319-325 how well do patients with schizophrenia track multiple moving targets

8/2/2019 319-325 How Well Do Patients With Schizophrenia Track Multiple Moving Targets

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How Well Do Patients With Schizophrenia Track Multiple Moving Targets?

Oguz Kelemen, Orsolya Nagy, andAdrienne Matyassy

Bacs-Kiskun Country Hospital

Istvan BitterSemmelweis University

Gyorgy Benedek University of Szeged

Zoltan VidnyanszkyHungarian Academy of Sciences and Semmelweis University

Szabolcs KeriSemmelweis University

It has been demonstrated that patients with schizophrenia perform poorly on tasks that require orienting,

focusing, maintaining, and shifting attention. However, it is unknown how patients with schizophrenia

can track multiple moving targets. To elucidate this issue, the authors investigated fast and slow

multiple-object tracking in patients with schizophrenia (n 30) and in matched healthy control

participants (n 30) and assessed their relationship with motion perception (velocity discrimination),

sustained attention and context processing (Continuous Performance Test, 1–9 version; J. R. Finkelstein,

T. D. Cannon, R. E. Gur, R. C. Gur, & P. Moberg, 1997), and object and spatial working memory. Results

revealed that patients with schizophrenia displayed impaired performances on multiple-object tracking

tasks. Linear regression analysis revealed a specific relationship among object tracking, velocity dis-

crimination, and spatial working memory. In patients with schizophrenia, velocity discrimination and

spatial working memory were the predictive factors of multiple-object tracking, whereas in healthy

control participants, the single predictive factor was velocity discrimination. Probabilistic regression

analysis revealed that only the Continuous Performance Test made significant contribution to discrim-

inating between patients and control participants. These results suggest that multiple-object tracking is

impaired in schizophrenia, and that it is specifically associated with motion perception and spatial

working memory.

Keywords: schizophrenia, attention, multiple-object tracking, working memory, motion perception

Attentional deficit is thought to be a core feature of schizophre-nia; it contributes to impairments in community functions and

represents a vulnerability marker for psychosis (Braff, 1993; Corn-

blatt & Keilp, 1994; Green, 1996; Heinrichs & Zakzanis, 1998;

Langdon, Corner, McLaren, Coltheart, & Ward, 2006; Nuechter-

lein & Dawson, 1984; Yung, Phillips, Yuen, & McGorry, 2004).

Patients with schizophrenia regularly perform poorly on tasks

requiring maintenance of vigilance and focus of attention, orien-

tation to targets, and control and allocation of attentional capacity,

or executive control (Chan, Yip, & Lee, 2004; Nieuwenstein,

Aleman, & de Haan, 2001; Wang et al., 2005). In spite of its

importance, attention is an ambiguously defined term (Lezak,

1995). According to Heinrichs & Zakzanis (1998), Digit Spantasks, the Continuous Performance Test (CPT), the Trail Making

Test, and the Stroop task (the reference for all tasks is Lezak,

1995) all measure vigilance, concentration, and selection. These

tasks are the most commonly used procedures to assess attentional

functions in schizophrenia.

Although attentional dysfunctions are extensively documented

among those with schizophrenia (Braff, 1993; Cornblatt & Keilp,

1994; Nuechterlein & Dawson, 1984), surprisingly few studies

have explored the nature and mechanism of this deficit according

to current theoretical frameworks of attention. Wang et al. (2005)

used the attention network test to assess the functioning of three

anatomically defined attentional networks: alerting, orienting, and

executive control. In patients with schizophrenia, executive controlfunctions were severely affected, orienting was less affected, and

alerting was spared. This suggests the impairment of lateral pre-

frontal areas, anterior cingulate cortex, and parietal lobes, which is

consistent with the neuroimaging literature of schizophrenia

(Kircher & Thienel, 2005).

In contrast to Wang et al. (2005), Birkett, Brindley, Norman,

Harrison, and Baddeley (2005) arrived at substantially different

conclusions. These authors investigated the ability to focus atten-

tion, to resist distraction, to shift attention, and to divide attention

in patients with schizophrenia and in healthy control participants.

