a pattern mayeflect reduced cortical control over the striatum, rather than aysfunctional striatum.

The finding that the anterior cingulate is more active duringontrolled compared with baseline motor processing is consis-ent with the notion that the anterior cingulate is involved inigher cognitive functions such as error detection (Carter et al998; Garavan et al 2002) and action monitoring (Badgaiyan andosner 1998).

Although the current analysis showed no significant evidencef activation in other brain areas as possible compensatory areasn the siblings of schizophrenia patients, the cerebral compen-ating mechanism in siblings may involve activation changes inrain regions falling outside the selected regions of interest ofhis study. In the direct comparison of activation maps betweeniblings and their control subjects, however, no difference wasound. Further lowering of the statistical threshold may revealuch regions, but at the cost of increasing the number ofalse-positive voxels. The regions we selected appear to be stablever groups (schizophrenia patients and healthy control sub-

ects) and are in agreement with the regions we reported in therevious study (Vink et al 2005), indicating that we have selectedhe most relevant regions.

The overall reduction in striatum activity in patients could beaused by medication. All patients included in our study werereated with atypical neuroleptics. Before neuroleptic treatment,here appear to be no abnormalities in either striatal blood flowCorson et al 2002) or basal ganglia volume (Gunduz et al 2002)n schizophrenia patients. Siblings, who have an increased risk ofeveloping schizophrenia but did not receive any neurolepticedication also showed striatal abnormalities. We therefore

rgue that impaired striatal functioning may be related to agenetic) risk factor for the development of schizophrenia,ndependent of medication. Medication, or the illness itself, mayave an additional deteriorative effect on striatal functioning.

In conclusion, our study indicates that striatal abnormalitiesre present in schizophrenia patients and in unaffected siblings.triatal hypoactivity was associated with behavioral deficits inatients only, whereas siblings showed normal behavior, sug-esting some form of intact cerebral compensating mechanism.aken together, these findings suggest that striatal abnormalitiesay be related to a (genetic) risk factor for the development of

chizophrenia.

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Adler LE, Pachtman E, Franks RD, Pecevich M, Waldo MC, Freedman R (1982):Neurophysiological evidence for a defect in neuronal mechanisms in-volved in sensory gating in schizophrenia. Biol Psychiatry 17:639 – 654.

Alexander GE, DeLong MR, Strick PL (1986): Parallel organization of function-ally segregated circuits linking basal ganglia and cortex. Annu Rev Neu-rosci 9:357–381.

Andreasen NC (1987): The diagnosis of schizophrenia. Schizophr Bull13:9 –22.

Badgaiyan RD, Posner MI (1998): Mapping the cingulate cortex in responseselection and monitoring. Neuroimage 7:255–260.

Bleuler E (1911): Dementia Praecox or the Group of Schizophrenias. New York:International Universities Press.

Braff DL, Geyer MA, Light GA, Sprock J, Perry W, Cadenhead KS, et al (2001):Impact of prepulse characteristics on the detection of sensorimotorgating deficits in schizophrenia. Schizophr Res 49:171–178.

Cadenhead KS, Swerdlow NR, Shafer KM, Diaz M, Braff DL (2000): Modulationof the startle response and startle laterality in relatives of schizophrenicpatients and in subjects with schizotypal personality disorder: Evidenceof inhibitory deficits. Am J Psychiatry 157:1660 –1668.

Carter CS, Braver TS, Barch DM, Botvinick MM, Noll D, Cohen JD (1998):Anterior cingulate cortex, error detection, and the online monitoring ofperformance. Science 280:747–749.

Clementz BA, Geyer MA, Braff DL (1998): Poor P50 suppression amongschizophrenia patients and their first-degree biological relatives. Am JPsychiatry 155:1691–1694.

Corson PW, O’Leary DS, Miller, SD, Andreasen NC (2002): The effects ofneuroleptic medications on basal ganglia blood flow in schizophreni-form disorders: A comparison between the neuroleptic-naive and med-icated states. Biol Psychiatry 52:855– 862.

