Eye Tracking Disorder in Schizophrenia Is Characterized by Specific Ocular Motor Defects and Is Associated with the Deficit Syndrome

Eye Tracking Disorder in Schizophrenia Is Characterized by Specific Ocular Motor Defects and Is Associated with the Deficit Syndrome David E. Ross, Gunvant K. Thaker, Robert W. Buchanan, Brian Kirkpatrick, Adrienne C. Lahti, Deborah Medoff, John J. Bartko, Jason Goodman, and Allen Tien

The objective was to determine the relationships between eye tracking disorder (ETD) in schizophrenia, specific ocular motor measures, and the deficit syndrome. Twenty-five normal comparison subjects and 53 schizophrenic patients had eye movements tested with infrared oculography using a sinusoidal target. Patients were assessed with the Schedule for the Deficit Syndrome. For the patients, the distribution of position root mean square error (a global measure of pursuit) was best fit by a mixture of two normal distributions. This information was used to divide the patients into two subgroups, those with and those without ETD. ETD was almost completely accounted for by several specific ocular motor measures and was significantly associated with the deficit syndrome. The finding that ETD was almost completely accounted for by specific measures bridges a gap of interpretation in this field. ETD and the deficit syndrome of schizophrenia may share a common pathophysiology of cerebral cortical–subcortical circuits. © 1997 Society of Biological Psychiatry Key Words: Eye movements, schizophrenia, smooth pursuit, saccades, mixture analysis BIOL PSYCHIATRY 1997;42:781–796

Introduction It is well known that schizophrenic patients have abnormal smooth pursuit eye movements (for review, see Levy et al 1993). Although a large amount of research has been done in this area, questions remain in at least two major areas. First, it is still not clear that eye tracking disorder (ETD) can be fully explained in terms of specific oculomotor From the Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, (DER, GKT, RWB, BK, AL, DM, JJB, JG); and Department of Mental Hygiene, Johns Hopkins Hospital, Baltimore, Maryland (AT). Address reprint requests to Dr. David E. Ross, Maryland Psychiatric Research Center, P.O. Box 21247, Baltimore, MD 21228. Received March 12, 1996; revised October 14, 1996.

© 1997 Society of Biological Psychiatry

defects. In other words, although everyone agrees that patients have abnormal smooth pursuit, not everyone agrees on exactly what the abnormality is. Second, although schizophrenia is defined exclusively on the basis of psychopathological criteria, little is known about the relationship between ETD and psychopathology. Addressing these questions will be crucial if ETD is to be used as a tool for gaining insight into schizophrenia.

Global versus Specific Ocular Motor Measures Previous studies of smooth pursuit eye movements in schizophrenia can be divided into two major classes. The first class of studies has used global measures of eye 0006-3223/97/$17.00 PII S0006-3223(96)00492-1

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tracking, and the second class of studies has used specific measures. What are the differences between the two, and what are their advantages and disadvantages? Global measures reflect tracking error due to any cause. The most commonly used global measures have been qualitative ratings, position root mean square (RMS) error, and natural logarithm of signal-to-noise ratio. Global measures are important for at least three reasons: 1) a vast amount of early research was based on these measures, making it important to understand them; 2) global measures satisfy several criteria for construct validity as a trait-related marker of schizophrenia (Blackwood et al 1991; Iacono et al 1992; Iacono and Clementz 1993); and 3) it is important to know the amount of variance in global error that can be accounted for by the more specific measures, to rule out the possibility that specific defects have been overlooked. Global measures are limited, however, in that they cannot distinguish between aspects of smooth pursuit that are importantly related to the oculomotor system. For example, they do not even distinguish between the smooth or saccadic components of smooth pursuit, a distinction which is of fundamental importance. What does the term “specific” in “specific measures” mean? Typically, it means oculographically more specific than global measures, and that is how the term will be used here, unless otherwise stated. For example, gain is oculographically more specific than position RMS error, which might reflect low gain, excessive saccades, etc.; however, specific measures are not necessarily neuro-ophthalmologically specific. Studies in the neuro-ophthalmological literature have been successful in linking brain diseases to oculomotor defects, and these studies have relied almost exclusively on oculographically specific measures. For these reasons, it has been suggested that greater use of specific measures would be necessary for advancement of research on smooth pursuit in schizophrenia (Abel and Ziegler 1988), and many investigators have heeded this call. Nevertheless, whether or not these measures are neuro-ophthalmologically more specific depends on the measure being used and the context of interpretation. For example, gain is oculographically specific to the smooth component, but abnormally low steady-state gain is relatively nonspecific with respect to neuroanatomy or disease (for review, see Leigh and Zee 1991). In addition to questions about validity, another question immediately poses itself. What is the relationship between global and specific measures in schizophrenia? Several studies have used both global and specific measures of pursuit (for examples, see Ross et al 1988, 1996a; Clementz et al 1992; Sweeney et al 1993). These studies have found that global measures of pursuit are related to low pursuit gain, increased frequency of saccades, and increased phase lag. Nevertheless, these studies have not

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made it clear that global measures of pursuit can be fully accounted for by specific measures. If this were the case, then the two types of measures could be fully understood with respect to each other. If not, then a gap of interpretation would remain, leaving the relationship between the two lines of research unclear and uncomplementary. The relationship between global and specific oculomotor defects may differ between subgroups of patients with and without ETD. There is a substantial amount of evidence that schizophrenic patients and their relatives can be divided into subgroups of trackers, based on qualitative analysis of the data as well as mixture in the distributions of global measures of eye tracking (Gibbons et al 1984; Clementz et al 1992; Iacono et al 1992; Sweeney et al 1993; Ross et al 1996a). Mixture in a distribution means that the sampled data were more likely drawn from a population that was characterized by a mixture of two or more normal distributions than a single normal distribution. The presence of mixture suggests two or more fundamentally different underlying phenomena, and it would be advantageous to study them as such, from the perspectives of statistical analysis (Gibbons et al 1984), genetic research (Iacono and Clementz 1993), and experimental design (Carpenter and Buchanan 1989; Carpenter et al 1993). Little is known about how subgroups of better and worse tracking patients compare with each other and with normal comparison subjects. Previous studies have found that patients with ETD differ from non-ETD patients and normal comparison subjects with respect to several specific measures of pursuit (Sweeney et al 1993; Ross et al 1996a).

