Psychiatry Research. 26, 203-22 I Elsevier

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Auditory Event-Related Potentials in Children at Risk for Schizophrenia: The Complete Initial Sample

David Friedman, Barbara Cornblatt, Herbert Vaughan, Jr., and L. Erlenmeyer-Kimling

Received April 3, 1987; revised version received October 9, 1987; accepted October 31, 1987.

Abstract. Event-related potentials (ERPs) were recorded from children of schizo- phrenic parents, children of parents with affective disorders, and children of parents without a history of psychiatric illness. ERPs were elicited during a modification of the “oddball” paradigm, in which two infrequents (a change in pitch and a missing stimulus) were embedded in a series of frequent background events. The data were recorded from electrodes located at midline frontal, central, parietal, and occipital scalp sites. Diagnostic assessments of the parents were performed using the Schedule for Affective Disorders and Schizophrenia-Lifetime Version (SADS-L) and Research Diagnostic Criteria (RDC). Behavioral assess- ments of the children were made with a modified version (BGAS) of the Global Assessment Scale. ERP amplitudes for several electrophysiological events were compared among groups for target and nontarget stimuli using analyses of var- iance of both factor score and baseline to peak measures. No systematic differences suggesting waveform abnormalities in the children of schizophrenic parents (high- risk subjects) were found. However, when the results were analyzed using only those children whose parents had a “pure” diagnosis of either schizophrenia or affective disorder, the children of affectively disordered parents (psychiatric con- trol subjects) showed significantly lower NlOO amplitudes (to the frequent event only) than either the normal control or high-risk subjects. No consistent behavioral differences among the three groups emerged. Since only a small percentage of children at risk will eventually develop schizophrenia, ERP amplitude frequency distribution analyses were also performed and compared among groups. However, these did not provide evidence of an outlying subgroup in any of the three groups. There were complex relationships between ERP component amplitudes and behavioral adjustment in adolescence but, in general, these did not distinguish high-risk and psychiatric control subjects from each other. There was no evidence of a relationship between deviant attentional functioning as measured in an earlier round of laboratory testing and ERP late component amplitude.

Key Words. Children at risk for schizophrenia, cognitive event-related brain potentials.

David Friedman, Ph.D., is Associate Research Scientist, Division of Developmental and Behavioral Studies, Department of Medical Genetics, New York State Psychiatric Institute,and Associate Professor, Department of Psychiatry, Columbia University Medical School, New York, NY. Barbara A. Cornblatt. Ph:D., is Senior Research Scientist, Division of Developmental and Behavioral Studies, Department of Medical Genetics, New York State Psychiatric Institute, and Research Associate, Department of Psychia- try, Columbia University Medical School, New York, NY. Herbert Vaughan, Jr., M.D., is Professor of Neurosciences, Albert Einstein College of Medicine, and Director of the Rose F. Kennedy Center for Research in Mental Retardation, Bronx, NY. L. Erlenmeyer-Kimling, Ph.D., is Director of the Division of Developmental and Behavioral Studies, Department of Medical Genetics, New York State Psychiatric Institute, and Professor, Departments of Psychiatry and Human Genetics, Columbia University Medical School, New York, NY. (Reprint requests to Dr. D. Friedman, New York State Psychiatric Institute, A308, 722 W. 168th St., New York, NY 10032, USA.)

01651781 j88jSO3.50 @ 1988 Elsevier Scientific Publishers Ireland Ltd.

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This is the second in a series of articles dealing with event-related potentials (ERPs) recorded as part of a battery of biobehavioral tests in the New York High-Risk Project. These data are from our initial sample (Sample A) seen for their third round of longitudinal testing (Round A3). In a previous publication (Friedman et al., 1986), we described the visual ERPs recorded from these same subjects elicited by stimuli during two versions of the Continuous Performance Test (CPT). We report here the auditory ERP and behavioral indices from the same sample, elicited during our modification of the “oddball” paradigm. Preliminary results with this paradigm were published earlier (Friedman et al., 1982), but the data reported here represent the complete sample, including the psychiatric control group, after the patient parents were rediagnosed using Research Diagnostic Criteria (RDC) (Spitzer et al., 1975) and the Schedule for Affective Disorders and Schizophrenia-Lifetime Version (SADS-L) (Spitzer et al., 1977).

Methods

Subject Selection and Parental Diagnoses. A complete description of the recruitment of subjects for study is provided in Friedman et al. (1986). Only a brief description is given here. The children of mentally ill parents were ascertained through the admission in 1971 or 1972 of either one or both of the parents to one of several state psychiatric facilities in the New York Metropolitan area. Only those parents for whom there was full diagnostic agreement about the presence of schizophrenia (by two board-certified psychiatrists, using DSM-II criteria) were retained for study. If the children of these parents were found to be mentally retarded or to have known psychiatric problems, they were excluded from the study. All subjects were aged 7-12, white and English-speaking, and the family had to be intact at intake.1 The parents of these children were later rediagnosed using the SAD.%L in conjunction with the RDC. In the data to be reported here, the children are grouped according to their parents’ RDC diagnoses.

The normal control (NC) group was obtained with the cooperation of two large school systems within the New York Metropolitan area. Families were excluded from the NC group if either parent was found to have had psychiatric treatment.

Regular Definition of Schizophrenia. For purposes of data analysis, the children of the rediagnosed patient parents were grouped into a “high-risk” (HR) group (one or both parents receiving a diagnosis of “pure” schizophrenia or schizoaffective psychosis, mainly schizo- phrenic), and a psychiatric control (PC) group (one or both parents receiving a diagnosis of “pure” affective disorder or schizoaffective psychosis, mainly affective).

