Selected quantitative EEG (QEEG) and event-related potential (ERP) variables as discriminators for positive and negative schizophrenia

Selected Quantitative EEG (QEEG) and Event-Related Potential (ERP) Variables as Discriminators for Positive and Negative Schizophrenia Montserrat Gerez and Armando Tello

Heterogenei U is a major obstacle in the search for biological substrates in schizophrenia. The positive and negative distinction, even [f too simplistie, may improve our understanding of underlying processes. Frontostriatal deficits have been related to negative symptoms, while clv~;~nction of the dominant temporal lobe appears more relevant to the generation of positive symptoms. Despite interactions between the subsystems, d~(ferent neurophysiological profiles could be expected for patients predominantly affected at each of those levels. We performed discriminant analysis on 10 neurophysiological variables (hypothesis-related) in schizophrenic patients grouped by positive or negative symptoms (PANSS), obtaining a discriminant that correctly classified the sample. The fimction was then tested in a new sample of patients with schizophrenia, affeetive psychoses, and controls, cklssilS"ing subjects with 78% sensitivity and 85% specificity. Our flndings suggest that predominantly negative and positive schi~.ophrenics have different neurophysiological profiles, which are consistent with the hypotheses of hypo.fi'ontaliO' and temporal lobe dy.~function, respectively. A linear relation between discriminant scores and PANSS ratings might reflect coexisting pathologies or compensato o" interactions in the mixed subgroup. Key Words: Schizophrenia, positive, negative symptoms (PANSS), QEEG, EEG, P300

Introduction Although considered a single disorder, schizophrenia is most likely a mixture of different pathogenic entities. Several authors have argued for a separation of negative and positive (Crow 1980; Andreasen 1985: Kay et al 1987a), or deficit-non deficit (Carpenter et al 1988) syndromes, claiming two symptomatic clusters with different course,

From the Neurophysiology IAT. MGI and Psychiatry i MG} Departments. Hospilal Espafiol Mdxico, Col Granada. Mexico Ad&ess reprint requests to Monsterral Gerez, MD. Ph,D. Neurophysiology and Psychiatry Departments. Hospital E',pafiol de M6xico. EjOrcit~ National 613. Sala 8, Col. Granada. I 1520. Mexico DF. Received J une 16. 1993: revised July 1g. 1994

© 1995 Societ), of Biological Psychiatr~

family and personal history, and response to treatment (for review, see Andreasen et al 1990). Several criticisms have been raised against this model, which seems to oversimplify the rather complex nature of the disease (de Leon et al 1992; Minas et al 1992; Peralta et al 1992: Klimidis et al 1993). Nevertheless, these approaches have been useful for clinicopathological correlations (Carpenter and Buchanan 1989) and may help in the search for biological substrates. The negative syndrome is characterized by blunted affect, apathetic social withdrawal and impaired abstract thinking (Kay 1987a). Patients frequently have premorbid personality traits and poorer prognosis (Peralta et al 1991; Fenton and McGlashan 1991; Addington and Addington 1993), soft frontal neurological signs (Merriam et al 1990), and 0006-3223/95/$09.50 SSDI 0006-3223(94)00205-H