The Relationships between Negative Symptoms and Eye Tracking Disorder In addition to understanding the relationship between global and specific measures, other important areas remain to be fully elucidated, in particular, the relationship between ETD and psychopathology. Several studies suggest that the psychopathological manifestations of schizophrenia fall into three domains: 1) psychosis, 2) thought disorder/cognitive dysfunction, and 3) negative symptoms or deficit syndrome (for review, see Buchanan and Carpenter 1994). Some studies have found an association between negative symptoms and ETD, as measured by the withdrawal/ retardation subscale of the brief psychiatric rating scale [BPRS (Overall and Gorman 1961)], (Blackwood et al 1991); or the Scale for the Assessment of Negative Symptoms [SANS (Andreasen 1989)], (Katsanis and Iacono 1991; Sweeney et al 1994); however, other studies have not found a significant relationship between poor eye

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tracking and the SANS (Keefe et al 1989; Kelly et al 1990; Lieberman et al 1993; Sweeney et al 1993). In part, the discrepancy may be due to the fact that the SANS does not distinguish negative symptoms on the basis of whether they are primary or secondary, or whether they are temporary (state related) or enduring (trait related). It is possible that eye tracking dysfunction is only associated with primary and enduring negative symptoms. The deficit syndrome of schizophrenia has been defined as a subtype of schizophrenia that is characterized by primary and enduring negative symptoms (Carpenter et al 1988; Kirkpatrick et al 1989). An increasing body of evidence has supported the validity of the deficit syndrome (Wagman et al 1987; Kirkpatrick and Buchanan 1989; Buchanan et al 1990, 1993; Tamminga et al 1992; Fenton and McGlashan 1994). Deficit patients have abnormal oculomotor responses to the antisaccade task (Thaker et al 1989), but little is known about the relationship between the deficit syndrome and smooth pursuit dysfunction. Our laboratory has reported previously that deficit patients have abnormal initiation of smooth pursuit in response to a step-ramp task (Ross et al 1996b). For the present study, the groups from the previous study were enlarged, and a sinusoidal task was used to attempt to extend the previous findings. The goals of this study were as follows: 1) to test the hypothesis that the distribution of a global measure of eye tracking in schizophrenic patients would be best fit by a mixture of two normal distributions; 2) to determine the relationship between ETD and specific ocular motor measures; 3) to test the hypothesis that ETD patients differ from non-ETD patients and normal comparison subjects with respect to several specific oculomotor measures; and 4) to determine the relationship between ETD and the deficit syndrome.

Methods Subjects Twenty-five normal comparison subjects and 53 schizophrenic patients participated in the study. Written informed consent was obtained from all subjects after the procedures had been fully explained. All subjects were administered the Structured Clinical Interview for DSMIII-R. Subjects were screened to exclude those with medical illnesses or medications known to adversely affect eye movements (including lithium and benzodiazepines). Socioeconomic status (SES) of subjects and their heads of household were obtained using a previously developed scale (Hollingshead and Redlich 1988). Demographic and clinical characteristics of subjects are shown in Table 1. Normal comparison subjects were recruited through

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newspaper advertisements. Exclusion criteria for normal comparison subjects included an Axis I diagnosis. Normal comparison subjects also were administered the Structured Interview for DSM-III-R Personality Disorders–Revised (Pfohl et al 1989) and were excluded if they had more than two spectrum traits in one of the three DSM-III-R categories (schizotypal, schizoid, and paranoid) or more than three total spectrum traits. Patients were recruited from outpatient and inpatient programs at Maryland Psychiatric Research Center (MPRC). All patients satisfied DSM-III-R (American Psychiatric Association 1987) criteria for schizophrenia. All patients were clinically stabilized on antipsychotic medication; some were on antiparkinsonian medication. “Clinically stabilized” was defined as having been on the same antipsychotic medication for at least 4 weeks (usually longer) without a change in dose or significant change in clinical state as assessed by at least two treating clinicians, including the primary psychiatrist. Patients were assessed with the MPRC Involuntary Movement Scale (IMS) and diagnosed according to research diagnostic criteria for tardive dyskinesia (TD) (Schooler and Kane 1982) (Table 1). Thirty-five patients were diagnosed as having TD and 18 were diagnosed as not having TD. The BPRS (Overall and Gorman 1961) was administered to each patient within 1 week of eye movement testing. Patients also were assessed with the Schedule for the Deficit Syndrome (SDS; Kirkpatrick et al 1989), which was done blindly with respect to oculomotor performance. According to this instrument, a diagnosis of deficit syndrome requires that the patient have two of the following six negative symptoms, which are judged to be primary and enduring: restricted affect, diminished emotional range, poverty of speech, curbing of interests, diminished sense of purpose, and diminished social drive. All of the patients were assessed with the SDS except one, who moved away from the region before the assessment could be completed (this patient was included for comparisons of TD and non-TD groups and for mixture analysis). Twelve patients were diagnosed with deficit syndrome and 41 patients were diagnosed as nondeficit. Comparisons were made between subgroups of patients and the normal comparison subjects to assess the presence of potential confounds. Chi-square tests were used for categorical variables, and independent t tests were used for continuous variables. Patients were divided into those with and those without ETD as described below (see Results/Mixture Analysis). The three groups (normal comparison subjects, ETD patients, and non-ETD patients) did not differ significantly with respect to age or SES of head of household (all ps . .10). The ETD and non-ETD patients did not differ significantly with respect to subject’s SES, duration of

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Table 1. Demographic and Clinical Characteristics of Subjects

n Sex Race TD Age (years)a SES of subjecta SES of head of householda Duration of illness (years)a Duration of treatment with antipsychotic medication (years)a BPRS total scorea Mean dose neuroleptic (mg CPZ equivalents)a Global parkinsonism score (0 5 none, 7 5 severe)a

Normal controls

Non-ETD schizophrenic patients

ETD schizophrenic patients

25 17 F, 8 M 18 white, 5 black, 2 other Not applicable 32.2 (9.8) 3.1 (0.9) 3.2 (1.3)

35 11 F, 24 M 23 white, 10 black, 2 other 24 TD, 11 non-TD 33.1 (6.3) 4.4 (0.7) 3.3 (1.2)