“Narrow” and “Wide” Definitions of Schizophrenia. To eliminate the possibility that the results could have been due to the inclusion of subjects in the HR group whose parents had differing symptomatology, additional groupings employing “narrow”and “wide” definitions of schizophrenia were constructed. This was also done to be consistent with our previous article (Friedman et al., 1986), which also used these additional definitions. Narrowly defined groups consisted of children whose parents received a diagnosis of “pure” schizophrenia (n = 20) or a diagnosis of “pure” affective disorder (n = 19). A widely defined HR group was formed by including not only those children whose parents received a diagnosis of pure schizophrenia or schizoaffective, mainly schizophrenic, but all children from the PC group whose parents received a diagnosis of schizoaffective, mainly affective. This resulted in an n of 40 for the widely defined group.

I, Because the New York High Risk Project was designed to assess the role of genetic factors in the etiology of schizophrenia, it was important to have identified both biological parents.

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Table 1 presents the demographic characteristics of the subjects for whom ERP data were available in Round 3 of testing (1977-79) including parental diagnoses, behavioral global adjustment scores (BGAS), age, sex, IQ, and socioeconomic status @ES). There was one NC subject for whom we were unable to obtain an IQ or SES score. Between-group analyses of variance (ANOVAs) showed that for both SES (F q 15.91; df= 2,127; p < 0.05) and IQ (F q

13.08, df = 2, 127; p < 0.05), the NC group was significantly better than either the PC or HR groups, which did not differ from one another. However, correlational analyses of SES and IQ with the component scores produced a few extremely small-magnitude correlations which, when corrected for chance levels, were no longer significant. Thus, it is doubtful that either of these measures influenced the ERP results reported below.

Assessment of Adjustment in Adolescence. Behavioral assessments were made on the basis of information obtained from the parents of participating children during routine follow- up telephone calls (see Cornblatt and Erlenmeyer-Kimling [ 19851 for a complete description). Three major areas of functioning were assessed: (1) the child’s overall relationship with family members; (2) peer interactions; and (3) school functioning. Ratings were scored on a 5-point scale (the higher the score, the healthier the behavior) and range from gross behavioral disturbance requiring hospitalization (a rating of 1) to above average functioning (a rating of 5).

Table 1. Demographic characteristics of the A3 sample

Mean Group 11 12 13 14 15 16 17 16 19 Total (SD)

NC 1 8 16 14 7 15 8 3 0 72 14.5

Il.71 HR 0 2 6 5 7 5 3 4 1 33 15.1

i 1.9, PC 0 3 3 2 6 3 6 1 2 26 15.3

/ 2.1)

Total 1 13 25 21 20 23 17 8 3 131

Parental diagnosis

High risk Psychiatric control

Pure Schiz SchirlSchizoaff Pure Ati SchizoaWAff (n = 20) tn = 131 b-i = 191 In = 71

Males Sex

Females

NC 40 32 HR 21 12 PC 10 16

Totals 71 60

Group BGAS SE!? Full Scale IQ

NC 3.9 IO.581 58 1261 114 ( 9.8, HR 3.1 (0.751 84 1281 104 111 I PC 3.4 \l.lOl 83 i21I 1081 8 I

Note. A3 sample = inlttal sample seen for third round of testing NC = normal control HR = high risk for schizophrema. PC = psychiatric control. Schiz = schizophrema. Schizoaffec = schlzoaffectlve disorder. Aff = affective disorder. BGAS = BehavIoral Global Adjustment Scale

1. Higher score Indicates better adjustment. 2. Lower score Indicates higher socioeconomic status SESI

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This scale, a modification of the Global Assessment Scale (Endicott et al., 1976) is called the Behavioral Global Adjustment Scale (BGAS).

Attentional Deviance. When these children were seen for the first time in the laboratory (Sample Al), they were given a battery of tests that tapped attentional processing (cf. Erlenmeyer-Kimling et al., 1982; Cornblatt and Erlenmeyer-Kimling, 1984, 1985). These sub- jects were later characterized as being deviant or nondeviant across the various measures that made up the test battery (Cornblatt and Erlenmeyer-Kimling, 1985). Since Cornblatt and Erlenmeyer-Kimling (1985) had reported that there were significantly more attentionally deviant subjects in the HR than in either the PC or NC groups, we used their attentional index in an attempt to determine (via ANOVA, see Results below) if those subjects defined as attention- ally deviant had different ERP patterns from nondeviant subjects. The Cornblatt and Erlenmeyer-Kimling (1985) index was constructed as follows: First, a set of response indices was selected from those generated by the three measures included in the attentional test battery-the Continuous Performance Test (CPT), Attention Span, and the Digit Span subtest of the Wechsler Intelligence Scale for Children (WISC). Then, for each response variable, a cutoff score was selected that identified the most poorly performing 5% of the NC group. Subjects in each group (NC, HR, PC) who performed below this score were considered deviant on that particular variable. Each of the 15 attentional variables included in the deviance index was dichotomized, with subjects defined as deviant receiving a score of I and all others receiving a score of 0. The IS dichotomized variables were then combined into the single composite attentional deviance index by tallying the number of l’s each subject received. Subjects with a score 2 4 were considered to be deviant performers.

