Neuroanatomical bases of electrodermal hypo-responding: A cluster analytic study

INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY

ELSEVIER

International

Neuroanatomical

Journal of Psychophysiology

22

(I 996) 14 1- 153

bases of electrodermal hypo-responding: A cluster analytic study

Todd Lencz a7*, Adrian Raine b, Charlotte Sheard ’ ’ Hillside Hospital Division qf the Long Island Jewish Medical Center, Department ofResearch. Glen Oaks, NY 11004, USA b Department of Psychology, Unicersity of Southern California, California. USA ’ Department of Psychiatry, Unil~ersity of Nottingham, Nottingham, UK Received

16 August

1994; revised 28 December

1995; accepted 26 January

1996

Abstract Schizophrenics and other psychiatric patients have been found to have a high incidence of electrodermal hypo-responding. Different neural mechanisms may underlie hypo-responding in these groups. The present study utilized cluster analysis of magnetic resonance imaging (MRI) and electrodermal orienting data to examine the neuroanatomical correlates of electrodermal hypo-responding in 15 schizophrenics, 15 psychiatric controls (predominately affective disorders), and 1.5 normal controls. The number of electrodermal responses was recorded during a standard orienting paradigm. MRI scans were obtained, yielding area measures for the pre-frontal cortex and lateral ventricle-brain ratios (VBRS) The number of electrodermal orienting responses and the MRI measures were transformed into z-scores and entered into an agglomerative hierarchical cluster analysis, which yielded three clusters. A 3 X 3 Chi-square analysis revealed that the three clusters significantly differed according to diagnostic group. Analyses of variance (ANOVAS) revealed that the first two clusters had significantly fewer electrodermal orienting responses than the third cluster (predominately normals). Further, the first cluster (predominately schizophrenics) had significantly smaller frontal lobes than the other two clusters. Additionally, the three normals in the first cluster had relatively high levels of schizotypy. The second cluster (predominately affective disorders) had significantly larger VBRs than the other two clusters. Schizophrenics in the three clusters differed with respect to gender composition and positive symptoms. Thus, diminished pre-frontal area may underlie electrodermal hypo-responding in a subgroup of schizophrenics and schizotypals, while enlarged ventricles may underlie the same phenomenon in the affective disorders and another subgroup of schizophrenics. Keywords: Ekctrodermal Cluster analysis

activity;

Hypo-responding;

Magnetic

1. Introduction Two relatively well-replicated schizophrenia literature have been

* Corresponding

results in the the findings of

author. Fax: 718.343- 1659.

0167.8760/96/$15.00 Published PI/ SO 167.8760(96)00024-4

resonance

imaging;

Frontal

lobe; Ventricle-brain

ratio;

Schizophrenia;

decreased electrodermal responding in psychophysiological studies (e.g. Iacono et al., 1993; Bernstein, 1987; Dawson and Nuechterlein, 1984; Ohman, 198 1; Gruzelier and Venables, 1972) and the reports of structural brain abnormalities in brain imaging studies (for summaries, see Cannon and Marco, 1994; Raz and Raz, 1990). Despite the number of studies

by Elsevier Science B.V. All rights reserved

142

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Journal of‘Ps?choph?sioloR~

published in these areas, two key uncertainties remain concerning the etiological implications of these findings. First, the diagnostic specificity of these findings is unclear, as studies of patients with other forms of psychopathology have reported both skin conductance (SC) abnormalities (Iacono et al., 1993; Bernstein et al., 1988; Zahn et al., 1987) and structural brain deficits (Andreasen et al., 1990; Schlegel et al., 1989) in a variety of patient samples, particularly patients with affective disorders. Second, the relationship between these two abnormalities has not been clearly established. To date, there have been 10 studies examining the relationship between structural brain abnormalities and SC responding (Tranel and Damasio, 1994; Kim et al., 1993; Katsanis and Iacono, 1992; Katsanis et al., 1991; Raine et al., 1991; Schnur et al., 1989; Cannon et al., 1988; Bartfai et al., 1987; Alm et al., 1984; Zahn et al., 1982). Eight of these studies have utilized computed tomography (CT) to obtain the brain images; key features and results of these studTable 1 Kev findines

of comuuterised

tomoeraohv

22 (1996) 141-153

ies are shown in Table 1. Table 1 shows that most of the studies have not found significant relationships between brain imaging measures and SC activity; studies with significant findings are conflicting, with brain deficits alternately related to hypo-responding or hyper-responding. (For a more detailed comparison of these studies, including methodological considerations, see Raine and Lencz, 1993.) Despite the somewhat conflicting findings of Table 1, those studies with positive findings have indicated that ventricular enlargement may be significantly related to abnormal electrodermal activity in patient groups. The generally negative findings in many studies may be due to inherent limitations in CT methodology (e.g. Pfefferbaum et al., 1990; Andreasen, 1989). The major limitation of CT is that signal-to-noise ratio (SNR) is poor relative to magnetic resonance imaging (MRI), thereby limiting the ability to clearly and reliably differentiate structures. Because of this, measures derived from CT are relatively global and non-specific. As can be seen in