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cognitive impairment (Addington and Addington 1993, Strauss 1993). Although the association of ventricular enlargement with negative symptoms has been controverted (see review by Marks and Luchins 1990), other neuroimaging techniques have shown frontal, thalamic, and basal ganglia abnormalities in patients with high negative ratings (Volkow et al 1987; Guenther et al 1988: Hoffman et al 1991 : Williamson et al 1991 ; Young et al 1991 ; Andreasen et al 1992; Wolkin et al 1992; Siegel et al 1993). From this evidence, and some biochemical and clinical similarities with Parkinson's disease, the "hypofrontality'" hypothesis has been extended to embrace the wholeness of frontodiencephalic circuits (Sandyk and Kay 1990; Pantelis et al 1992; Bermanzohn and Siris 1992). Predominant features of the positive syndrome are delusions, bizarre thinking, and hallucinations that can be multimodal. History is often unremarkable (Kay et al 1987a), except for very few patients with remitted temporal lobe epilepsy (Trimble 1991 ). Clinical similarities with the schizophreniform epileptic psychosis have suggested a relationship between positive symptoms and overactivity in the dominant temporal lobe (Slater and Beard 1963: Wolf and Trimble 1985; Roberts et al 1990; Gloor 1991 ). Supportive evidence can be found along several lines, such as intracranial recordings (Heath 1986) and metabolic studies during hallucinations (Cleghorn et al 1990: Suzuki et al 1993), and reports of focal neurophysiologieal (Morihisa et al 1983; Flor-Henry 1987: McCarley et al 1989, 1991 : Ohta et al 1993), and neuropsychological abnormalities (Silverstein et al 1991: Mathew et al 1993; Wexler et al 1991: Strauss 1993), as well as anatomical changes in patients with positive symptoms (McCarley et al 1989, 1993; Barta et al 1990; O' Donnell et al 1993; Bogerts et al 1993). Hypofrontality and abnormal lateralization are not universal findings in schizophrenia (Pfefferbaum et al 1989; Michie et al 1990), nor have they always been related to either negative or positive symptoms (Stirk et al 1993: Buchanan et al 1993). Discrepancies may arise from difficulties in identifying primary and secondary symptoms, as well as from the complexity of the dysfunction, which may be poorly represented by isolated variables. Yet, neurophysiological differences would be expected between the negative and positive syndromes, if the former was related to a frontal deficit and the later to an overactive focal dysfunction. This study addressed three questions: I ) Are there differences in neurophysiological profiles between the two subtypes? 2) How specific are those differences? 3) What would be the profiles of patients with mixed symptoms? The study was conducted in two stages: the first, to develop a discrimination function with a set of neurophysiological variables, from a sample of strongly positive and strongly negative schizophrenics; the second, to test the discrimination function in a new sample, with positive, negative,

and mixed schizophrenics, affective disorder patients, and controls. Methods

Subjects and Groups FIRST STAGE. Ninety-one patients fulfilling DSM-IIIR criteria for schizophrenia (APA 1987) were evaluated according to the positive and negative syndrome scale, PANSS (Kay 1987b). The scale includes seven positive, seven negative, and 16 general psychopathology items, individually graded in a 7-point severity scale. Composite scores were obtained by subtracting positive and negative scores. Seventeen patients with a composite score -> 3 were included in the positive subgroup, and 17 with a score -< - 8 were in the negative subgroup. Exclusion criteria were history of seizures, head injury, neurologic disorder, left-handedness, electroconvulsive therapy, substance abuse in the past 2 years, psychotropic medication other than neuroleptics and biperiden in the last 2 weeks, or presence of another DSM-III-R Axis I diagnosis. All patients were at a remission state, more than 2 years after first episode and without acute manifestations. They all had been treated with neuroleptics for more than 1 month, with good response in terms of general psychopathology, yet persistent positive or negative symptoms. General psychopathology scores, chronicity, age, neuroleptic dose and type, extrapyramidal symptom ratings (Alpert et al 1978), and Hamilton depression scores (Lyerly 1978) did not differ significantly between the groups (Table 1). Nevertheless, additional correlation analyses were conducted on the last three variables indepen-

Table I. Demographic Characteristics of the Discriminant Sample Group N Sex Age (yr) Chronicity (yr) General psychopathology Extrapyramidal scores DSM-III-R Subtype Paranoid Undifferentiated/ hebephrenic Residual/simple Neuroleptic type Haloperidol Phenoliazines Clozapine Nem'oleptic mean dose (CPZ eq) Biperiden mean dose (mg/d) CPZ = chlorpromazine.

Negative

Positive

17 M 14/F3 29 ± ?.6 7.6 ± 3.4 19 ± 4.5 3.00 ± 1.94

17 M9/F8 31 ± 5.5 5.8 2 4.7 22 -~ 3.6 2.12 ~+ 1.59

6

12

b 5

4 I

3 9 5

5 9 3

230 ± 48. I

196 ± 56.2

2.0 _+ 1.9

1.9 ± 1,7

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Table 2. Demographic and Clinical Data of the Test Sample

Age (yr)

Positive

Negative

31.2 _+ 6.3

28.8 ± 6.9

M7/F5

M8/F4

Sex

Mixed 29.5 ± 4.t

Affective

Control

32.2 + 13.4

30.9 ± 9.0

M5/F7

M5/F7

M6/F6

Psychiatric diagnosis

I 0 paranoid 2 undifferentiated

3 paranoid 5 residual 4 undifferentiated

7 paranoid 4 undifferentiated I hebephrenic

3 pure manic 9 mixed bipolar

5 depression 3 anxiety

Neurological diagnosis

none

I encephalitis (7 years before study)

none

1 peripheral neuropathy

3 spinal trauma 1 myelopathy

Chronicity

7.5 _+ 5.9

7.3 ± 6.8

6.5 ± 3.4

5.2 _+ 5.3

5.4 -+ 6.31

Medication

4 HAL 5 PHZ 3 clozapine 4 BZD 6 biperiden

2 HAL 6 PHZ 4 clozapine 2 BZD 7 biperiden

5 HAL 6 PHZ 1 clozapine 4 BZD 5 biperiden

3 HAL 1 PHZ 5 CBZ 7 CaLi 6 BZD

8 BZD 3 TCA 5 fluoxetine

Substance abuse

3 alcohol (R) 1 cannabis (R)