Oddball Paradigm. The task was constructed to be consistent with the tasks that had produced P300 reduction in adult schizophrenics(e.g., Roth and Cannon, 1972; Levit et al., 1973). During each block of trials, the children heard three kinds of events: a frequent or standard (STD) tone pip (1,000 Hz, 64 dB SPL), which occurred 66% of the time; a pitch change (PCH) from the standard frequency (700 Hz, 64 dB SPL); and a stimulus omission or missing stimulus (MS). The two oddballs (MS and PCH) each occurred 17% of the time. The stimuli (2.5 ms rise and fall times; 50 ms duration) were presented binaurally over headphones with an interstimulus interval of 800 ms. Subjects were instructed to respond with a finger lift (which activated a reaction time key) as quickly as possible to one of the infrequent events. The relevant stimulus (i.e., a target) was alternated across four blocks of trials, with a total of 300 stimuli per block.

Data Acquisition and Electroencephalographic (EEG) Recording Procedures. EEG was recorded from electrodes located at midline frontal (Fz), central(Cz), parietal (Pz), and occipital (Oz) scalp sites. Vertical electro-oculogram (EOG) was recorded from an electrode located at the supraorbital ridge of the right eye and, in some instances, from an additional electrode located below the right eye. All leads were referred to an electrode located on the right earlobe (A2). Electrode impedances were never above 5 Kohms and in most cases were considerably below that value. The physiological signals were amplified on an eight-channel Beckman (Type RM) Dynograph recorder with I-set time constant and 30 Hz high-frequency cutoff. Data acquisition and stimulus presentation were under the control of a PDPll/ 10 computer, which digitized the EEG and EOG at 4 ms intervals for a 100 ms prestimulus and a 700 ms poststimulus period, and stored the digitized records, along with the subject’s reaction time responses, on nine-track digital tape.

Averaged ERPs were computed on line in approximately two-thirds of the subjects using a program for rejecting epochs that contained eye movement artifacts. In the remaining subjects, the averages were computed off line, with artifactual epochs determined by visual inspection and manually rejected. The two techniques for artifact rejection were compared in several subjects and found to give essentially the same results.

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Data Analyses. Baseline to peak measures. All peak measures were computed as averaged voltages with

respect to the 100 ms prestimulus epoch. The measurement of baseline to peak amplitude was automated via computer program, using predefined latency windows (see Results below).

Principal components analyses (PCAs). Our rationale for the use of PCA of the averaged waveforms is explained in detail in Friedman et al. (198 1). PCA was used in an attempt to obtain measures of ERP activity in which component overlap had presumably been reduced (see Glaser and Ruchkin, 1976; Donchin and Heffley, 1978). An additional reason for the use of PCA was to obtain objective confirmation, via the basis waves (i.e., factor loading functions), of components we had visually identified in the individual and grand mean data.

PCA has been shown to be capable of misallocating variance (Wood and McCarthy, 1984), so that caution must be exercised when interpreting results based solely on PCA. Our strategy was to use both baseline to peak and PCA-derived indices in describing the results of group effects present in these data.

The cross-products matrix was factored, since no transformations are performed on the data when using this matrix. The BMDP statistical package was used (BMDP4M; Dixon, 1983). The original waveforms were reduced from 198 to 66 points (to reduce the number of “variables” entered into the PCA) by averaging every three adjacent time points, so that each “new” voltage represented 12 ms of EEG activity. Although this technique would tend to preclude the extraction by the PCA of short time-constant peaks (such as P30 and PSO), neither P30 nor PSO were prominent aspects of the raw waveforms (see Fig. 1).

PCA with Varimax rotation was first performed on each group’s averaged ERP waveforms. If the resultant factors were highly similar, 2 the PCA was then performed across groups, subjects, conditions, and electrodes. For the single-group analyses, there were three PCAs (one for each stimulus) performed across subjects. For the pitch change and missing stimulus, the number of cases entered was 2 (relevant/irrelevant) x 4 (electrodes: Fz, Cz, Pz, Oz) x number of subjects, yielding 576 waveforms for the NC group with 72 subjects, 264 waveforms for the HR group with 33 subjects, and 208 waveforms for the PC group with 26 subjects. For the PCAs of the STD, there were 4 electrodes (Fz, Cz, Pz, Oz) x number of subjects, yielding 288, 132, and 104 waveforms for the NC, HR, and PC groups, respectively.

For the PCA performed with the data pooled across groups, there were 1,048 waveforms for the pitch change and missing stimulus (131 subjects x 2 conditions x 4 electrodes), and 524 waveforms for the frequent stimulus (131 subjects x 4 electrodes).

Analyses of variance. ANOVAs of baseline to peak, factor score, and behavioral measures were performed using the BMDP4V program. Because of possible nonhomogeneity of variance-covariance matrices associated with repeated measures, the degrees of freedom were adjusted using epsilon (Geisser and Greenhouse, 1958; Greenhouse and Geisser, 1959), accord- ing to the method outlined by Jennings and Wood (1976). Since risk group, age, and sex were not repeated measures, no adjustment of the numerator degrees of freedom associated with F tests of these variables was made. Only findings reaching the 0.05 level or better after adjusting degrees of freedom were considered significant.

2. Several subjective criteria were used to determine similarity of the varimax-rotated factors: (1) the latency to peak and wave shape of the factors were visually assessed for similarity; (2) in addition, the scalp distribution of factors identified as similar in the three groups was required to be identical; (3) moreover, the amplitudes of the extracted factors (i.e., factor scores) had to show similar relationships (via ANOVA) to the experimental variable of Relevance.