18 9 F, 9 M 9 white, 8 black, 1 other 11 TD, 7 non-TD 33.5 (10.5) 4.1 (0.9) 3.4 (1.0)

Not applicable

14.2

(4.7)

Not applicable

12.1

(5.7)

Not applicable Not applicable

Not applicable

31.8 (9.4) 821.3 (539.2)

0.5

(0.8)

15.8 (12.4) 8.7

(6.3)

30.5 (6.6) 944.4 (458.5)

0.1

(0.3)

ETD indicates eye tracking disorder. TD indicates tardive dyskinesia. SES indicates socioeconomic status. Head of household was defined as major income earner in household when subject was 16 years old. Duration of illness was measured from onset of psychosis. Duration of treatment with antipsychotic medication was determined by adding all the periods during which the patient received antipsychotic medication. CPZ indicates chlorpromazine. CPZ equivalents (mg) were determined based on Gelenberg et al (1991). Parkinsonism was measured with the Maryland Psychiatric Research Center Involuntary Movement Scale. BPRS indicates brief psychiatric rating scale. a Mean (SD).

psychotic illness, duration of treatment with neuroleptic medication, neuroleptic dose in chlorpromazine equivalents, global parkinsonism score (from the IMS), or total BPRS score within 1 week of eye movement testing (all ps . .05). The normal comparison subjects, deficit patients, and nondeficit patients did not differ significantly with respect to age or SES of head of household (all ps . .10). The deficit and nondeficit patients did not differ significantly with respect to diagnosis of TD, age, SES of subject, SES of head of household, duration of psychotic illness, duration of treatment with antipsychotic medication, antipsychotic dose in chlorpromazine equivalents, global parkinsonism score (from the IMS), or total BPRS score within 1 week of eye movement testing (all ps . .10). The TD and non-TD patients did not differ significantly with respect to age, sex, or SES of subject (all ps . .10). The TD and non-TD patients did not differ significantly with respect to presence or absence of ETD, chi-square likelihood ratio 5 0.29, p 5 .59 (the sample was classified into the four cells as follows: ETD and TD, 11/53 subjects, 21%; non-ETD and TD, 24/53 subjects, 45%; ETD and non-TD, 7/53 subjects, 13%; non-ETD and non-TD, 11/53 subjects, 21%). The TD and non-TD patients did not differ

significantly with respect to any of the other ocular motor measures, all ps . .42, all effect sizes d , 0.3.

Eye Movement Procedure OCULOGRAPHIC APPARATUS. All subjects had eye movements tested. Eye movements were detected with infrared oculography using the Applied Sciences Laboratory Eye-Trac 210® recording system, which had a resolution of less than 0.25 deg and a time constant of 4 msec. Blinks were detected by Ag-AgCl electrodes attached above and below the center of one eye; a reference electrode was placed in the center of the forehead. The head was restrained using a forehead rest, chin rest, and head strap. The right eye, left eye, target, and blink analog signals were digitized at 333 Hz using a 16-bit analog-todigital converter. Data were monitored on a computer in real time and saved for later analysis using the Biopac MP100 system®. The target consisted of a small (0.7 cm2) disk of white light that moved horizontally on a screen 1.2 m in front of the subject. The screen was curved concavely with respect to the subject to eliminate errors from accommodative eye movements. The photometric contrast of the target was 2

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log units above the background luminance. The smooth pursuit target consisted of eight cycles of a 0.3-Hz sine wave traversing 6 10 degrees of visual angle. The sinusoidal target was preceded by a square-wave calibration routine. EYE MOVEMENT DATA ANALYSIS. Eye movement data were analyzed using Igor®, a software program written by WaveMetrics for general purpose waveform analysis, using macros customized in-house for analysis of eye movement data. The eye and target waveforms were calibrated using linear transformations with reference to a standard square-wave routine (212, 210, 25, 0, 5, 10, and 12 deg of visual angle), which preceded the sinusoidal target. From the eight cycles of the sinusoidal target, three contiguous cycles (10 sec) were chosen for analysis according to our previously described method (Ross et al 1988). This method minimizes inclusion of blinks and phenomena thought to reflect general inattention (that is, anticipatory saccades and periods of nontracking, which are defined below). Blinks that could not be avoided were replaced by NANs (“not-a-numbers” or gaps, an Igor® convention), so that they did not affect subsequent calculations. The eye tracking response to a smoothly moving target consists of two components, smooth and saccadic (Dodge 1903; Rashbass 1961). To optimize the identification of saccades, the eye waveform was low-pass filtered at 74 Hz (Bahill and McDonald 1983), using a finite impulse response filter (transition band 5 74 – 84 Hz, attenuation in reject band 5 80 dB). Saccades were identified with reference to position, velocity, and acceleration waveforms as events that had dynamic characteristics consistent with the “main sequence” for saccades (Bahill et al 1975).

Nontracking Periods. Nontracking periods were defined as sustained (.500 msec) periods during which the velocity of the eye was near zero, including no saccades. The percentage of time occupied by nontracking periods was measured, and then the nontracking periods were replaced by NANs, so that they did not affect subsequent calculations. Catch-Up Saccades and Anticipatory Saccades. Catch-up saccades were defined as saccades occurring during pursuit, in the direction of target motion, that took the eyes from a position behind the target to one on or near the target, thereby reducing position error (Friedman et al 1991). Because a sinusoidal target has zero velocity at each extremum, saccades that occur near the extrema may be related more to anticipation of target slowing or

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reversal of direction than to steady-state pursuit. Therefore, for the measurement of catch-up saccades, portions of the data in which the target was near an extremum (absolute value of target velocity less than 5 deg/sec) were not included. Catch-up saccade frequency was defined as the number of saccades/sec, after having excluded nontracking intervals. Other characteristics of catch-up saccades that were measured included amplitude and desired amplitude (defined as the amplitude that would have placed the eye exactly on the target) (Thaker et al in press b). Anticipatory saccades were defined as saccades that took the eye ahead of the target, were larger than 4 deg in amplitude, and were followed by a postsaccadic velocity of close to zero (Abel and Ziegler 1988; Clementz et al 1990). Anticipatory saccade frequency was defined as the number of anticipatory saccades/sec, after having excluded nontracking intervals. Position RMS Error. Position RMS error was calculated using our previously described method (Ross et al 1988), using the following definition:

RMS 5

3

O~r 2 s ! n

2

i

i51

n21

i

1 2

4

where ri is the position of the eye (response) at each ith point in time; si is the position of the stimulus at the same time; and n is the number of data points measured. Phenomena that may reflect general inattention, including periods of nontracking and anticipatory saccades (including their postsaccadic, near-zero velocity periods), were replaced with NANs so that they did not affect calculation of position RMS error. Gain and Variability of Gain. Gain was determined by measuring time-weighted average gain, using a slightly modified version of a method previously described (Friedman et al 1991). This method calculates the velocity of the smooth component of the eye divided by the velocity of the target, weighted by time. Since Friedman et al used a constant velocity target, and this study used a sinusoidal target, the method was modified accordingly as follows. The method required the prior removal of saccades (including anticipatory saccades and their postsaccadic nearzero gain portions) and periods of nontracking. Also, because gain is undefined when target velocity is near zero, portions of the data in which the target was near an extremum (defined here as absolute value of target velocity less than 5 deg/sec) were not included. This procedure left several intervals that were used for the calculation of

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gain. For each interval, the mean velocity of the eye and the mean velocity of the target were determined. As a result, the mean velocity of the target would usually be different for each interval (in contrast, if a constant velocity target had been used, the mean target velocity for each interval would have been the same). For each interval, a gain was computed by dividing the mean velocity of the eye by that of the target. Time-weighted average gain was determined by computing the mean gain of all these intervals, weighting by the time duration of each interval. Although gain is usually computed as an average, it can fluctuate during the pursuit of a target. A gain waveform can be created that is a plot of instantaneous gain versus time. The mean of this waveform would be mathematically equivalent to time-weighted average gain. (In practice, for the 78 subjects in this study, the intraclass correlation between time-weighted average gain and the mean of the gain waveform was .96, p , .0001.) Variability of gain was measured as the standard deviation about the mean of the gain waveform (gain SD). Phase Lag. Phase lag was obtained by subtracting the phase of the fundamental component (frequency 5 0.3 Hz) of the position of the eye from that of the target, and it was measured in degrees.

Statistical Analyses MIXTURE ANALYSIS.

To test hypotheses regarding mixture of normal distributions in eye tracking data, the program SKUMIX (MacLean et al 1976) was used. This method has been described in detail in several sources (MacLean et al 1976; McGue et al 1989; Levy et al 1993) and has been applied previously to eye tracking scores in schizophrenia (Clementz et al 1992; Iacono et al 1992; Sweeney et al 1993; Ross et al 1996a). The data were transformed into standardized z scores by subtracting the mean and dividing by the standard deviation. A chi-square test was used to determine if the distribution of the variable was skewed. If so, the following modified Box– Cox power transformation (MacLean et al 1976) was used to normalize the distribution:

y5

FS D G S D x 11 R

P

21 z

R P

where x is the original value, P is the power transformation value, R is a constant (always set equal to 6 in this study), and y is the power-transformed variable. A likelihood ratio statistic (G2) was computed to assess the significance of the increase in log likelihood for data

distributions when they were modeled with more than one normal distribution. The sample size and G2 were used to determine the p value by reference to Thode et al (1988), particularly their Table 1. This study demonstrated that G2 has approximately a chi-square distribution with 2 degrees of freedom. A statistically significant G2 indicates that the data are consistent with the higher component model, e.g., two normal distributions instead of one. This method was applied to data from the schizophrenic patients (n 5 53); there was an insufficient number of normal comparison subjects (n 5 25) to do mixture analysis on that group. COMPARISONS BETWEEN GROUPS.

To compare the oculomotor variables, a three-group multivariate analysis of variance (MANOVA) was performed using group as a between-subjects factor and the six specific oculomotor measures as the dependent variables. In the event that the omnibus test was significant, nonorthogonal post hoc contrasts included comparisons between the following groups: 1) normal comparison subjects and the pair of patient subgroups (to test for an effect of diagnosis of schizophrenia); 2) normal comparison subjects and ETD patients; 3) normal comparison subjects and non-ETD patients; and 4) ETD and non-ETD patients. The comparisons listed under 2), 3), and 4) were designed to determine how subgroup differences were related to an effect of schizophrenia. Using the Bonferroni correction, the comparison-wise alpha level was set at .0125. ASSOCIATION BETWEEN OCULOMOTOR VARIABLES. To determine the relationship between global and specific measures of pursuit, correlations between position RMS error and the specific oculomotor variables were examined for the normal comparison subjects and patients. To determine the extent to which correlations in the group of patients were due to correlations within subgroups of patients (ETD and non-ETD) and/or differences between subgroups, additional tests included correlations within subgroups and comparisons between subgroups (see next paragraph). Forward stepwise discriminant analysis was used to determine the extent to which the specific oculomotor measures predicted ETD or non-ETD classification. The sequence in which the specific oculomotor measures were entered into the model was determined by their ability to contribute to the discriminatory power of the model, from most to least. Variables were accepted (p , .05) or rejected (p . .05) by the model according to the significance level of the discriminant function F test. Fisher’s Exact Test was used to test the hypothesis that deficit and nondeficit patients would differ with respect to presence or absence of ETD.

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Figure 1. For the schizophrenic patients, the distribution of position RMS error was best fit by a mixture of two normal distributions. The point of overlap was used to divide patients into two subgroups, those with and those without eye tracking disorder (ETD). This point equalled 0.096 in transformed units and 1.10 deg in original units of position RMS error.