4 alcohol IRI

3 alcohol (R) I alcohol (A)

3 alcohol (R) 1 alcohol (A)

1 alcohol (R) 2 alcohol and cocaine (A)

HAL = haldol: PHZ = phenothiazinics; CBZ = carbamazepine, TCA = tricyclic antidepressants: BZD = benzodiacepines: CaLl = lithium carbonate. R = remitted, more than 2 years abstinence: A = active, except during hospitalization.

dently with PANSS and discriminant (L)-scores. For that purpose, neuroleptics were divided into three groups depending on their ratio of 5-HT to dopamine (DA) antagonism (Tamminga and Gerlach 1987) and dummy-coded: 3 for clozapine and other broad spectrum compounds, 2 for pbenothiazines, and I for strongly dopaminergic drugs, mostly haloperidol. Males were overrepresented in the negative group; therefore sex was included as control variable in the discriminant analysis. SECOND STAGE. The discriminant function was tested in a different population of 12 positive, 12 negative, and 12 mixed schizophrenic patients, 12 patients with affective psychoses, and 12 controls with no personal or family history of psychoses. Schizophrenia and affective disorder diagnoses were made according to the DSM-III-R, schizophrenia subgroups according to the PANSS scale, including in the mixed group patients with a PANSS composite score between -7 and 2. Schizophrenic patients were at the resolution phase of an acute episode, with a general psychopathology score > 31, and had received neuroleptics for the last month. Control subjects were hospitalized for neurologic or nonpsychotic psychiatric illness and had not been treated with neuroleptics. Only patients with substance abuse during the last month were excluded in this sample. Clinical details of this sample are found in Table 2.

Recording and Analysis The eyes-closed, resting EEG was recorded from 21 monopolar electrodes (International 10/20 System) referenced to linked earlobes, impedance below 5 kl), eye movements monitored with epicanthal electrodes (Gasser et al

1992). Special care was taken to assure an awake, relaxed behavioral state by looking at the EEG trace and talking to the patient whenever signs of light drowsiness or increased muscle tension were observed. Recordings were suspended if the patient was unable to sustain a relaxed state for at least five consecutive minutes. Five patients were rescheduled for a second session in which an acceptable record was obtained. Forty-eight contiguous artifact and epileptiformfree EEG epochs, 2.5 seconds each, were collected after a 3-minute adaptation period and analyzed in a Cadwell Spectrum 32 machine. Power spectral analysis (Fast Fourier Transform) for each monopolar derivation, power asymmetry (P~JP,~h, = A; where P is absolute power) and interhemispheric coherence (Q~eftr~gh,/P~ef, Pngh~= C; where Q is cross spectral power) were computed between homologous sites by the system's software (for details on calculations see John et al 1987). The auditory event-related potentials, oddball paradigm Onofrj et al 1990), were recorded with the same electrode placements and reference, filtering 0.5-50 Hz, independently averaging the response to common (1000 Hz) and to rare (1500 Hz) binaural stimuli at 70 dBSL. Event-related potentials (ERPs) were recorded eyes open with center fixation point, after the 20 minutes of EEG and a short rest. Patients were instructed to count silently the 20% randomly presented high tones (40-50 total) within a stream of low tones, 1.2 msec mean interstimulus interval. Performance was similar for the two groups, with an average accuracy of 92%. Sampling of 256 data points for a 750 msec epoch started 100 msec before stimulus (baseline). Amplitude measurements were taken from the difference between the rare and the frequent responses with a time window from 280-400 msec after the stimulus for the P300