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Results

ERP Waveforms. Fig. 1 presents the grand mean waveforms averaged across sub- jects within each group. The target or relevant (REL in Fig. 1) pitch change ERPs for each group are characterized by N 100 and P200 potentials, a negative potential at 250 ms (Fz-Cz maximum), which is followed by a parietal maximum positive component peaking at about 350 ms. A component reaching peak negativity at about 450 ms follows P350 and is overlapped by slow wave activity (negative frontally and positive parietally), which lasts until the end of the recording epoch. The nontarget (irrelevant-IRR in Fig. 1) pitch change ERPs comprise N 100 and P200 components, and small-amplitude N250 deflections. The P350 component is markedly reduced in these ERPs compared to the relevant ERPs, and is followed by the N450 deflection and smaller (than in the relevant PCH ERPs) frontally negative and parietally positive slow waves.

The ERPs elicited by the standard (i.e., frequent-STD in Fig. 1) stimulus are characterized by small-amplitude NlOO and P200 potentials, followed by a negative component at about 300 ms. This component is followed by slow wave activity, which contrary to the slow wave elicited by either the missing stimulus or pitch change, is negative at all electrode sites. Unlike the PCH ERPs, a prominent P350 component is not present in the standard waveforms.

For the missing stimulus potentials, all three groups show a small negativity (N200-Fz-Cz maximum) preceding the positive component of the missing stimulus ERP (P400-Pz maximum), which is followed by slow wave activity (negative fron- tally and positive at the parietal electrode). The relevant MS elicited larger P4OO’s and slow waves than the irrelevant MS.

Principal Components Analyses (PCAs). Separate PCAs of each group’s ERPs produced highly similar factor structures, thus justifying the performance of the PCA

across groups. Basis waves. Fig. 2 (A-Pitch change; B-Missing stimulus; and C-Standard)

presents the basis waves3 resulting from PCAs performed across groups, conditions, and electrodes, separately for each stimulus. For the pitch change ERPs, basis waves corresponding to NlOO (9.1% energy), P200 (13.2%), P350 (35.4%), N450 (10.6%) and slow wave (29.1%) were extracted. For the missing stimulus, basis waves correspond- ing to N200 (lo%), P400 (22.4%), and slow wave (63.8%) were extracted. For the frequent, standard stimulus, basis waves corresponding to NlOO (7.1%), P200 (13.1%), N300 (54.4%), and slow wave (14.8%) were obtained. Depicted below each basis wave is the scalp distribution (across subjects and conditions) for each of the three groups. In conjunction with the ERP waveforms presented in Fig. 1, the PCA waveforms and their topographic distributions depicted in Fig. 2, P350 of the pitch change, and P400 of the missing stimulus are considered to be the classical “P300” component.

3. For the pitch change and missing stimulus ERPs, one factor (2.5% and 3.8% energy, respectively) was uninterpretable, while for the ERPs elicited by the frequent stimulus, two factors (6.9y0 and 3.6%) were uninterpretable, and are not discussed further.

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Fig. 2a. Varimax rotated basis waves (factor loading functions) resulting from PCAs performed (separately for each stimulus) across groups, electrodes, and conditions: Pitch change ERPs

PITCH CHANGE

A =

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High Rirk___________.

PCA = prlnclpal components analysis. ERP = event-related potential. The factor score scalp distribution for each group and component IS depicted below each basis wave. Arrows mark stimulus onset with time lines every 200 ms.

Baseline to peak measures. These indices4 were computed as averaged voltages roughly centered about the peak of the basis wave with which the component was associated.

Factor score analyses. In the data reported below, the PCA scores are reported in detail. However, where discrepancies exist in the two data sets, the baseline to peak results are also described. For N300 of the ERPs elicited by the frequent event, and N450 of the pitch change ERPs, baseline to peak measures were not computed.

Only the results in which Group effects occurred are reported here. Due to small n’s that resulted when attempting to assess Age x Group effects, ages were combined for

4. For the ERPs elicited by the pitch change and standard stimuli, the criteria were (in ms poststimulus): N 100 (SO-150 ms), P200 (135-220 ms), P300 (260-400 ms), slow wave (500-600 ms), NZOO in pitch change (200-325 ms), and N300 in standard (200-325 ms); for the missing stimulus ERPs, the criteria were: N200 (175.300 ms), P300 (375-575 ms), and slow wave (600-700 ms).

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Fig. 26. Varimax rotated basis waves (factor loading functions) resulting from PCAs performed (separately for each stimulus) across groups, electrodes, and conditions: Missing stimulus ERPs

MISSING STIMULUS

N200 P400 SW

Normal Controls m

Psych ConWols o-------9

High Risk ______ ______.

PCA = principal components analysis. ERP = event-related potential. The factor score scalp distribution for each group and component is depicted below each basis wave. Arrows mark stimulus onset with time linesevery 200 ms.

Fig. 2c. Varimax rotated basis waves (factor loading functions) resulting from PCAs performed (separately for each stimulus) across groups, electrodes, and conditions: Standard stimulus ERPS

STANDARD

t t 21 -l

N300 SW

NlOO P200

Normal ._._--. Controls

Psych Controls M

High Risk ____ ___. _

PGA = principal components analysis. ERP = event-related potential. The factor score scalp distribution for each group and component is depicted below each basis wave. Arrows mark stimulus onset with time lines every 200 ms.

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these analyses into 13 and younger, 13 to 16, and 16 and older. However, Age x Group and Sex x Group effects were not present in either the amplitude (factor score or baseline to peak) or latency data. Main effects of Electrode Location, Relevance, Age, and Sex were essentially identical to those reported by Friedman et al. (1984) for the NC sample. Therefore, the reader is referred to Friedman et al. (1984) for a complete description of these findings.