Patients with schizophrenia showed worse performances across

nearly all conditions, but they were not disproportionately im-

Oguz Kelemen, Orsolya Nagy, and Adrienne Matyassy, Bacs-Kiskun

Country Hospital, Kecskemet, Hungary; Istvan Bitter and Szabolcs Keri,

Department of Psychiatry and Psychotherapy, Semmelweis University,

Budapest, Hungary; Gyorgy Benedek, Department of Physiology, Univer-

sity of Szeged, Szeged, Hungary; Zoltan Vidnyanszky, Neurobiology Re-

search Group, Hungarian Academy of Sciences, Budapest, Hungary, and

Semmelweis University.

This study was supported in part by Hungarian Scientific Research Fund

Grant T048949 and by the Bolyai Fellowship to Zoltan Vidnyanszky.

Correspondence concerning this article should be addressed to

Szabolcs Keri, Department of Psychiatry and Psychotherapy, Semmel-

weis University, Balassa u. 6, H1083, Budapest, Hungary. E-mail:

[email protected]

Neuropsychology Copyright 2007 by the American Psychological Association2007, Vol. 21, No. 3, 319 –325 0894-4105/07/$12.00 DOI: 10.1037/0894-4105.21.3.319

319



paired during tasks of higher level executive control. Birkett et al.

concluded that the attentional and executive functions studied in

their sample were not specifically and significantly affected by the

schizophrenic disease process.

In traditional laboratory paradigms, visual attention selects in-

formation from a single location of the environment. However,

many typical everyday activities, such as video games, simulta-

neously watching people in a crowd, or navigating in heavy traffic,

require that attention be paid to multiple locations of the environ-

ment. These functions, which model real-life attentional demands

more reliably than traditional laboratory tasks, have not been

investigated in schizophrenia.

Pylyshyn and Storm (1988) were the first to demonstrate that

participants are able to continuously track multiple moving ob-

jects. In the multiple-object tracking test, identical squares move

randomly within a rectangular area, bouncing off the borders and

each other. Participants are asked to follow some selected squares

(target items) embedded in a group of distractors. At the end of a

trial, a square is marked and participants report whether the square

is one of the target items (see Figure 1).

There are several models of multiple-object tracking. For ex-ample, the switching model proposes a single locus of attention

that cycles quickly through target items and indexes their loca-

tions. In contrast, multifocal attention models claim that each

target attracts independent “beams” of attention following target

items while they move (for a detailed review of other theoretical

approaches, see Oksama & Hyona, 2004). Multiple-object tracking

has several capacity limitations. Observers are regularly able to

track approximately four targets for 15–20 s. Temporal properties

of attention are of special importance: If target items move too fast,

it is more difficult to follow them (Verstraten, Cavanagh, &

Labianca, 2000). Finally, increasing evidence suggests that visual

working memory is indispensable for successful multiple-object

tracking (Allen, McGeorge, Pearson, & Milne, 2006). It has beenshown by several studies that patients with schizophrenia are

impaired on tests of motion perception (Chen, Levy, Sheremata, &

Holzman, 2004, 2006; Chen, Nakayama, Levy, Matthysse, &

Holzman, 1999, 2003; Kelemen et al., 2005; Kim, Wylie, Paster-

nak, Butler, & Javitt, 2006; Stuve et al., 1997) and of visual

working memory (Conklin, Curtis, Calkins, & Iacono, 2005; Gold,

Wilk, McMahon, Buchanan, & Luck, 2003; Lee & Park, 2005;

Pantelis et al., 1997), and that these dysfunctions are related to

each other (Brenner, Lysaker, Wilt, & O’Donnell, 2002). Motion

perception dysfunctions are also related to the deficit of smooth-

pursuit eye movements. Specifically, Chen, Nakayama, et al.