Results Mixture Analysis For the patients, the distribution of position RMS error z scores was significantly skewed, chi-square (1, n 5 53) 5 21.64, p , .01. Using power-transformed values (power transformation parameter 5 23.41), the G2 test for two versus one component models was significant, G2 (2, n 5 53) 5 8.01, p , .05. The model for three distributions would not converge after trying several different sets of initial values, suggesting that the data were not adequately described by a mixture of three normal distributions. Thus, the data were best fit by a mixture of two normal distributions. Based on maximum likelihood estimates, there was a 3.1 SD separation between the means for the components, with 34.3% of the patients falling in the higher (deviant) component. The point of overlap between the two theoretical normal curves was determined from the results of the mixture analysis (Figure 1). This point was based on powertransformed (hence, skew-corrected) data and corresponded to 0.096 in transformed standardized units or 1.10 deg in original units of position RMS error. This value was used to divide patients into subgroups with and without ETD. This procedure resulted in a classification of the 53 patients as 18 (34.0%) ETD and 35 (66.0%) non-ETD patients. One of the 25 normal comparison subjects (4.0%) fell above the cutoff value. Examples of smooth pursuit

eye movements in patients with ETD are shown in Figures 2 and 3. Nontracking epochs and anticipatory saccades occurred in very few subjects and, when they did occur, they occupied a very small portion of time spent tracking. More specifically, nontracking epochs did not occur in the normal comparison subjects or non-ETD patients, and they only occurred in 3 of the 18 (16.7%) ETD patients. For these 3 ETD patients, the values equaled 3.3%, 5.5%, and 5.7%, indicating that nontracking epochs occurred for only a very brief time even in these patients. Anticipatory saccades occurred in 2 of the 25 (8.0%) normal comparison subjects (values 5 0.10 and 0.11 saccades/sec); 3 of the 35 (8.6%) non-ETD patients (values 5 0.10, 0.20, and 0.20 saccades/sec); and 4 of the 18 (22.2%) ETD patients (values 5 0.10, 0.11, 0.22, and 0.53 saccades/sec). The finding that these phenomena occurred rarely and that the presence of mixture in position RMS error did not depend on these specific measures indicated that they were not importantly related to ETD; therefore, they were not considered in subsequent analyses. The means and standard deviations for the other oculomotor variables are shown in Table 2.

Comparisons A MANOVA, using group as a between-subjects factor and the six specific oculomotor measures as the dependent

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Figure 2. Example of smooth pursuit eye movements from a schizophrenic patient with eye tracking disorder (position RMS error 5 1.32 deg) and deficit syndrome. On the vertical axes, positive indicates rightward. On the velocity axis, saccades are truncated at 6 40 deg/sec. This patient had low gain (0.71), increased catch-up saccade desired amplitude (2.95 deg), and normal variability of gain (gain SD 5 0.33). Some saccades are hypometric.

variables, revealed a significant effect of group, Wilk’s lambda 5 0.46, F(2,75) 5 43.50, p , .0001. The results of the post hoc contrasts, which are described below in more detail, generally revealed the following: 1) the oculomotor performance of the ETD patients was much worse than that of the non-ETD patients and normal comparison subjects; and 2) the oculomotor performance of the non-ETD patients was much more similar to that of the normal comparison subjects than to that of the ETD patients. The effect sizes associated with the contrasts are shown in Table 3.

POSITION RMS ERROR. Although ETD and nonETD patients would be expected to differ on position RMS error, it was of interest to compare position RMS error between patients and normal comparison subjects. In comparison with the normal comparison subjects, the pair of patient subgroups had significantly larger position RMS error, F(1,75) 5 63.67, p , .0001, indicating an effect of a diagnosis of schizophrenia. Also, in comparison with the normal comparison subjects, the ETD patients had larger position RMS error, F(1,75) 5 143.47, p , .0001; and the non-ETD patients did not differ signifi-

Figure 3. Example of smooth pursuit eye movements from a schizophrenic patient with eye tracking disorder (position RMS error 5 2.34 deg). This patient had normal gain (0.90) but increased variability of gain (gain SD 5 0.83).

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Table 2. Means and Standard Deviations for the Oculomotor Variables Normal controls (n 5 25)

Position RMS error (degrees of visual angle) Pursuit gain Gain SD CUS freq (saccades/sec) CUS amp (degrees of visual angle) CUS desired amp (degrees of visual angle) Phase lag (deg)

Non-ETD patients (n 5 35)

ETD patients (n 5 18)

Mean

SD

Mean

SD

Mean

SD

0.67

0.21

0.74

0.17

1.67

0.44

0.93 0.39 1.20 1.34

0.05 0.13 0.58 0.55

0.88 0.37 1.33 1.54

0.08 0.12 0.62 0.48

0.74 0.61 1.53 2.14

0.10 0.31 0.76 0.85

1.60

0.42

1.67

0.42

2.94

0.80

2.01

1.83

2.65

2.09

7.20

3.20

ETD indicates eye tracking disorder; RMS indicates root mean square; gain SD indicates standard deviation about the mean of the gain waveform (a measure of variability of gain); CUS indicates catch-up saccade; freq indicates frequency; amp indicates amplitude.

cantly with regard to position RMS error, F(1,75) 5 0.84, p 5 .36.

F(1,75) 5 7.67, p 5 .007. An example of an ETD patient with abnormally large gain SD is shown in Figure 3.

GAIN. Gain was significantly lower for the ETD patients than for the non-ETD patients, F(1,75) 5 38.51, p , .0001, and normal comparison subjects, F(1,75) 5 60.20, p , .0001. Gain was not significantly lower for the non-ETD patients than for the normal comparison subjects, F(1,75) 5 5.22, p 5 .03. The pair of patient subgroups had significantly lower gain than did the normal comparison subjects, F(1,75) 5 36.78, p , .0001. An example of an ETD patient with low gain is shown in Figure 2.

CATCH-UP SACCADE FREQUENCY. Catch-up saccade frequency did not differ significantly between any of the three groups or between the pair of patient subgroups and the normal comparison subjects (all ps . .10).

VARIABILITY OF GAIN. Gain standard deviation (gain SD) was significantly greater for the ETD patients than for the non-ETD patients, F(1,75) 5 17.11, p , .0001, and normal comparison subjects, F(1,75) 5 17.11, p , .0001. Gain SD did not differ significantly between non-ETD patients and normal comparison subjects, F(1,75) 5 0.10, p 5 .75. The pair of patient subgroups had significantly larger gain SD than did the normal comparison subjects,

Table 3. Effect Sizes Associated with Post Hoc Contrasts

Position RMS error Pursuit gain Gain SD CUS freq CUS amp CUS desired amp Phase lag

ETD vs. normal

ETD vs. non-ETD

Non-ETD vs. normal

3.1a 22.5a 1.0a 0.5 1.2a 2.2a 2.1a

3.2b 21.6a 1.2a 0.3 1.0a 2.2a 1.8a

0.4 20.7 20.2 0.2 0.4 0.2 0.3

Effect size was defined as difference in means divided by pooled standard deviation (Cohen 1988). Abbreviations are explained in Table 2. a Indicates a contrast that was associated with a significant p value (,.0125). b Indicates that no statistical test was performed.