Missing Stimulus (MS) and Pitch Change (PCH) ERPs. The results ofthefactor score ANOVAs, using “regular,” “ wide,” and “narrow” criteria to define the groups, are presented in Table 2. Only the F ratios that assessed Group main and interaction effects are tabled.

Regular definition of schizophrenia. For the pitch change ERPs, there was a Relevance x Electrode x Group interaction for N450 (F= 3.52; df= 4,285;~ < 0.05) and NlOO (F = 2.97; df= 4,279; p < 0.05). Both of these interactions were very modest. The N450 interaction was due mainly to the PC group’s producing somewhat more positive N450 amplitudes at Pz and Oz than the NC group (F = 6.12; df=2,212; p <

Table 2. Significant f ratios (after df reduction) and associated components for Group effects in Regular, Wide, and Narrow ANOVAs in the factor score data set

Group effect: Group (G) Rel (R) X Gl Elec (E) X G RxExGl

Analysis type: Pitch change

Regular NS NS NS NlOO (2.97) N450 (3.52)

Narrow2 NS NS NS NS

Wide3 NS NS NS NS

Missing stimulus

Regular NS NS SW (2.56) NS

Narrow NS NS NS NS

Wide NS NS NS NS

Standard stimulus

Regular NS NS

Narrow NlOO (3.78) NS

Wide NS NS

Note. NS = nonsignificant for any of the components analyzed for the stimuli listed in the table. To tally the total number of F tests involving Group that were performed, for each type of analysis it is necessary to multiply the number of components assessed by the number of F tests listed in the table. For example, since there were 5 components for the pitch change, and there were4 Ftests involving Group per component, the total number of F tests that assessed Group was 20. Rel = Relevance. Elec = Electrode location. ANOVA = analysis of variance.

1. Was not analyzed in Standard stimulus ANOVAs. 2. Narrow analyses contrasted 3 groups: (1 I children whose parents werediagnosed as pureschlzophrenia / n = 201; (21 children whose parents were diagnosed pure affective in = 191; and 131 the normal control group. 3. Wide analyses contrasted a group composed of children whose parents were diagnosed as pure schizo- phrenia; as schlzoaffective, mainly schizophrenic; and as schizoaffective, mainly affective (total n =40), with the normal control group.

213

0.05), but only for the target ERPs. This interaction did not occur when the HR and PC and HR and NC groups were contrasted separately. The NlOO interaction was extremely difficult to interpret and, since it was not replicated in the baseline to peak data, is not dealt with further.

For the slow wave elicited by the missing stimulus, there was a modest interaction of Group and Electrode Location for the factor score data (F= 2.56; df = 4,268;~ < O.OS), which was not seen in the baseline to peak data. As can be seen in Fig. 26, this interaction was due to the fact that the PC group showed smaller frontal negative and parietal positive slow wave amplitudes than the NC group (F= 4.08; df = 2,204; p < 0.05). This interaction was not seen when the HR and PC and HR and NC groups were

separately compared. Wide and narrow definitions. There were no significant main or interaction

effects for the missing stimulus or pitch change component scores when the subjects were classified using the wide and narrow definitions detailed in Methods above.

Standard ERPs. Regular definition of schizophrenia. For the ERPs elicited by the frequent

event, there was a modestly significant interaction of Electrode Location and Group for Slow Wave in the baseline to peak data (F= 2.56; df = 3,224; p < O.OS), which was not significant in the factor score data set. This interaction was due to the PC subjects showing less negative values at the two posterior electrodes than the NC subjects (F = 5.60; df = 2,177; p < 0.05). The interaction was not seen when the HR and PC and HR and NC groups were compared separately.

Wide and narrow definitions. For the frequent event, ANOVAs using groups based on the wide definition yielded no significant effects. For the narrow analyses, there was a between-group effect for NlOO (F= 3.78; df = 2,109;p<O.O5) when the pure HR, pure PC, and NC groups were contrasted. Separate ANOVAs showed that this effect was due to the pure PC subjects producing significantly less NlOO amplitude than either the pure HR (F = 5.63; df = 1,38; p < 0.05) or NC (F = 7.37; df = 1,90; p < 0.05) groups, which did not differ from oneanother. Interestingly, this NlOO between- group effect did not occur for the pitch change ERPs.

With the exception of the NlOO finding in the narrow definition analyses, the effects reported above were modestly significant and were not consistently shown in both PCA and baseline to peak data sets. In addition, the most robust ERP effect was found for the pure PC group (lower NlOO amplitude) and not for the pure HR group. Thus, these data do not provide strong evidence of ERP abnormalities in the HR group.

Behavioral Data. Reaction time (RT) and its mean within-subject standard devia- tion, the number of correct target detections, and the number of irrelevant responses (a finger lift to the nontarget infrequent event) are presented in Table 3. These numbers are based on all trials, including those that were rejected due to artifact contamination. Group x Stimulus (MS/PCH) ANOVAs were performed on these data. Due to problems with digital tape artifact when the data were analyzed, the numbers of subjects on which these analyses were based are somewhat reduced relative to those for the ERP analyses: NC, 67; HR, 29; PC, 25. For the wide and narrow definition groups, these numbers were: HR (wide), n = 35; pure PC, n = 19; pure HR, n = 18.

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As can be seen in Table 3, RT was faster (F = 338; df = 1,118; p < 0.05) and its mean within-subject standard deviation (WSD) was smaller (F = 209; df = 1,118;~ < 0.05) to the PCH than to the MS. There were no Group effects on these two behavioral measures.

When the subjects were classified according to the narrow or wide definitions of risk described above, there were also no significant Group main or interaction effects for either RT or WSD.