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and 180-280 msec for the N200. All variables were logtransformed before the analysis with natural log for power, asymmetry, and amplitude, and log [C2/( 1-C2)] for coherence (John et al 1987; Niwa and Hayashida 1993). Group means for all electrode sites were used to construct representative maps, although only the following neurophysiological variables were included in the discriminant analysis: anterior (Fz) absolute power of alpha (7.5-12.5 Hz), theta (3.5-7,5 Hz), and left temporal (T3) fast beta (20-30 Hz), anterior mean frequency (Fz), frontal interhemispheric alpha coherence (F3 F4), temporal interhemispheric alpha coherence (T3 T4), wideband power temporal asymmetry (T3/T4, 3.5-30 Hz), P300 temporal amplitude ratio (T3/T4), P300 amplitude (Pz), and N200 amplitude (Fz). Variable selection was guided by their expected potential as discriminators, the highest being for those previously reported abnormal in schizophrenia (for EEG variables, see Itil 1977, Flor-Henry 1987, Shagass et al 1982, 1984, Zhan 1986; for ERP variables, see reviews by Shagass 1983, Pritchard 1986, Ford et al 1992). To minimize technical error, only measures routinely used in our laboratory were considered, delta power was excluded to avoid eyemovement artifact (Williamson and Mamelak 1987; Karson et al 1990; Small et al 1987), and ERP latencies because we have found low test-retest reliability in schizophrenic patients. Further reduction was theoretically driven, based on different physiopathogenic hypothesis for negative and positive symptoms. Abnormalities in the N200 and P300, but not in the N 100 and P200 components, have been reported in frontal or basal ganglia syndromes (Knight et al 1980; Ebmeier et al 1992; Takeda et al 1993; Arendt et al 1993; Nasman and Dorio 1993). Consistently, a N200 generator has been located at prefrontal regions (McCarthy and Wood 1987; Smith et al 1990: Onofrj et al 1990, 1991 ), while the N ! 00 and P200 are generated at primary association areas. Increased frontal theta, decreased mean frequency, and changes in interhemispheric coherence and alpha gradient are also found in dementias with predominant anterior involvement (Brenner et al 1986; Leuchter et al 1987, 1992, Szelies et al 1992: Newton et al 1993). The following variables intended to identify frontodiencephalic dysfunction: absolute theta and alpha power and mean frequency at Fz, frontal interhemispheric alpha coherence, and P300 and N200 amplitudes. Focal lesions cause different changes in EEG and ERP measures, depending upon their impact on neuronal activity (Harner et al 1987; Kowell et al 1987; Nuwer ! 988; Hughes et al 1991; Salinsky et al 1992; Hamburger and Triantafyllou 1990; Rugg et al 1991; Dolisi et al 1990). To identify' unilateral temporal lobe dysfunction, we selected wideband temporal asymmetry, a measure that would reflect either a significant power increase in one band or subtle

changes in a wider spectrum. Of particular interest was fast beta activity because it frequently increases over epileptogenic zones (Nealis and Duffy 1978; Lombroso and Duffy 1982). P300 temporal asymmetry, measured at the time of maximal Pz amplitude, would be affected by either amplitude difference or asynchrony between the temporal regions. Additional evidence of unilateral involvement was expected from changes in temporal interhemispheric coherence (Coger and Serafetinides 1990).

Statistical Analysis FIRST STAGE. Multiple correlation coefficients and beta weights were calculated with standard formulas after the removal of the partial correlation with the control variable, sex (Marascuilo and Levin 1983). Discriminant scores were standardized by subtracting the sample mean and dividing by the standard deviation of the sample discriminant scores, variance set to one. The likelihood and relative probability of group membership for each subject were obtained from the subject's discriminant score. Probability curves of discriminant scores were drawn for each group and compared with Hotelling's T squared. SECOND STAGE. Beta weights derived from the first stage were used to calculate the discriminant scores and relative probability of group membership for the new sample. Probability curves were drawn for each group and compared to the curves in the discriminant sample. The correlation between PANSS scores and discriminant scores for the schizophrenic group as a whole was also calculated.

Results Stage One GENERAL FINDINGS. The proportion of patients with marginal or abnormal records at visual inspection was similar for the two groups (Table 3). Even though the negative subgroup showed more diffuse changes and lower ERP amplitudes, group differences were not significant, nor could individual patients be classified by their records. DISCRIMINANT ANALYSIS. Coefficients, standard deviation of coefficients, and standardized beta weights of the multiple correlation are shown in Table 4. The correlation explained 76% of the variance in the sample (multiple correlation coefficient = 0.76, standard error = 0.29). Probability curves of discriminant scores were bell-shaped (Figure I), and the mean of the two groups significantly different (Hotelling's T 2 = 21.06; F = 4.87; df 11,24; p < .OO5). The negative group was characterized by higher absolute power in theta and alpha, lower mean frequency, lower