(CT) studies of skin conductance

activitv

Subjects

N

Imaging

Key structures

Key findings

SZ atrophy SZ normal SZR SZ NR SZ NR SZ HAB SZ NH SZ high risk

8 20 I2 22 6 7 5 34

CT

Sulci Fissures VBR

SZ atrophy - smaller SCORs, Slower RT and T2 N.S.D.

Schnur et al. (1989)

SZ R SZ NR

9 15

CT

Katsanis et al. (1991)

36 33 19 65

CT

Trend: wide 3V in SZ NH N.S.D. N.S.D. Wide 3V - reduced SCOR amp. N.S.D. Wide 3V in SZ responders N.S.D. N.S.D. N.S.D. N.S.D. SCL, NSF, #SCOR.

Katsanis and Iacono (1992)

SZ Affective SZ FORM SZ

3V width FH width Sulcal width 3V width VBR 3V width VBR Pre-F sulcal PR-OCC sulcal VBR

Kim et al. (1993)

SZ

31

CT

VBR 3V width FHBR Sulcal width VBR

N.S.D. SCL, NSF, N.S.D. SCL. NSF, N.S.D. SCL, NSF. N.S.D. SCL, NSF, Enlarged ventricles in non-responders

Zahn et al. (1982) Aim et al. (1984) Bartfai et al. (1987)

Cannon et al. (1988)

CT

CT CT

CT

habituation rate habituation rate habituation rate habituation rate more common

VBR = ventricle/brain ratio for lateral ventricles; SZ = schizophrenics; SZ FORM = schizophreniform; R = responders: NR = nonresponders; HAB = habituators; NH = non-habituators; 3V = third ventricle; FH = frontal horn; Pre-F = pre-frontal. Par-Occ = parietaloccipital; FH BR = frontal horn/brain ratio; N.S.D. = no significant differences; NSF = non-specific fluctuations; SCL = skin conductance level.

T. L.mc: et al./Intemational

Journal of Psychophysiology

Table 1, the CT studies of SC activity do not directly measure cerebral cortex; they utilize width of sulci and fissures as approximations for cortical area. In addition, CT imaging is restricted to the axial plane which limits the structures which can be reasonably assessed. One feature common to the studies listed in Table 1 is that they all utilized subjects with schizophrenia or schizophreniform disorder, or subjects at risk for schizophrenia. Only the study of Katsanis et al. (1991) also employed patients with affective disorders in addition to schizophrenic patients. Therefore, most of these studies have been unable to address the issue of diagnostic specificity of electrodermal deficits. Furthermore, these studies did not examine differential effects based on heterogeneity of symptoms within the schizophrenic sample. Only two studies of neural correlates of electrodermal activity have been conducted using the more powerful tool of MRI (Raine et al., 1991; Tranel and Damasio, 1994). Raine et al. (1991) compared individual differences in SC orienting to individual differences in selected neuroanatomical areas in a group of 17 normal subjects. Significant positive correlations were found between pre-frontal area measures from a coronal cut and frequency of SC orienting responses, indicating that diminished pre-frontal area was associated with reduced SC orienting. Significant relationships for frontal area were not a function of greater overall brain size, as correlations remained significant after expressing key areas as a ratio of overall brain size. Similar findings were reported by Tranel and Damasio (1994) who utilized MRI to determine the site and size of brain damage in patients who had either suffered vascular lesions or undergone surgical resection of brain tumors. These authors concluded that damage to the frontal lobes (specifically bilateral ventromedial and/or dorsolatera1 prefrontal cortex) resulted in reduced magnitude of electrodermal response to physical or psychological stimuli. These two studies are consistent with some of the previous data from several older studies of the effects of frontal lesions in humans and animals (Luria and Homskaya, 1970; Bagshaw et al., 1965; Grueninger et al., 1965). However, interpretation of the study of Tranel and Damasio (1994) in this context should be tempered by the fact that they did not employ simple orienting tones. To date, there