For the number of correct target detections, there was a large effect of Stimulus (PCH > MS: F= 63; df= 1 ,I 18;p<O.O5), and an interaction of Group and Stimulus (F = 3.5; df = 2,118). This was due to the PC subjects producing a greater number of correct PCH detections than the NC group, with no difference in the number of correctly detected MSs between these groups (F = 6.94; df = 1,90; p < 0.05). This did not occur when the PC and HR or the HR and NC groups were separately compared.

There were no significant Group main or interaction effects on the number of correct responses when the subjects were classified according to the narrow definitions of risk. For the wide definition analyses, however, there was a Stimulus x Group interaction (F = 4.12; df = 1,100; p < 0.05) which indicated that the wide schizophrenic group made fewer (mean = 82.5) correct detections of the missing stimulus than the normal controls (mean = 87.4) but did not differ from the NC group in the number of correctly detected pitch change stimuli.

For the number of responses to the irrelevant infrequent stimuli, there were more irrelevant responses when the MS was the target than when the PCH was the target (F = 53; df = 1,118; p < 0.05), but no effect of Group.

There were no significant effects of Group on the number of irrelevant responses for the wide definition analyses. For the narrow definition analyses, the ANOVAs showed that the pure PC group produced more irrelevant responses than the pure HR (F = 5.89; df = 1,35; p < 0.05) group, with the difference between the pure PC and NC

Table 3. Behavioral data-Reaction time

Group

Pitch change Missing stimulus

RT WSD RT WSD

NC 347 160) 98 129, 443 177)

HR 359 (62) 98 (26) 466 (77)

PC 347 154) 101 I301 429 (52,

NC HR

PC

NC HR

PC

Number correct target detections 92 (101 87 110,

92 ill1 83 i13,

971 5) 85 110)

Number of irrelevant responses 5( 51 10 I 8)

41 51 7( 51

7r 7) 13 1141

149 134)

145 (271

154 (28)

Note. RT = reachon time. WSD = mean wthm-subject standard dewation of RT. NC = normal control. HR = high risk. PC = psychiatric control

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groups approaching significance (F= 3.48; df = 1,84;p < 0.06). There was no difference between the pure HR and NC groups.

Behavioral Adjustment in Adolescence. To determine whether behavioral adjust- ment during adolescence was related to ERP component amplitude, subjects within each of the three risk groups were categorized on the basis of their BGAS ratings (Cornblatt and Erlenmeyer-Kimling, 1985). Subjects were divided into three group- ings: scores of l-2 (severely impaired functioning), 3 (moderately impaired), and 4-5 (average and above average functioning). ANOVAs using these groupings were then performed on the factor scores, separately for each stimulus. We were unable to obtain BGAS ratings on three of these subjects-two from the PC group and one from the NC group. Due to the small numbers of subjects falling into these subgroupings, conservative degrees of freedom were used to test all main and interaction effects.

For the pitch change, P350 amplitude was larger in the ERPs of subjects whose BGAS scores indicated better adjustment (Fz4.55; df= 1,121;p<O.O5). However, the interaction of BGAS rating and Group (F = 4.49; df = 1,121; p < 0.05) was also significant. Tests for simple effects showed that this relationship held only for PC subjects (F = 6.72; df = 1,12 1; p < 0.05). Additional tests for simple effects indicated that the HR group showed larger P350 amplitude than the PC group at a BGAS rating indicative of poor adjustment (F = 3.95; df = 1,120; p < 0.05) and that there was a marginally significant effect of Group at the highest BGAS rating (F= 3.57; df = 1,120; p < 0.1). Newman Keuls procedures showed that only the PC and NC groups differed, with the PC group producing larger P350 amplitude.

P400 of the missing stimulus also showed a BGAS rating x Group interaction (F = 4.96; df = 1,121; p < 0.05). Tests for simple effects indicated that there was a marginally significant relationship between BGAS rating and P400 amplitude, but only for the HR subjects (F= 3.24; df = 1,121; p < 0.1). For these subjects, unlike the finding for the PC subjects detailed above, P400 amplitude decreased with better adolescent adjustment. Additional tests for simple effects indicated that there was a marginally significant Group effect only at the BGAS rating indicative of better adolescent adjustment (F = 3.13; df = 1,120; p < 0. I). Newman Keuls procedures indicated that only the PC and HR groups differed, with the PC group showing greater P400 amplitude.

For the frequent stimulus, N300 showed a main effect of BGAS rating(F= 5.37; df q 1,121; p <0.05), becoming progressively more negative as BGAS rating indicated poorer adolescent adjustment. There were no interactions with Group for this component.

In general, the above analyses did not yield consistent findings. While PC subjects showed greater P300 amplitude to the PCH as adolescent adjustment improved, HR subjects showed smaller P300 amplitude to the MS as adolescent adjustment improved. Moreover, poor adolescent adjustment ratings yielded larger PCH P300 amplitudes for HR than for PC subjects, while better adolescent adjustment ratings produced smaller MS P300 amplitudes for HR than for PC subjects. Additionally, there was no relationship between BGAS rating and ERP amplitude in the NC group.

Attentional Deviance. We wanted to determine whether the subjects defined as attentionally deviant on their Round 1 laboratory data had different patterns of ERP

216

component amplitudes compared to those subjects characterized as being nondeviant on the attentional index. Of the 26 subjects defined as deviant at Round 1 according to the criteria described in Methods, 22 had Round 3 ERP data available. Eleven of the subjects were in the HR group, 7 were in the NC group, and 4 were in the PC group. We compared ERP amplitudes between the deviant and nondeviant subjects using Deviance (Deviant/Nondeviant) x Relevance x Electrode Location ANOVAs for the pitch change and missing stimulus ERPs and using Deviance x Electrode Location ANOVAs for the ERPs elicited by the frequent stimulus. Due to the small numbers of subjects falling into these subgroupings, conservative degrees of freedom were used to test all main and interaction effects. None of the analyses yielded significant main or interaction effects.