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Table 3. Visual EEG and EP Findings in the Two Groups Clinical group

Negative

Positive

Normal EEG Slight slowing diffuse focal Moderate slowing diffuse focal Epileptic changes" non focal focal N200 amplitude P300 amplitude p~V

10 4 3 1 3 2 I 5 4 I - 3 +- 1.1 7 + 2.0

11 3 I 2 I 0 I 6 4 1 - 5 + 1.4 9 Jr 2.8

<'Epileptiform activity: spikes, sharp waves, spike and wave complexes (single 3/see, 4-5/see. and runs of 6/see if voltage exceeded two times that of the background and were anteriorly located).

frontal interhemispheric coherence, and lower N200 and P300 amplitudes (Figure 2). No major asymmetries were observed in this group. Focal changes appeared in the topographic maps of positive schizophrenics (Figures 3 and 4). Focal involvement was reflected in the discriminant /'unction by interhemispheric temporal wideband power asymmetry; temporal coherence was decreased in the positive group. With a 0.75 cutoff, 13 negative and 14 positive schizophrenics were correctly classified; no one was misclassified in this sample (correct classification 0.79).

Stage Two The probability distribution of the negative and the positive groups in the test sample did not differ significantly in mean nor shape from those of the di scriminant sample (Figure 5). The distribution of mixed schizophrenia L scores was not bell-shaped, but somewhat bimodal. Yet, the group mean was close to zero (distribution grand mean), as were those of the affective psychoses and control groups. Two patients from the negative and three from the positive groups did not

reach classification level; one negative subject was misclassifted as positive. The misclassified subject, had a clear predominance of negative symptoms (PANSS score - 1 3 ) but had no premorbid personality, no family history of schizophrenia, and a history of encephalitis 7 years before the schizophrenic symptoms. Within the mixed group, 10 patients did not reach classification level, and two were classified as positive and one as negative (correct classification for the three schizophrenic subgroups: 0.78, specificity 0.89). One control subject--spine i n j u r y - - w a s misclassifled as positive schizophrenia and another as negative schizophrenia. This last patient, 48 years old, was hospitalized because of major depression with slight cognitive impairment. At follow-up he showed tomographic and clinical evidence of selective frontal lobe disease. Two affective patients, floridly psychotic, were misclassified as positive schizophrenics, and one as negative. The overall test sample correct classification was 0.78, specificity 0.85. There were no significant differences in L scores between genders in either the schizophrenic (mean L scores for schizophrenic females 0.69 -+ 3.18, males 0.18 + 3.53), nor the nonschizophrenic subgroups (nonschizophrenic females -0.37 _+ 1.50, males 0.09 _+ 1.44). And, there was no direct or inverse correlation of sex with L scores (schizophrenic subgroup r~x ~,= .006; nonschizophrenic r~x ~.= .024). The relationship among the three schizophrenic groups was further explored by calculating the correlation of discriminani scores and PANSS scores for all schizophrenics in both samples. PANSS scores were linearly related to discriminant scores. The 0.73 correlation coefficient was significant at p < .005) (t = 12.73. df = 68). ADDITIONAL ANALYSIS. No significant correlations were found for either PANSS or discriminant scores with neuroleptic type, extrapyramidal symptoms, or depression ratings in the discriminant sample (PANSS R-" = .022, L scores R 2 = .018). Also, there was no correlation of sex

Table 4. Results from the Multiple Correlation and Standardized Beta Weights Variable Alpha coherence (T3 T4) Theta absolute power (Fz) P300 asymmetry (T3FF4~ Fast [3 absolute power (T3) N200 amplitude (Fz)<' Mean frequency (Fz) Wideband asymmetry (T3FF4) Alpha coherence (F3 F4) P300 amplitude (Pz) ° Alpha absolute power (Fz) Sex

X cocflicienl

SEM of X coefficient

0.1 I -0.09 -0.10 -0.04 I). 15 I). 19 0.12 ll.02 (!. 13 -0. I 1 0.31

0.05 ll.05 0.1)5 0.06 0.07 0.05 0.06 0.07 0.(15 0.06 0.10

<'Expected maximal locations in the auditory paradigm.