CATCH-UP SACCADE AMPLITUDE. Catch-up saccade amplitude was significantly greater for the ETD patients than for the non-ETD patients, F(1,75) 5 11.95, p 5 .0009, and normal comparison subjects, F(1,75) 5 18.63, p , .0001. Catch-up saccade amplitude did not differ significantly between non-ETD patients and normal comparison subjects, F(1,75) 5 1.60, p 5 .21. The pair of patient subgroups had significantly larger catch-up saccade amplitude than did the normal comparison subjects, F(1,75) 5 11.37, p 5 .001. CATCH-UP SACCADE DESIRED AMPLITUDE. Catch-up saccade desired amplitude was significantly greater for the ETD patients than for the non-ETD patients, F(1,75) 5 60.65, p , .0001, and normal comparison subjects, F(1,75) 5 18.75, p , .0001. Catch-up saccade desired amplitude did not differ significantly between non-ETD patients and normal comparison subjects, F(1,75) 5 0.25, p 5 .62. The pair of patient subgroups had significantly larger catch-up saccade desired amplitude than did the normal comparison subjects, F(1,75) 5 26.02, p , .0001. An example of an ETD patient with large catch-up saccade desired amplitude is shown in Figure 2. PHASE LAG. Phase lag was significantly greater for the ETD patients than for the non-ETD patients, F(1,75) 5 49.04, p , .0001, and normal comparison subjects F(1,75) 5 55.93, p , .0001. Phase lag did not differ significantly

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Table 4. Spearman Correlations between Position RMS Error and the Specific Oculomotor Variables

Gain Gain SD CUS freq CUS amp CUS desired amp Phase lag

Normal controls (n 5 25)

Schizophrenic patients (n 5 53)

ETD patients (n 5 18)

Non-ETD patients (n 5 35)

2.44a .31 2.19 .56a .58a

2.65a .62a 2.01 .49a .84a

2.22 .45 2.37 .43 .50a

2.31 .60a 2.16 .34a .65a

.41

.29

.18

.65a

Abbreviations are explained in Table 2. a Indicates correlations that were associated with p , .05.

between non-ETD patients and normal comparison subjects F(1,75) 5 1.15, p 5 .29. The pair of patient subgroups had significantly greater phase lag than did the normal comparison subjects F(1,75) 5 27.53, p , .0001.

Association between Oculomotor Variables CORRELATIONS BETWEEN GLOBAL AND SPECIFIC MEASURES.

Correlations between the global and specific oculomotor variables are shown in Table 4. Nonparametric correlations (Spearman’s) were used because position RMS error exhibited mixture in its distribution (see above).

DISCRIMINANT ANALYSIS. Forward stepwise discriminant analysis was used to determine the extent to which the specific oculomotor measures predicted ETD or nonETD classification. The ocular motor measures included gain, gain variability, catch-up saccade frequency, catch-up saccade amplitude, catch-up saccade desired amplitude, and phase lag. Four of the six specific oculomotor measures (gain, gain standard deviation, catch-up saccade desired amplitude, and catch-up saccade amplitude) were accepted by the model. In the final model, each of the four measures maintained a significant contribution (p , .05) to the discriminatory power of the model. A jackknife procedure revealed that the set of four specific measures correctly predicted subgroup membership in 18 of the 18 (100%) ETD patients and 32 of the 35 (91.4%) non-ETD patients. To enhance the understanding of the discriminant analysis, Pearson correlations between the specific ocular motor variables for the group of schizophrenic patients were determined (Table 5).

Relationship between the Deficit Syndrome and Eye Tracking Disorder The deficit and nondeficit patients differed significantly with respect to presence or absence of ETD; Fisher’s Exact Test, p 5 .002 (Table 6). An example of abnormal

Table 5. Pearson Correlations between the Specific Oculomotor Variables for the Group of Schizophrenic Patients

Gain Gain SD CUS freq CUS amp CUS desired amp Phase lag

Gain

Gain SD

CUS freq

CUS amp

CUS desired amp

1.00 2.29 2.37 2.53 2.62

1.00 2.06 .20 .25

1.00 2.18 .04

1.00 .80

1.00

2.52

.23

.43

.40

.66

Abbreviations are explained in Table 2.

smooth pursuit from a patient with deficit syndrome is shown in Figure 2.

Discussion Main Findings The results of this study clarify and extend previous ones that have examined the relationship between eye tracking disorder, specific measures of pursuit, and psychopathological domains of schizophrenia. Classification of patients into subgroups with or without ETD, defined using a global measure of pursuit, can be almost completely accounted for by several specific measures of pursuit. Eye tracking disorder in schizophrenia is characterized by abnormally low pursuit gain, increased variability of gain, and large, hypometric catch-up saccades. These results provide a bridge of interpretation between two major classes of previous studies of smooth pursuit eye movements in schizophrenia, those based on global or specific measures of smooth pursuit. Furthermore, ETD is strongly associated with the deficit syndrome, a major psychopathological domain of schizophrenia that is characterized by primary and enduring negative features.

The Relationship between Global and Specific Measures of Pursuit MIXTURE ANALYSIS. The distribution of position RMS error values in the schizophrenic patients best fit a mixture of two normal distributions. One subgroup of patients had a distribution of position RMS error values that was very similar to those of the normal comparison subjects; the second subgroup had values that were much larger than those of the comparison subjects. These findings replicate

Table 6. Eye Tracking Disorder (ETD) Was Significantly Associated with the Deficit Syndrome

Deficit Nondeficit

ETD

Non-ETD

9 9

3 31

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those of previous studies that used data from schizophrenic patients (Clementz et al 1992; Iacono et al 1992; Sweeney et al 1993; Ross et al 1996a) and are consistent with the findings of studies that used data from the relatives of schizophrenic patients (Gibbons et al 1984; Blackwood et al 1991). Based on the results of mixture analysis, the patients in this study were divided into those with and those without ETD. Because anticipatory saccades and nontracking periods were removed prior to the calculation of position RMS error, the presence of mixture cannot be attributed to these phenomena. This finding replicates a previous study (Ross et al 1996a) and shows that the presence of mixture cannot be attributed to an anticipatory saccade “artifact” (Sweeney et al 1993). ASSOCIATIONS BETWEEN GLOBAL AND SPECIFIC MEASURES.