(1999) reported that the motion discrimination deficit occurred

both in patients with schizophrenia and in their first-degree rela-

tives and involved a failure of velocity detection. Impaired velocity

discrimination was associated with sluggish initiation of smooth-

pursuit eye movements. Although eye movement dysfunctions

may contribute to multiple-object tracking deficits in schizophre-

nia, evidence suggests that eye movements alone or a single broad

focus of attention cannot explain multiple-object tracking capacity

in healthy control participants (Cavanagh & Alvarez, 2005; Ok-

sama & Hyona, 2004; Pylyshyn, 2003).

The purpose of this study was twofold. First, we aimed to

investigate multiple-object tracking in patients with schizophrenia.

We hypothesized that patients with schizophrenia are less effi-

ciently able to track multiple moving objects. Second, we inves-

tigated the contribution of positive and negative symptoms, veloc-

ity discrimination, sustained attention and context processing, andvisual working memory to multiple-object tracking performance.

Our hypothesis was that velocity discrimination, sustained atten-

tion, and visual working memory are related to multiple-object

tracking performance in both patients with schizophrenia and

control participants. The impairment of these cognitive functions

potentially contributes to multiple-object tracking deficits in

schizophrenia. Finally, we assessed the relationship between clin-

ical symptoms and multiple-object tracking performance. Because

many studies have demonstrated correlations between negative

symptoms and cognitive dysfunctions (e.g., Addington, Adding-

ton, & Maticka-Tyndale, 1991; Nieuwenstein et al., 2001; Strauss,

1993), we predicted that negative symptoms are related to multi-

ple-object tracking performance.

Method

Participants

A sample of 30 patients with a Diagnostic and Statistical

Manual of Mental Disorders (4th ed.; DSM-IV; American Psychi-

atric Association, 1994) diagnosis of schizophrenia and 30 healthy

volunteers participated in the study. Among the patients (21 men, 9

women), 18 were diagnosed as paranoid schizophrenics, 6 as

undifferentiated schizophrenics, 4 as residual schizophrenics,

and 2 as disorganized schizophrenics. The mean age was 39.6

years (SD 9.4), mean duration of illness was 12.5 years

(SD 6.0), and mean years of education was 11.4 (SD 3.2).Among the healthy volunteers (21 men, 9 women), the mean age

was 40.1 years (SD 10.6), and the mean years of education

was 12.2 (SD 4.7). All participants were screened with the

Mini-International Neuropsychiatric Interview (Sheehan et al.,

1998). A detailed medical history of each patient and reports from

the treating physicians were available. General intellectual abilities

were assessed with the revised version of the Wechsler Adult

Intelligence Scale (Wechsler, 1981). The mean IQ values

were 97.1 (SD 17.8) in the patient group and 102.8 (SD 12.6)

in the control group. There were no significant differences between

patients and control participants in age, years of education, and IQ

( p .1, two-tailed t test). Of the patients, 28 were receiving

A B C

Figure 1. The multiple-object tracking test. Out of eight identical

squares, four are targets, and four are distractors. The target squares blink

briefly (white) at the beginning of each trial (Panel A). The squares then

move randomly within a rectangular area, bouncing off the borders and

each other. Participants are asked to follow the target squares (Panel B). At

the end of a trial, a square is blanked (white), and participants report

whether the square is one of the target items (Panel C).

320 KELEMEN ET AL.



antipsychotic medication at the time of testing (aripiprazole, olan-

zapine, quetiapine, risperidone, haloperidol, zuclopenthixol). The

mean chlorpromazine-equivalent dose was 645.6 (SD 185.4)

mg/day. The Positive and Negative Syndrome Scale was used for

the assessment of clinical symptoms (Kay, Fiszbein, & Opler,

1987); mean positive symptoms was 12.7 (SD 7.2), mean

negative symptoms was 17.3 (SD 9.0), and mean general symp-

toms was 36.1 (SD 10.3). Neurological disorders, substance

dependence, history of head injury, electroconvulsive therapy, and

central nervous system disorders that were due to general medical

conditions were the exclusion criteria. All participants had normal

or corrected-to-normal visual acuity. The study was approved by

the unversity ethics committee at the University of Szeged and was

performed according to the Declaration of Helsinki. All partici-

pants gave their written informed consent.