Crawford TJ, Bennett D, Lekwuwa G, Shaunak S, Deakin JF (2002): Cognitionand the inhibitory control of saccades in schizophrenia and Parkinson’sdisease. Prog Brain Res 140:449 – 466.

Crawford TJ, Haeger B, Kennard C, Reveley MA, Henderson L (1995): Saccadicabnormalities in psychotic patients. I. Neuroleptic-free psychotic pa-tients. Psychol Med 25:461– 471.

Ford JM, Gray M, Whitfield SL, Turken AU, Glover G, Faustman WO, et al(2004): Acquiring and inhibiting prepotent responses in schizophrenia:Event-related brain potentials and functional magnetic resonance imag-ing. Arch Gen Psychiatry 61:119 –129.

Fukushima J, Fukushima K, Chiba T, Tanaka S, Yamashita I, Kato M (1988):Disturbances of voluntary control of saccadic eye movements in schizo-phrenic patients. Biol Psychiatry 23:670 – 677.

Fukushima J, Fukushima K, Morita N, Yamashita I (1990): Further analysis ofthe control of voluntary saccadic eye movements in schizophrenic pa-tients. Biol Psychiatry 28:943–958.

Garavan H, Ross TJ, Murphy K, Roche RA, Stein EA (2002): Dissociable exec-utive functions in the dynamic control of behavior: Inhibition, errordetection, and correction. Neuroimage 17:1820 –1829.

Gunduz H, Wu H, Ashtari M, Bogerts B, Crandall D, Robinson DG, et al (2002):Basal ganglia volumes in first-episode schizophrenia and healthy com-parison subjects. Biol Psychiatry 51:801– 808.

Ha TH, Youn T, Ha KS, Rho KS, Lee JM, Kim IY, et al (2004): Gray matterabnormalities in paranoid schizophrenia and their clinical correlations.Psychiatry Res 132:251–260.

Heimberg DR, Naber G, Hemmeter U, Zechner S, Witzke W, Gerhard U, et al(1999): Contingent negative variation and attention in schizophrenicand depressed patients. Neuropsychobiology 39:131–140.

Henik A, Carter CS, Salo R, Chaderjian M, Kraft L, Nordahl TE, et al (2002):Attentional control and word inhibition in schizophrenia. Psychiatry Res110:137–149.

Joyce JN, Goldsmith SG, Gurevich EV (1997): Limbic circuits and monoaminereceptors: dissecting the effects of antipsychotics from disease pro-cesses. J Psychiatr Res 31:197–217.

Kaji R (2001): Basal ganglia as a sensory gating devise for motor control.J Med Invest 48:142–146.

Kiehl KA, Smith AM, Hare RD, Liddle PF (2000): An event-related potentialinvestigation of response inhibition in schizophrenia and psychopathy.Biol Psychiatry 48:210 –221.

Kumari V, Gray JA, Honey GD, Soni W, Bullmore ET, Williams SC, et al (2002):Procedural learning in schizophrenia: A functional magnetic resonanceimaging investigation. Schizophr Res 57:97–107.

Lipska BK (2004): Using animal models to test a neurodevelopmental hy-

pothesis of schizophrenia. J Psychiatry Neurosci 29:282–286.

L

L

M

M

M

O

P

P

R

R

M. Vink et al BIOL PSYCHIATRY 2006;60:32–39 39

ogan GD, Cowan WB (1984): On the ability to inhibit thought and action:A theory of an act of control. Psychological Review 91:295–327.

ubow RE, Weiner I, Schlossberg A, Baruch I (1987): Latent inhibition andschizophrenia. Bull Psychonomic Soc 25:464 – 467.

cCarley RW, Niznikiewicz MA, Salisbury DF, Nestor PG, O’Donnell BF, Hira-yasu Y, et al (1999): Cognitive dysfunction in schizophrenia: Unifyingbasic research and clinical aspects. Eur Arch Psychiatry Clin Neurosci249(4 suppl):69 – 82.