In the group of schizophrenic patients, position RMS error correlated strongly with most of the specific measures of pursuit. The finding of a significant correlation between position RMS error and low gain replicates previous studies (Clementz et al 1992; Sweeney et al 1993); however, in this study, when the correlations between position RMS error and the specific measures were examined in the two subgroups of patients (ETD and non-ETD), they were generally weaker and often not statistically significant. This finding, along with the finding that the two subgroups differed strongly on these specific measures (see below), suggests that the correlations between position RMS error and the specific measures in the entire group of schizophrenic patients were due more to differences between subgroups than to correlations within subgroups (an example is shown in Figure 4). The results of the discriminant analysis showed that four specific measures (gain, variability of gain, catch-up saccade amplitude, and desired catch-up saccade amplitude) made significant and independent contributions to ETD versus non-ETD classification. Sweeney et al (1993) used a regression technique and found that, for the group of patients with schizophrenia, anticipatory saccade frequency and gain made independent and significant contributions to RMS error. Thus, the results of both studies are consistent in finding that gain makes a significant and independent contribution to global eye tracking error. As discussed below, our results showed that anticipatory saccades occurred rarely, and therefore anticipatory saccade frequency was not included in our discriminant analysis. COMPARISONS OF OCULOMOTOR VARIABLES.

With respect to most of the oculomotor measures, the performance of the ETD patients was worse than that of the

Figure 4. Low gain correlated significantly with position RMS error in the group of schizophrenic patients (Spearman’s r 5 2.65, p , .001); however, the overall correlation was due more to the difference in gain between ETD and non-ETD patients (effect size d 5 21.6) than to correlations within the subgroups (ETD: r 5 2.22, p 5 .37; non-ETD: r 5 2.31, p 5 .07). The cutoff score separating ETD from non-ETD patients is indicated. ETD indicates eye tracking disorder.

non-ETD patients and normal comparison subjects. In contrast, the oculomotor performance of the non-ETD patients generally was similar to that of the normal comparison subjects. Position RMS Error. The finding that ETD patients had larger position RMS error than the normal comparison subjects replicates previous studies (Sweeney et al 1993; Ross et al 1996a). Non-ETD patients and normal comparison subjects did not differ significantly with respect to position RMS error, consistent with a previous study (Ross et al 1996a), but in contrast with another study (Sweeney et al 1993). One possible explanation of the different findings is that the latter study included anticipatory saccades in the measurement of position RMS error, which might have resulted in increased position RMS error for both patient subgroups relative to the normal comparison subjects. All three studies found that the position RMS error of the non-ETD patients was much closer to that of the normal comparison subjects than to that of the ETD patients. Gain. The finding that pursuit gain was significantly lower for the ETD patients than for the non-ETD patients and normal comparison subjects replicates previous studies (Sweeney et al 1993; Ross et al 1996a).

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Gain was not significantly different between the nonETD patients and the normal comparison subjects, consistent with a previous study (Ross et al 1996a). Another study found a significant difference (Sweeney et al 1993). The effect sizes for the current study and the previous one by Ross et al were moderate and in the same direction as that of the study by Sweeney et al, leaving it unclear whether or not a difference exists in the two populations. Variability of Gain. Variability of gain, measured as the standard deviation about the mean of the gain waveform (gain SD), was abnormally large in the schizophrenic patients (an example is shown in Figure 3). Gain SD was significantly larger in the ETD patients than in the nonETD patients and normal comparison subjects. The nonETD patients and normal comparison subjects did not differ significantly. These findings provide quantitative evidence supporting previous qualitative descriptions of abnormal pursuit in schizophrenia as being erratic or containing oscillations (Ross et al 1988) or being irregular and wavy (Friedman et al 1995). The increased variability of gain could be due to abnormal movement of the eye, or it could be due to an artifact such as squinting or head movement. In either case, it is important, because it contributes significantly to global pursuit inaccuracy. If it reflects eye movement, it could be related to previously described oscillations during normal smooth pursuit (Robinson 1965; Robinson et al 1986; Lisberger et al 1987; Luebke and Robinson 1988; Goldreich et al 1992). If it reflects an artifact of measurement technique, it would be important to eliminate from analyses of eye movements. Catch-Up Saccade Frequency. In comparison with the normal comparison subjects, the schizophrenic patients had modestly increased frequency of catch-up saccades (effect size d 5 0.3), but the difference was not statistically significant. The lack of finding a significant difference is consistent with that of a previous study (SchmidBurgk et al 1982); however, several studies have found an abnormally increased frequency of catch-up saccades (Levin et al 1988; Moser et al 1990; Friedman et al 1991, 1992b; Campion et al 1992; Radant and Hommer 1992; Sweeney et al 1992; Ross et al 1996a), suggesting that the lack of finding a significant difference in this study may have been due to type II statistical error. In this study, frequency of catch-up saccades did not differ significantly between the ETD and non-ETD subgroups. This finding replicates a previous one (Ross et al 1996a), and the effect sizes for both studies were small. It appears that increased catch-up saccade frequency is unique among pursuit abnormalities commonly found in schizophrenia, in that it is associated with schizophrenia in general and is not limited to the ETD or non-ETD subgroup. It is not known why this abnormality is unique,