Frequency Distribution Analyses. Since only a relatively small percentage of HR children are expected to develop schizophrenia (Erlenmeyer-Kimling, 1968; Zerbin- Rudin, 1968) we wanted to determine whether an outlying subgroup was present in the data sets of the HR group. Frequency distributions of ERP amplitudes were computed for each group (NC, PC, HR) for each component, stimulus, and condition. These were visually inspected (all three groups for a given condition and electrode on the same axes) and did not provide evidence for an outlying subgroup in any of the three groups. Fig. 3 presents these data for the factor score measures of the ERPs elicited by the pitch change. The degree of overlap among the three groups for each of the components depicted is striking. The impressions from this “eyeball” analysis were statistically supported by computing the measures of skewness and kurtosis for each ERP component separately for each group. The computed value was divided by its standard error to obtain an approximate measure of whether either index of normality was significantly different from zero. No consistent pattern for either the PC or HR groups could be discerned. For example, both the HR and PC groups showed significantly negatively skewed distributions for frontal negative slow wave elicited by the missing stimulus. In addition, the sign of the skew was, in many cases, identical to that shown by the NC group. Considering the large number of variables for which these indices were computed (100 separate tests), the data do not provide strong evidence for a systematic outlying subgroup within the HR sample.

Discussion

The data reported here for the auditory oddball paradigm from our complete initial sample (A3) do not provide evidence of any consistent pattern of between-group ERP differences. The data on behavioral adjustment in adolescence do not suggest that those individuals within the HR group with behavioral adjustment (BGAS) scores indicative of poorest functioning are also those with the most aberrant ERP wave- forms. In fact, only for the PC group did the relationship between BGAS and P300 amplitude hold. The analyses of attentional deviance (measured at Round Al) do not change these conclusions.

The ERPs recorded from all three groups (NC/HR/PC) displayed essentially identical morphologies (see Fig. l), so that visual inspection and quantitative analyses yielded few areas of difference among the groups along the ERP waveform. Topo- graphic distributions for each of the ERP components elicited by each stimulus were

217

Fig. 3. Frequency distributions for the factor score component measures of the ERPs elicited by the pitch change

FACTOR SCORE

NORMAL CONTROLS

HIGH RISK

PSYCH CONTROLS

ic I I!.

AMPLITUDE IN UNITS NlOO:

p:oo’ p350:

Cz I Pz

L i b-

SW:

s

b.- b- li

SW:

pt The distributions are plotted at the electrode where the Component in question displayed its maximum amplitude. ERP = event-related potential.

also highly similar for the three groups. There were a few modest but significant interactions, which were not consistently seen in both PCA and baseline to peak data sets. These were not always significant in the factor score data, as might have been expected had overlap among components been responsible for the differences between the two data sets. Coupled with this is the fact that for all three stimuli these were only a few of many Group effects that were tested in each of the ANOVAs. For example, for the regular analyses, there were 20 F tests for the pitch change involving Group or its interaction with Relevance and/or Electrode Location-5 components x 4 Ftests; for the missing stimulus, 12 (3 components x 4 F tests) and for the frequent stimulus, 8 (4 components x 2 F tests-Relevance was not a variable in this analysis), making it difficult to interpret these findings. Further, neither the behavioral adjustment (BGAS) nor attentional deviance analyses yielded evidence of a subgroup that was characterized by aberrant amplitudes of the kind indicated in the modestly significant ERP amplitude analyses.

The ERP amplitude distributional analyses suggest that the ERP indices obtained from these auditory ERP data cannot, by themselves, differentiate subjects at risk

218

from children of parents without psychiatric disturbance or from children of parents with affective disorders. When taken component by component in the frequency distribution analyses, the data failed to yield evidence of an outlying subgroup that could be considered to comprise the most vulnerable subjects within the HR sample.

As with the CPT data published earlier (Friedman et al., 1986), age and sex trends for each of the two experimental groups (HR/ PC) were similar to those found for the NC group. This suggests that hypotheses of maturational lag (cf. Herman et al., 1977) as explanatory of the deficits seen in HR subjects are not tenable for this sample of subjects. In addition, since there were no consistent interactions of Relevance with Group, and only one significant behavioral difference (when the wide definition analyses were employed), the data suggest that the HR and PC subjects process the information in these auditory stimuli in a similar fashion to the children of non- psychiatrically disturbed parents.

Pritchard (1986) has recently argued that tasks producing behavioral differences between HR and normal controls should be used to elicit ERPs in these populations. He has suggested that the reason we did not obtain significant between-group ERP findings in the current data (presented in abstract form in Friedman et al., 1985) was due to our use of a fairly easy oddball paradigm. However, in the current data the detection of the missing stimulus was more difficult than detecting the change in pitch in all three groups, and apparently led to the wide definition HR group’s showing less accurate detection of the missing stimulus than either the PC or NC subjects. How- ever, this behavioral difference was not mirrored in a between-group ERP finding. In a similar vein, in Friedman et al. (1986), with more cognitively challenging CPTs, we also found significant between-group behavioral differences (HR subjects performed somewhat more poorly on average than either normal or psychiatric control subjects). However, we were unable to demonstrate a consistent pattern of between-group ERP differences, or a deviant subgroup within the HR sample characterized by abnormal ERP component amplitudes. Thus, these factors argue against Pritchard’s (1986) notion that the less difficult nature of the current tasks accounts for the lack of between-group ERP findings.