cDonald C, Bullmore ET, Sham PC, Chitnis, X, Wickham H, Bramon E, et al(2004): Association of genetic risks for schizophrenia and bipolar disor-der with specific and generic brain structural endophenotypes. Arch GenPsychiatry 61:974 –984.

enon V, Anagnoson RT, Glover GH, Pfefferbaum A (2001): Functional mag-netic resonance imaging evidence for disrupted basal ganglia functionin schizophrenia. Am J Psychiatry 158:646 – 649.

ldfield RC (1971): The assessment and analysis of handedness: The Edin-burgh inventory. Neuropsychologia 9:97–113.

eters ER, Pickering AD, Hemsley DR (1994): “Cognitive inhibition” and pos-itive symptomatology in schizotypy. Br J Clin Psychol 33(pt 1):33– 48.

eters ER, Pickering AD, Kent A, Glasper A, Irani M, David AS, et al (2000): Therelationship between cognitive inhibition and psychotic symptoms.J Abnorm Psychol 109:386 –395.

aemaekers M, Jansma JM, Cahn W, van der Geest JN, van der Linden JA,Kahn RS, et al (2002): Neuronal substrate of the saccadic inhibitiondeficit in schizophrenia investigated with 3-dimensional event-re-lated functional magnetic resonance imaging. Arch Gen Psychiatry59:313–320.

amsey NF, van den Brink JS, van Muiswinkel AM, Folkers PJ, Moonen CT,Jansma JM, et al (1998): Phase navigator correction in 3D fMRI improves

detection of brain activation: Quantitative assessment with a gradedmotor activation procedure. Neuroimage 8:240 –248.

Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al(1998): The Mini-International Neuropsychiatric Interview (M.I.N.I.): Thedevelopment and validation of a structured diagnostic psychiatric inter-view for DSM-IV and ICD–10. J Clin Psychiatry 59(20 suppl):22–33.

Swerdlow NR, Braff DL, Geyer MA (2000): Animal models of deficient senso-rimotor gating: what we know, what we think we know, and what wehope to know soon. Behav Pharmacol 11:185–204.

Swerdlow NR, Braff DL, Hartston H, Perry W, Geyer MA (1996): Latent inhibi-tion in schizophrenia. Schizophr Res 20:91–103.

Takase K, Tamagaki C, Okugawa G, Nobuhara K, Minami T, Sugimoto T, et al(2004): Reduced white matter volume of the caudate nucleus in patientswith schizophrenia. Neuropsychobiology 50:296 –300.

Tekin S, Cummings JL (2002): Frontal-subcortical neuronal circuits and clin-ical neuropsychiatry: An update. J Psychosom Res 53:647– 654.

Thevenaz P, Ruttimann UE, Unser M (1998): A pyramid approach to subpixelregistration based on intensity. IEEE Trans Image Processing 7:27– 41.

Vink M, Kahn RS, Raemaekers M, Ramsey NF (2005): Perceptual bias follow-ing visual target selection. Neuroimage 25:1168 –1174.

Vink M, Kahn RS, Raemaekers M, van den HM, Boersma M, Ramsey NF (2005):Function of striatum beyond inhibition and execution of motor re-sponses. Hum Brain Mapp 25:336 –344.

Vink M, Ramsey NF, Raemaekers M, Kahn RS (2005): Negative priming inschizophrenia revisited. Schizophr Res 79:211–216.

Waters FA, Badcock JC, Maybery MT, Michie PT (2003): Inhibition in schizo-phrenia: Association with auditory hallucinations. Schizophr Res 62:275–280.

Weisbrod M, Kiefer M, Marzinzik F, Spitzer M (2000): Executive control isdisturbed in schizophrenia: Evidence from event-related potentials in aGo/NoGo task. Biol Psychiatry 47:51– 60.

Worsley KJ (1994): Local maxima and the expected Euler characteristic ofexcursion sets of chi-square, F and t fields. Adv Appl Probability 26:13– 42.

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