Setup and General Design

Stimuli were presented on a gamma-corrected ViewSonic

PF815 monitor (resolution, 800 600 pixels; refresh rate, 100 Hz;

VSG graphic card, Version 5.02; Cambridge Research System Ltd,Rochester, United Kingdom) controlled by a PC. The viewing

distance was 70 cm. The average luminance of the display field

was 40 cd/m2. This apparatus was used for all the tests, which were

administered in three different sessions on 2 consecutive days.

Rest periods were provided as needed. Before each test, a practice

run was provided to ensure that participants understood the in-

structions and were able to stay on task. The order of tests was

counterbalanced across participants.

Multiple-Object Tracking

The tracking field (the area in which the items moved) was a

central white rectangle occupying 16.2 deg 12.2 deg on the

computer screen. Each trial employed four target items and fourdistractor items, all presented as identical black squares (subtend-

ing 0.54 deg 0.54 deg) on a white background. Each item’s

initial position was generated randomly on each trial. A fixation

cross was presented throughout the trials at the center of the

tracking field. At the beginning of each trial, four randomly se-

lected items blinked several times to indicate their status as targets.

After this, all items began to move independently for 15 s (see

Figure 1). Every 500 ms, a new velocity was randomly selected for

each moving item. There were two velocity conditions: (a) the

velocities of the items ranged from 1 to 20 deg/s with an average

velocity over all trials and items of 6.4 deg/s (slow condition); (b)

the velocities of the items ranged from 1 to 28 deg/s with an

average velocity of 8.4 deg/s (fast condition). Item motion wasconstrained so that items repelled the borders of the tracking field,

and no item ever came nearer than 0.7 deg to another item.

Participants were requested to track the four target items

throughout the motion sequence. When the motion ceased, a

randomly selected target or a nontarget item had changed its color

to blue, and participants indicated whether it was a target or a

nontarget by pressing the left or right mouse button, respectively

(see Figure 1). Twenty-five trials were applied in both fast and

slow conditions. The order of presentation for fast and slow

conditions was counterbalanced across participants. The dependent

measure was the percentage of right answers (correct identification

of targets and correct rejection of distractors).

Velocity Discrimination

Stimuli were vertical sinusoidal gratings appearing in a circular

window (diameter, 20 deg; spatial frequency, 0.5 cycle/deg; con-

trast, 20%). The basal velocity (V ) was 10 deg/s. First, a fixation

point was presented for 500 ms. Following the fixation point,

participants viewed two sequential gratings that differed in veloc-

ity (V ; exposure time, 500 ms; interstimulus interval, 300 ms).The task was to decide which grating moved faster by pressing the

left (first grating) or the right (second grating) mouse button. The

initial velocity of the faster grating was 20 deg/s. The just-notice-

able difference (Weber fraction; V / V ) was determined with a

three-down, one-up staircase, meaning that the velocity difference

between the targets was reduced by 30% after three consecutive

correct responses or increased by 30% after a single error. The

staircase was terminated after 12 reversals converging at 74.9%

accuracy (Chen et al., 2004; Chen, Nakayama, et al, 1999; Chen,

Palafox, et al., 1999).

CPT, 1–9 Version

The 1–9 CPT was administered according to Finkelstein, Can-

non, Gur, Gur, and Moberg (1997). During the test, participants

were asked to press a button when a 1 was followed by a 9 in the

sequence. The stimulus duration was 200 ms, and the interstimulus

interval was 800 ms. During the test, 300 trials were presented

with 30 targets. The sensitivity index (d ) was calculated from hit

rates and false alarm rates. Beyond sustained attention, which is

indispensable to detect many sequentially presented stimuli, the

1–9 CPT requires the maintenance of context and the inhibition of

proponent responses (the number 9 preceded by a number other

than 1), which are related to working memory and context pro-

cessing (Finkelstein et al., 1997).