[3 weight

Standardized [3 weight

Correlation with L score

I.(17 -0.88 -0.88 -0.38 1.12 2,02 0.90 0.15 1.34 -0.84

0.16 - 1.04 -2.23 0.47 I. 12 1.66 0.54 -0.21 0.98 - 1.20

0.16 0.17 0.27 0,08 0,33 0.14 0,44 0.19 0.07 0,45 0.002

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0.5

Hotelling's T'- - 21.06 Log

=

0

-9

-3.48

[, p~, = 3.06

I

I

0

9

Figure I. Discriminant scores' probability distributions of the two groups in the discriminant sample (negative group left, positive right; Lpos mean of discriminant scores for the positive subgroup, LNEUfor the negative subgroup).

and discriminant scores for any group in the test sample (schizophrenic R 2= .029, nonschizophrenic R -~= .04).

Discussion Methodological Issues STATISTICAL ASPECTS. Multivariate statistics are intuitively appealing for the study of altered higher brain function. Yet, these techniques convey increased demands particularly hard to meet in our field, such as building large enough samples that are clinically uniform. Our sample was small for the number of variables, and the results should be seen as preliminary. The multivariate function must be normally distributed. Although logarithmic transformation normalizes individual EEG and ERP variables (Gasser et al 1982; John et al 1987), and our distributions of L scores were bell shaped, this does not guarantee normality of the overall function. Multivariate differences between the groups do not imply that they would differ significantly in individual variables. This issue limits the extent to which our findings can be related to univariate work. CLINICAL AND PHARMACOLOGICAL ASPECTS. Gender influences neurophysiological measures (Duffy et al

1993), and its effects may differ in schizophrenia (Josiassen et al 1990), Males were overrepresented in the negative subgroup of the discriminant sample. We attempted to remove sex effects from the discriminant by including gender as a control variable to be partialed out from all other con+elations. The efficacy of these approach was corroborated in the test sample, since there was no relationship between sex and L-scores for either the schizophrenic or the nonschizophrenic subgroups. All schizophrenic patients were on low-dose maintenance treatment (Tables 1 and 2). Neuroleptics may alter clinical profiles by simulating negative and obscuring positive manifestations. Neuroleptic type could also have in-

fluenced the discriminant because of different dopamine/serotonin affinity ratios (Small et al 1987; Galderisi et al 1991; Saletu et al 1990; Czobor and Volavka 1993). Despite no significant differences between subgroups in neuroleptic type, depressive symptoms, or extrapyramidal side effects, we conducted additional analyses to identify potential confounding effects. As expected, neither PANSS or L scores correlated with these measures (Table 5). Neurophysiologically, neuroleptics tend to normalize deviant patterns, often in parallel with clinical improvement (Duncan et al 1987; d'Elia et al 1977; Etevenon et al 1979; Merrin et al 1986; Schellenberg et al 1992; Czobor and Volavka 1992; Merrin and Floyd 1992; Nagase et al 1992). Yet, some abnormalities persist (Itil 1977; Pass et al 1980; Pritchard 1986; Duncan et al 1987; Blackwood et al 1987; Merrin et al 1989; Westphal et al 1990; Radwan et al 1991; Nagase et al 1992; Faux et al 1993). Persistent symptoms are more likely to reflect essential features of the disease (Hoffman et al 1991 ; Keefe et al 1991 ), since they resemble premorbid traits (Peralta et al 1991; Husted et al 1992; Addington and Addington 1993) and are not related to medication or psychotic decompensation (Kay and Lindenmayer 1991 ; Goldman et al 1991 ). Persistent neurophysiological changes may also be closer to the essential alterations. Our discriminant sample intended to represent patients with such changes. PATIENT SELECTION AND CLASSIFICATION. Patients

were classified during remission, using a scale that emphasizes identification of primary symptoms and excludes general psychopathology from the classification items. One reason to challenge the concept of positive and negative syndromes has been that symptom predominance varies over time (Maurer and Hafner 1991: Marneros et al 1992). For these syndromes to be considered distinct nosological entities+ they should be longitudinally stable. Only when assessed in the remitted phase does the positive/negative distinction appear stable (Lindenmayer et al 1986; McGlashah and Fenton 1993).