In a recent review chapter, Mirsky and Duncan (1986) suggested that another reason we did not obtain between-group ERP findings in Friedman et al. (1985) was the fact that we had restricted our sample to intact families only-the implication being that we had recruited parents with less severe schizophrenic disorders. Mednick (1978) has mustered the same argument in an attempt to explain our (Erlenmeyer- Kipling et al. [ 1985]-presented in preliminary form in Erlenmeyer-Kimling [ 19751) failure to replicate Mednick and Schulsinger’s (1968) finding of faster time to half- recovery of the galvanic skin response (GSR) in children of schizophrenic mothers compared to children of nonpsychiatrically impaired mothers. However, in our sample, most of the parents were rated as showing moderate to severe functional impairment, and their severity scores were unrelated to rate of recovery of the GSR in their children (Erlenmeyer-Kimling et al., 1985). Thus, severity of the parents’ illness seems an unlikely contributor to our lack of between-group ERP findings in the

current study. One rather interesting and unexpected finding was for N 100 amplitude in pure PC

subjects to be smaller than in either pure HR or NC samples. A consistent finding in

219

the adult ERP literature is for NlOO amplitude to be smaller in schizophrenics than in NC samples (e.g., Baribeau-Braun et al., 1983; Roth et al., 1980, 1981). However, when depressed patients are added as a control group, NlOO amplitude reduction is not found to be specific to schizophrenia (Roth et al., 1981). In Roth et al. (1980), the NlOO reduction was elicited by stimuli in both no-task and oddball (reaction time required to the infrequent stimulus) conditions, but was smaller within the oddball paradigm only when elicited by the frequent stimuli.

The N 100 reduction seen in the current data for the pure PC group is reminiscent of the NlOO reduction seen for adult schizophrenics (Roth et al., 1980), in that it occurs only for the frequent (i.e., standard) stimuli. It may be the case that reduced NlOO is a potential indicator of risk for depressive illness but, as with the caveats raised here and in our earlier article (Friedman et al., 1986), the large number of statistical tests and the small numbers of subjects in our risk groups argue for caution in strongly interpreting such isolated between-group findings.

Another modest and potentially interesting finding was the relationship between adolescent adjustment, as measured by BGAS ratings, and P300 amplitude. For the PC group, this relationship is similar to that which has been found for a number of patient groups: the larger the P300 amplitude, the better the clinical status of the patient (Roth et al., 1980; Josiassen et al., 1981; Duncan et al., 1987)-in ourcase, the better the rated adolescent adjustment. As an example of the work with adult groups, Josiassen et al. (198 1) studied ERP components in a heterogeneous sample of psychi- atric patients and normal controls in a modified version of the oddball paradigm using somatosensory stimuli. Their most important finding was not that P300 amplitude was reduced in the patients relative to the controls (which it was), but that P300 amplitude was correlated with a general psychopathology factor-larger P300 ampli- tudes indicated a lower level of genera1 psychopathology. For the HR subjects in the current study, however, the relationship between adolescent adjustment and P300 amplitude was opposite to that found for the PC group-larger P300 amplitudes went along with poor adolescent adjustment. This fact discourages a strong interpretation of these BGAS-P300 findings.

One of the goals of HR research in the psychophysiological domain is to determine which findings represent “true” markers. Because adult schizophrenics have been studied mainly while medicated and after long periods of hospitalization, any resulting findings are subject to question, owing to the confounding factors inherent in testing severely impaired psychiatric patients. The study of children at risk eliminates many of these biases, although other problems may exist (see Friedman, in press, for a review with respect to ERPs). One such problem is that the morbidity estimates may influence the magnitude of the differences one finds. For example, only a small percentage of children at risk is eventually expected to develop the psychosis. Thus, as attested to by the current data, the differences between children of schizophrenics and children of nonpsychiatrically impaired parents are likely to be quite small. With sample sizes of 20 or so, there may not be sufficient power to detect the small number of subjects (i.e., the IO-15%-in this case, 3-4) who are eventually expected to develop schizophrenia.

As with our isolated (but specific to HR subjects) finding for frontal negative slow wave (Friedman et al., 1986), we will follow all of our subjects with respect to the reduced NlOO (specific to children of parents with affective disorders). It is only upon

220

followup that the validity of any putative markers can be assessed. Although the behavioral adjustment ratings (BGAS) were not good interim predictors of ERP abnormality, ultimate validation must await more definitive outcome measures (e.g., the diagnosis of affective disorder, schizophrenia, or schizotypal personality disorder) obtained after these subjects have passed through the major risk period for psychosis. At that time, we should be able to determine, with greater certainty, whether these cognitive ERP indices are of predictive value.

Acknowledgments. The authors thank Mr. Charles Brown, Jr., for programming and aid with preliminary data reduction, and Mr. John Boltri for aid with data reduction. Ms. Susan Ball aided in the construction of figures. The research reported here was supported in part by grants HD14959 to Dr. Friedman, MH-19560 to Dr. Erlenmeyer-Kimling, and by the Depart- ment of Mental Hygiene of New York State. Dr. Friedman is supported in part by a Research Scientist Development Award (MH-005 10) from the National Institute of Mental Health. The Computer Center at New York State Psychiatric Institute is supported in part by a grant (MH-30906) from the National Institute of Mental Health.

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