Object Working Memory

A modified version of the change detection task was used to

investigate object working memory (Gold et al., 2003). Stimulus

displays (size, 10 deg 7 deg) consisted of six randomly oriented

bars (size, 1.6 deg 0.2 deg; orientation, 0 deg, 45 deg, 90 deg,

and 135 deg from vertical) with different randomly selected colors

(red, blue, green, and black). First, a fixation point was presented

for 500 ms, which was immediately followed by a sample array for

500 ms. The sample array was followed by a delay period (2 s)

with a blank screen. After the delay period, a test array was

presented for 4 s; either it was identical to the sample array (50%

of trials) or the color or orientation of a single item was changed

(50% of trials). Participants were asked to decide whether the test

array was identical to the sample array by pressing the left or the

right mouse button, respectively. The test consisted of 100 trials.

The dependent measure was sensitivity ( A), calculated according

to Stanislaw and Todorov (1999) with hit rates and false alarm

rates. A is a nonparametric version of d . If A 1, an ideal

observer shows a perfect ability to discriminate between the same

and different sample and test arrays. If A 0.5, performance is at

the chance level.

Spatial Working Memory

The spatial working memory task was a modified version of the

procedure used by Spindler, Sullivan, Menon, Lim, and Pfeffer-

321MULTIPLE-OBJECT TRACKING IN SCHIZOPHRENIA



baum (1997). A trial began with the presentation of a fixation point

for 500 ms, which was followed by a sequence of dots, each

exposed for 500 ms. The dots appeared in one of eight possible

locations around an oval shape. After the presentation of the dots,

the fixation point returned for 2 s. Then participants saw a test

array on the computer screen showing the eight possible locations

of the dots and were asked to click on the presented dots according

to their sequential appearance. The sequence length increased from

two to seven dots. Two trials were presented for each sequence

length. The test was stopped when the participant was unable to

complete both trials at a given length. The maximum score was 12

(2 trials 6 sequence lengths).

Data Analysis

The STATISTICA 6.0 package (StatSoft, Tulsa, OK) was used

for data analysis. The distribution of the data was checked with

Kolmogorov–Smirnov tests, and the homogeneity of variance was

checked with Levene’s tests. If normal distribution and homoge-

neity of variance were proven, the dependent measures were

compared with two-tailed t tests. In other cases, Mann-Whitney U

tests were applied. To determine the factors that predicted multi-

ple-object tracking performance, we performed a forward stepwise

multiple regression analysis (dependent measure: multiple-object

tracking performances in the slow and fast conditions). In the first

regression analysis, the clinical symptoms (Positive and Negative

Syndrome Scale scores), the duration of the illness, and the chlor-

promazine-equivalent dose of antipsychotics were the predictors.

In the second regression analysis, the measures of cognitive func-

tions (velocity discrimination, CPT, object and spatial working

memory) were the predictors. We also conducted a logistic regres-

sion analysis to determine which cognitive measures made signif-

icant independent contributions to discriminating between patients

and control participants. The level of significance was set at .05. Effect sizes (Cohen’s d ) were given for each comparison

(Cohen, 1988).

Results

The data shown in Table 1 were normally distributed (Kolmog-

orov–Smirnov tests, p .1). However, in the case of multiple-

object tracking data, Levene’s test showed a significant deviation

from the homogeneity of variance ( p .01); therefore, these data

were compared with Mann-Whitney U tests.

Patients with schizophrenia showed impaired performances on

the velocity discrimination test, CPT, and object and spatial work-

ing memory tasks (see Table 1). They were similarly impaired on

the fast and slow multiple-object tracking tests. The d statistics

revealed large effect size values (Cohen, 1988; see Table 1).

Because of the small number of trials, signal detection analysis

was not performed on the multiple-object tracking performances

(Stanislaw & Todorov, 1999). However, it can be excluded that the

worse performances of the patients with schizophrenia were

caused by a deliberate response strategy. The rate of false alarms

was 6.8% (SD 2.1) in the control participants, and it was 7.1%

(SD 2.8) in the patients with schizophrenia ( p .1).

In the control group, the single predictive factor for fast multi-

ple-object tracking performance was the velocity discrimination

threshold, .44; F (1, 28) 10.87, p .005; R2 .28. In the

slow condition, none of the factors reached the level of statistical

significance ( p .1).