Findings Two neurophysiological profiles were identified with significantly different means and similar probability distributions in both the discriminant function and the test samples. The discriminant function was capable of classifying individual subjects from the test sample 0.77 sensitivity and 0.85 specificity. The negative subgroup was characterized by increased anterior theta and alpha and decreased mean frequency, frontal coherence, and N200 amplitude. Since most variables selected to identify a frontostriatal deficit were good discriminants for this subgroup, our findings are consistent with the hypofrontality hypothesis of negative

40

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Reference Group: NEGATIVE S C H I Z O P H R E N I A M o n o p o l a r Group Means Theta

Beta2

Alpha

Absolute Power 2

( 0 - 2 5 uV )

Power Asymmetry (0-25%)

Coherence

(o -5o% )

N200

P300

3O uV, 750

ms

P300

N200

(o-lo uV)

(o-3 uV)

Figure 2. Group mean maps of EEG power, asymmetry, and coherence (lst-3rd rows), and ERP (4th row) amplitude maps (right) and trace (left), for the negative group. Increased frontal theta and alpha, decreased frontal coherence, and N200 amplitude without major asymmetries were found in this group. Gray scaling for the ranges specified below row labels.

QEEG and ERP Discriminators in Schizophrenia

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Reference Group: NEGATIVE SCHIZOPHRENIA Monopolar Group Means Theta

Alpha

. --.,

Beta2

Absolute Power

(o-25,uv 2)

Power

Asymmetry (0-25%)

Coherence

(o-5o%)

3° I.... . 3 o o

. . . . . . . . . . . . .

UV 'I 750 ms

P300

(o-lo/uv)

N200

(o-3j~vj

Figure 3. Group mean maps for the posmve group (same explanation as Figure 2). Characteristic findings were: left temporal wideband power increase, more evident in the asymmetry maps, decreased temporal coherence, and P300 focal amplitude decrease (note similar topography as the EEG power increase).

42

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]9 9 5 : 3 8 : 3 4 4 9

R e f e r e n c e Group: N O N - P S Y C H O T I C C O N T R O L S M o n o p o l a r Group Means Theta

+ Beta2

Alpha

Absolute Power 2 ( 0 - 2 5 ~uV )

Power Asymmetry (0-25%)

Coherence

(0-50%)

2/ i

N200 P300

30 uV 7 5 0 ms

P300

(o-lojuv)

N200

(o-3juv)

Figure 4. Group mean maps of the control group from the test sample (included only for comparison).

QEEG and ERP Discriminators in Schizophrenia

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I ~ L neg

= -3.48

L pos test-= 3.55

liD" L n~g

= -323

Lpo~ disc: 3"06'41

disc

i~_

test

2 ..... .~.:::::,~.:. ~. ~ ~@~.~ ~

Iff(:

I

0.5-

•" L .....

i

•~. i~

~ -9

:,

! :::::..::.:~:::::~:::::::: ..... !

= -o.o3

:~i~:

/ I 0

"

[

9

Figure 5. Discriminant (L) scores probability distributions |\)r the five groups in the test sample (curved lines). For comparison, the distributions from the discriminant sample are shown in shadow. Notice no difference between the means of the discriminant and test samples for either the two negative (L,,,.~..... vs. L,,~ ~k), or the two positive (Lr......... vs. Lp,,~d~*)subgroups. The means of the control (L,.~rt), affective psychosis (L:,O, and mixed schizophrenia (L,,,,,)groups were close to the grand mean of the discriminant sample (= 0).

symptoms. Indirectly supporting the discriminant's sensitivity to frontal dysfunction, the control misclassified as negative schizophrenia later developed overt signs of frontal dementia. The literature contains similar findings for each of the variables (Itil 1977: Etevenon et al 1979: Guenther et al 1988; Giannitrapani and Kayton 1974; Karson et al 1988; Merrim and Floyd 1992) as well as opposite findings (Merrim and Floyd 1992: Kessler and Kling 1991 ). A detailed analysis would be lengthy and probably unnecessary, given the classification differences. As an example, in-

creased anterior theta has been reported in acute hallucinating or in paranoid patients (Itil 1977; Shagass 1982; 1984; Stevens and Livermore 1982; Morstyn et al 1983b), but not in hebephrenics or residuals. Medication effects and treatment responsiveness do not explain theta increase in our negative subgroup. If neuroleptic type had introduced a bias, less slow activity would be expected in this subgroup by having more patients on clozapine (Saletu et al 1990; Small et al 1987: Czobor and Volavka 1993). Theta increase in responsive patients (Czobor and Volavka 1992) is also unlikely, since the positive subgroup was similarly respon-

44

BIOLPSYCHIATRY 1995:38:34-49

M. Gerez and A. Tello

20

10 0

-10 -20

-30 -10

-5

0 L SCORES

5

---1 10

Figure 6. Correlation between discriminant (L)-scores and PANSS scores for all schizophrenic groups pooled (R-"= 0.71, df = 68). Symbols indicate PANSS group, background tones show the neurophysiological classification (dark for negative, clear for positive, light shadow for unclassified). One PANSS negative patient was misclassified as positive, three mixed as positive and one as negative. R squared = 0.73, std err = 4.49, df = 68, X coefficient = 2.39, constant = 1.58.