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but one could speculate that it is associated with a phenomenon that affects most patients, such as psychosis or the effects of antipsychotic medication. Catch-Up Saccade Amplitude. The schizophrenic patients had abnormally increased catch-up saccade amplitude. Two previous studies found no significant differences, but the effect sizes were small to moderate and in the same direction as in this study (Abel et al 1991; Ross et al 1996a). In comparison with the normal comparison subjects and non-ETD patients, the ETD patients had significantly larger catch-up saccade amplitude. A previous study found no significant differences, but the effect sizes were moderate and in the same direction (Ross et al 1996a). Catch-Up Saccade Desired Amplitude. The schizophrenic patients had abnormally increased catch-up saccade desired amplitude. Further analysis revealed that this abnormality was limited to the ETD patients; the non-ETD patients and normal comparison subjects did not differ with respect to this measure. Catch-up saccade desired amplitude reflects the amount of position error that has accumulated prior to execution of a catch-up saccade. Taken together, these findings suggest that the increased catch-up saccade amplitude and desired amplitude may be relatively specific to the ETD patients. Distinguishing between subgroups of patients may be important for detecting differences with regard to these measures. Abnormally large catch-up saccade amplitude may be associated with low gain (for review, see Levy et al 1993). The results of the discriminant analysis suggested that amplitude and desired amplitude made independent contributions to the predictive power of the model. This finding, along with the means for these variables, suggests that the ETD patients allowed greater position error to accrue before executing a catch-up saccade, and when the catch-up saccade finally was executed, it was relatively hypometric. Examples of hypometric catch-up saccades can be seen in Figure 2. Phase Lag. Phase lag was significantly greater in the ETD patients than in the non-ETD patients and normal comparison subjects, and the latter two groups did not differ significantly with respect to this measure. A previous study also found that phase lag was abnormally large in the ETD patients but, in contrast with the present study, the phase lag of the non-ETD patients was also abnormally large (Ross et al 1996a). The reason for the difference between the two studies is not clear. Anticipatory Saccades. Anticipatory saccades occurred in very few subjects and, when they did occur, they occupied a very small portion of time spent tracking.

Eye Tracking Disorder in Schizophrenia

These findings are consistent with those of other investigators who have not found anticipatory saccade frequency to be abnormally increased in schizophrenia (Clementz et al 1990; Moser et al 1990; Grove et al 1991; Friedman et al 1992a; Mather et al 1992; Radant and Hommer 1992; Sweeney et al 1992). In contrast with the current study, it has been reported previously that high RMS error patients have a significantly increased number of anticipatory saccades when compared with non-ETD patients and normal comparison subjects (Sweeney et al 1993). The difference between the two studies may have been due to the following two methodological differences: 1) The current study used a shorter segment of data than did the Sweeney et al study. The current study chose a 10-sec segment of data relatively free of blinks, nontracking periods, and anticipatory saccades. This method was chosen for the following reasons: a) the validity of this method has been supported by studies involving mixture analysis (Ross et al 1996a) and metabolism in oculomotor regions of the brain (Ross et al 1995); and b) anticipatory saccades may be more closely associated with general inattention than with a specific oculomotor defect (Levy et al 1993). In contrast, the study by Sweeney et al included all the data from a 60-sec period, which contained a greater frequency of anticipatory saccades than found in the current study. 2) Unlike the current study, the Sweeney et al study included anticipatory saccades in the calculation of position RMS error. Anticipatory saccades, which greatly increase position RMS error, may have influenced the definition of high and low RMS error groups in the Sweeney et al study. One way of attempting to resolve the discrepancy between the two studies would be to define ETD and non-ETD subgroups after excluding anticipatory saccades, and then measure frequency of anticipatory saccades over a 60-sec time interval.

Abnormal Smooth Pursuit and the Deficit Syndrome of Schizophrenia The results of this study showed a strong association between the deficit syndrome of schizophrenia and ETD. A majority of deficit patients had ETD (9 of 12; 75.0%), whereas only a minority of nondeficit patients had ETD (9 of 40; 22.5%). These findings extend previous ones from this laboratory, which showed that abnormal smooth pursuit in response to step-ramp stimuli was particularly pronounced in patients with deficit syndrome (Ross et al 1996b). PREVIOUS STUDIES OF EYE TRACKING DISORDER AND NEGATIVE SYMPTOMS.

These findings support previous ones of an association between abnormal smooth pursuit

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and negative symptoms (Blackwood et al 1991; Katsanis and Iacono 1991; Sweeney et al 1994). In contrast, other studies have not found a significant association (Keefe et al 1989; Kelly et al 1990; Lieberman et al 1993; Sweeney et al 1993). These conflicting results stand in contrast to those from studies involving subjects with schizophrenia spectrum traits, which have consistently found a relationship between ETD and negative symptoms or schizoid traits (Siever et al 1982, 1984, 1990, 1994; Simons and Katkin 1985; Kendler et al 1991; Clementz et al 1992; Thaker et al in press a). EYE TRACKING DISORDER IS ASSOCIATED WITH PRIMARY ENDURING NEGATIVE SYMPTOMS. The negative symptoms rated in the spectrum studies were likely to be primary to the illness, and, in the current study, deficit syndrome was defined by the presence of primary and enduring negative symptoms. Thus, ETD appears to be associated with primary and enduring negative symptoms and not to be associated with secondary or transient negative symptoms. Previous studies that did not find an association between ETD and negative symptoms may have failed to do so because they used a rating scale (the SANS; Andreasen 1989) that does not distinguish negative symptoms on the basis of whether they are primary or secondary, or whether they are temporary (state related) or enduring (trait related). AND

EYE TRACKING DISORDER AND THE DEFICIT SYNDROME MAY SHARE A COMMON PATHOPHYSIOLOGY.

Independent groups of researchers have previously theorized that eye tracking disorder and the deficit syndrome of schizophrenia each reflect a discrete pathophysiological process (Carpenter et al 1988). The direct link between these two phenomena, reported here, suggests that the same discrete process underlies both. Abnormal smooth pursuit eye movements and deficit syndrome may share a common pathophysiology of cortical–subcortical cerebral circuits, and, depending on which circuits are affected, deficit pathology and/or poor tracking may result. Previous imaging studies in schizophrenia are consistent with this idea. Both phenomena are associated with decreased metabolism in frontal and parietal association cortex (Tamminga et al 1992; Ross et al 1995) and altered volume or metabolism of the caudate nucleus (Buchanan et al 1993; Ross et al 1995).

This study was supported in part by the Scottish Rite Schizophrenia Research Program, N.M.J., USA, and NIMH grants CRC MH40279, R01 MH43031, and R01 MH49826. Gratitude is expressed to John Ellsberry, Teresa Key, and Michael Nolet for their assistance in collection and analysis of the data.

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