In the patients with schizophrenia, fast multiple-object tracking

performance was predicted by velocity discrimination, .45;F (1, 28) 10.98, p .005; R2 .28, and spatial working

memory, .42; F (1, 28) 12.26, p .005; R2 .30. In the

slow condition, only spatial working memory predicted multiple-

object tracking performances, .40; F (1, 28) 7.32, p .05;

R2 .21.

The regression analysis, including the Positive and Negative

Syndrome Scale scores, the duration of the illness, and the chlor-

promazine-equivalent dose of antipsychotics, did not reveal a

significant effect ( p .1). The probabilistic regression analysis

indicated that only the CPT made significant contribution to pre-

dicting group membership (patients with schizophrenia vs. control

group), .27; F (1, 28) 10.48, p .005; R2 .15.

Discussion

The main finding of our study was that patients with schizo-

phrenia performed poorly on the multiple-object tracking test.

These results are consistent with those of previous studies dem-

onstrating that patients with schizophrenia are impaired when two

concurrent tasks must be monitored (Salame, Danion, Peretti, &

Cuervo, 1998). During multiple-object tracking, concurrent mon-

Table 1

Results From Patients With Schizophrenia and Healthy Control Participants

Test

Schizophrenia(n 30) Controls (n 30)

t / Z a P d M SD M SD

Multiple-object tracking—6.4 deg/s (% correct) 82.4 15.2 95.4 5.1 3.67a .0002 1.0Multiple-object tracking—8.4 deg/s (% correct) 73.2 18.6 88.6 8.3 3.30a .0009 0.95Velocity discrimination (V/V ) 0.22 0.08 0.16 0.07 3.40 .001 0.75Continuous Performance Test, 1–9 version (d ) 4.2 0.8 4.8 0.6 3.24 .002 0.80Object working memory ( A) 0.66 0.14 0.79 0.10 4.04 .0002 1.0Spatial working memory (max. score 12) 5.9 1.6 7.4 1.8 3.52 .001 0.83

Note. Data are means and standard deviations. Results from t tests (d f 58) and effect size values (d ) are also shown.a Indicates that the results are from a Mann–Whitney U test.

322 KELEMEN ET AL.



itoring of targets allows the investigation of the sensory (input)

component of task performance. Our data also suggest that im-

paired multiple-object tracking performance in schizophrenia is

not a mere consequence of clinical symptoms, generalized cogni-

tive impairment, medication effects, impaired sustained attention

and context processing (CPT), or impaired object working mem-

ory. Specifically, we demonstrated circumscribed relationshipsamong multiple-object tracking, processing of motion and speed

(velocity discrimination), and spatial working memory. Contrary

to our expectations, multiple-object tracking performance was not

related to the negative symptoms of schizophrenia. Brenner et al.

(2002) also found that visual dysfunctions do not correlate with the

clinical symptoms, and evidence suggests that such relationships

are weak (Nieuwenstein et al., 2001).

Bearing in mind that correlation is not causation, and that

regression analyses are susceptible to psychometric artifacts, we

hypothesized that the dysfunction of the cortical network related to

motion perception and spatial working memory may play an

important role in multifocal attentional dysfunctions in schizophre-

nia. LaBar, Gitelman, Parrish, and Mesulam (1999) found that

working memory and spatial attention activate partially overlap-

ping cortical areas, including the intraparietal sulcus, thalamus,

supplementary motor area, and frontal eye fields. This system

receives input from motion-sensitive visual areas, such as the

middle temporal cortex (V5), and it is responsible for attentional

orientation and eye movements (Grosbras, Laird, & Paus, 2005;

Orban, Van Essen, & Vanduffel, 2004; Shipp, 2004). In the pos-

terior parietal and frontal cortex, increased activation was found

during visual object tracking tasks (Culham et al., 1998; Culham,

Cavanagh, & Kanwisher, 2001; Jovicich et al., 2001), and there is

mounting evidence from neuroimaging studies that this frontopa-

rietal network is severely affected in schizophrenia (Kircher &

Thienel, 2005). Chen, Nakayama, et al. (1999) found a significant

relationship between velocity discrimination and smooth-pursuiteye movement dysfunctions in patients with schizophrenia and in

their siblings, whereas Brenner et al. (2002) found associations

between motion perception and visual working memory deficits. In

conclusion, we hypothesize that the dysfunction of multiple-object

tracking is related to a complex cortical network including motion-

sensitive regions (V5) and areas responsible for spatial processing

(posterior parietal cortex), eye movements, and working memory

(prefrontal cortex, including the frontal eye field).