sive regarding the acute manifestations. Sampling differences seem the most plausible explanation for the discrepancy. Many patients with an acute positive onset become negative in remission (Addington and Addington 1991: Mueser et al 1991). Also, a few DSM-III-R paranoid patients met criteria to be in our negative subgroup. Thus, some of the "acute hallucinating" or paranoid patients in other studies could have been biologically similar to our negative patients. The correspondence with high negative raw scores in unclassified samples is not clear, either. One of the most robust neurophysiological findings in schizophrenia, despite sample heterogeneity, is P300 decrease (Ford et al 1992). This variable was not a good discriminator in our study. A possible explanation could be that P300 abnormalities are related to aspects of psychopathology common to most schizophrenics. Yet, several authors have found P300 abnormalities to correlate with negative symptoms (Pritchard 1986; Kemali et al 1991: Ward et al 1991; Stirk et al 1993). It should be noted, though, that raw negative scores may be influenced by global severity and general psychopathology. The positive subgroup showed left temporal wide-band power increase, P300 asymmetry, and decreased temporal

coherence. Many studies have found abnormal EEG (FlorHenry 1987; Morstyn et al 1983b; Morihisa et al 1983; Guenther et al 1988) and ERP asymmetry (review by Ford et al 1992) in schizophrenia: some have related it to positive symptoms (McCarley et al 1989: Shagass et al 1983; Flor-Henry 1987). Negative findings and reversal with medication have also been reported (Pfefferbaum et al 1989: Michie et al 1990; Kemali et al 1991; Kahn et al 1993). We found wide-band power and P300 asymmetry in the positive subgroup while they were on medication. Our results agree with a left temporal dysfunction underlying the positive symptoms. Yet, left temporal fast beta increase was not a good discriminator. This was surprising, given the consistency of this finding in "florid," treatment-responsive patients (Giannitrapini and Kayton 1974; Flor-Henry 1987; Fenton et al 1980, Itil 1977; Serafatinides et al 1981, Moribisa 1983; Galderisi et al 1991: Kessler and Kling 1991 ). Differential effects of serotoninergic and dopaminergic neuroleptics (Small et ai 1987) could have decreased this variable's sensitivity to subgroup differences. Several studies suggest at least three phenomenological clusters (Liddle 1987; Peralta et al 1992; Lenzenweger et al

QEEG and ERP Discriminators in Schizophrenia

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Table 5. Multiple and Selected Partial Correlations of L Scores and PANSS with Potential Confounders for the Discriminant Sample Variables

L Scores

PANSS

Multiple NLPT(ESRS, DEP) ESRS (NLPT, DEP) DEP (ESRS, NLPT) ESRS DEP (NLPT) ESRS with NLPT

0.02 0.01 0.01 0.01 0.01

0.13 0.04 0.03 0.0 I 0.03

N L P T = neuroleptic type: D E P = Hamilton depression scores.

ESRS

Other

0.18 =

extrapyramidal

symplom

raling:

1991; Arndt et al 1991; Keefe et al 1992: Miller et al 1993: Silver et al 1993). Our sample was too small to test a threegroup discriminant function. The significant linear correlation of PANSS and L-scores, without any apparent clustering, would be more consistent with a continuum along the positive/negative dimension: however, our samples do not represent the schizophrenia spectrum, since only patients in

remission were included, and the mixed subtype was markedly underrepresented. It is possible that a third cluster could be better identified within the mixed subtype. Or alternatively, that some of the general psychopathology items, for which our patients had low scores, would give higher loads for a third cluster. An unbiased and larger sample would be necessary to investigate this issue. It is also possible that neurophysiologicai changes parallel symptomatic clustering only because both reflect transient biochemical states (van Kammen 1991). To investigate the longitudinal stability of neurophysiological differences, we are now retesting patients after a new episode or 1 year without exacerbations. Given the limitations of the study, these results should be seen as preliminary. They suggest the existence of at least two distinct neurophysiological subtypes, which correspond to the positive and negative PANSS subgroups. Noteworthy, variables selected to identify a frontostriatal deficit yielded the highest loads for a negative classification, while variables related to left temporal dysfunction were the best discriminators for the positive subgroup.

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