However, it must be noted that in healthy control participants,

multiple-object tracking was specifically associated with velocity

discrimination, which was the single predictive factor of fast

multiple-object tracking performance. In contrast, in patients with

schizophrenia, spatial working memory was a significant predic-tive factor of multiple-object tracking performance. It is likely,

however, that the nonsignificant result for spatial working memory

in the control group might simply reflect the reduced range of

object tracking scores in the control sample compared with the

patient sample. It is also important to note that in patients with

schizophrenia, multiple-object tracking impairments were not lim-

ited to the fast condition, which suggests that lower performances

on this test cannot be exclusively explained by the impaired

processing of speeded stimuli.

Pylyshyn (2003) proposed that during object tracking, “preat-

tentive indexes” attach to the targets as they move. These “in-

dexes” are not locations held in memory, do not have to be

refreshed, and do not require attention to maintain contact with

targets. However, novel evidence suggests that working memory is

necessary for multiple-object tracking (Allen et al., 2006). Patients

with schizophrenia may rely on visual–spatial working memory

during multiple-object tracking. Because of dysfunctional visual

working memory and motion processing, patients with schizophre-

nia perform poorly on multiple-object tracking tasks. This deficit

may contribute to the abnormal visual scanning of complex envi-

ronmental stimuli (Minassian, Granholm, Verney, & Perry, 2005).

Although the number of targets was constant in this experiment,

pilot data indicated that patients with schizophrenia are able to

track one or two targets (Keri, 2006). A significant drop of per-

formance at four targets may be a consequence of the capacity

limitation of spatial working memory.

In our study, patients with schizophrenia performed poorly on

each task, with the exception of the IQ test. However, multiple-

object tracking was specifically associated with motion processing

and with spatial working memory, which is against the possibility

that a generalized failure of executive functions can fully explain

multiple-object tracking results. For example, the 1–9 version of

the CPT requires the maintenance of context and the inhibition of proponent responses, whereas the object working memory task

requires the concurrent processing of orientation and color. Sus-

tained attention and context processing functions (1–9 CPT) were

significant predictors of group membership (patients vs. control

group) but were unrelated to multiple-object tracking in patients

with schizophrenia and in healthy control participants. It is some-

what surprising that the CPT was the single factor that predicted

group membership (schizophrenia vs. healthy control participants).

A possible explanation could be that this test integrates multiple

cognitive functions that are impaired in schizophrenia (rapid stim-

ulus encoding, sustained attention, working memory, and context

representation), and therefore its discriminating power is better

than that of the other tests used in this study.There is ample evidence suggesting that many aspects of mul-

tiple-object tracking are not mediated by higher level executive

functions, and that low-level visual “indexing” processes may play

a crucial role during this task (Pylyshyn, 2003). Low-level sensory

dysfunctions may also be important in schizophrenia (Braus, We-

ber-Fahr, Tost, Ruf, & Henn, 2002; Butler et al., 2005; Keri,

Kelemen, Benedek, & Janka, 2004; Keri, Kelemen, Janka, &

Benedek, 2005) and may contribute to the dysfunction of motion

perception (Kim et al., 2006). However, in this study, low-level

sensory functions were not specifically addressed, and therefore it

is not clear how these functions may contribute to multiple-object

tracking performance. Further studies are warranted to investigate

the complex relationship among low-level sensory processes, dif-ferent domains of attention, and multiple-object tracking functions

in normal and pathological conditions.

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Received June 20, 2006

Revision received November 27, 2006

Accepted December 11, 2006

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