22 (1996) 141-153

143

is still uncertainty regarding frontal lobe effects on electrodermal activity (Raine and Lencz, 1993) and the studies or Raine et al. (199 1) and Tranel and Damasio (1994) cannot yet be considered definitive. To summarize, previous research has demonstrated weak relationships between abnormal electrodermal responding in schizophrenics and CT measures of neuroanatomy, particularly ventricular enlargement. A single MRI study of normals has indicated that decreased frontal area may underlie SC hypo-responding; similar findings were reported in an MRI study of humans with brain lesions. The purpose of the present study is to extend previous research on the neural bases of electrodermal non-responding by relating MRI measures of the frontal lobes and ventricles to SC orienting activity in schizophrenics, psychiatric controls, and normal controls. The two brain areas examined in the present study, ventricular enlargement and decreased frontal area, were selected based on previous empirical research. Ventricular enlargement is one of the best replicated findings in schizophrenia (Cannon and Marco, 1994; Raz and Raz, 1990) and it has also recently been observed in affective groups (Andreasen et al., 1990). As such, it could account for SC orienting deficits reliably observed in both of these groups. Pre-frontal area was chosen because many neuroanatomical studies indicate that it plays a role in SC orienting (Tranel and Damasio, 1994; Raine and Lencz, 1993; Sequeira and Roy, 1993), and because some studies of schizophrenics have revealed reduced prefrontal area (Raine et al., 1992a; DeMyer et al., 1988). The images used for this study did not have the resolution to allow for measurement of smaller structures which may influence electroderma1 activity, such as the hippocampus, amygdala, and thalamus. The present study also seeks to extend previous research by utilizing cluster analysis, a statistical approach that can reveal potential heterogeneity of relationships both across and within diagnostic groups. The possible benefits of such an approach are indicated by several lines of research and theory. First, a number of studies have found that while different groups of patients (schizophrenics and affective disordered) both show SC hypo-responding to orienting tones, these groups may show different

patterns of response to alteration of the significance of the stimuli (Gruzelier and Venables, 1973; Iacono et al.. 1993; Bernstein et al., 1988). Second. the neuroanatomical research conducted on animals and human autopsies (cf. Sequeira and Roy, 1993). indicates that the orienting reflex is influenced by a number of cortical and subcortical neural structures, rather than one discrete brain area being responsible for orienting. A third reason to use cluster analysis is that numerous researchers and theorists have suggested that schizophrenia is itself a heterogeneous diagnosand that different sub-groups of tic category, schizophrenics may have unique psychophysiological and neuroanatomical substrates (Gruzelier and Raine, 1994; Heinrichs, 1993; Rippon, 1992; Gruzelier, 1990, 1994; Crow, 1980; Oades et al., 1996). Heinrichs (1993) has recently suggested that the use of clustering techniques on physiological variables may provide a more accurate means of subtyping schizophrenia than the traditional approach, which looks at clustering of overt symptoms. For example, there could be a sub-group of schizophrenics whose reduced SC orienting could be explained by pre-frontal deficits, while SC deficits in another schizophrenic sub-group could be explained by ventricular enlargement. Similarly, Schear (1987) demonstrated that the use of cluster analytic techniques on neurocognitive variables could provide a novel means of reclassifying a population of neuropsychiatric patients with diverse diagnoses, demonstrating similarities and differences between patients at the neurocognitive level. To address the issues raised above, the present study utilizes cluster analysis of SC orienting, frontal lobe area, and VBRs to test the following hypothe-

Table 2 Demographic

Sex (M/F) Age Parental SES ’ Years of education Height (cm)

2. Methods 2. I. Subjects Subjects were 15 schizophrenics, 15 psychiatric controls, and 15 normal controls. All subjects were

characteristics of normals, schizophrenics. and psychiatric controls (with S.D. in parentheses) Normals

Weight (kg)

ses: (1) SC hypo-responding in schizophrenics may have different neural correlates from hypo-responding in other psychiatric patients; (2) schizophrenics may show heterogeneity in the relationship between SC hypo-responding and brain abnormalities; (3) those with normal SC, regardless of diagnostic category, would not show brain abnormalities. To test the hypotheses of the present study. the cluster analysis will be examined both in terms of its internal properties (how the defining variables are related) and external correlates (how the clusters may differ on variables not entered into the cluster analysis). First, the three variables (SC and the two MRI measures) will be entered into a cluster analysis to determine how many clusters emerge. Second, the emergent clusters will be compared on the defining variables to reveal their determining characteristics. Third, a Chi-square analysis will be used to determine whether members of these clusters differ with respect to diagnostic category. Finally, symptom and demographic characteristics of the schizophrenics will be compared across clusters. It should be noted that the approach employed in the present study is exploratory, and that the goals of the present study are heuristic. Given the small sample size in the present study, it is intended to prompt future explorations of heterogeneity in schizophrenia and other psychiatric disorders.

7/s 33.9 (I 1.8)

Schizophrenics

Psychiatric controls

IO/5

IO/S

35.5 (10.1)

33.7 (11.3)

5.0

(3.0)

5.0

(3.0)

5.3

(3.0)

12.8

(2.4)

12.6

(3.4)

12.5

(1.6)

66.0 165

(3.3) (35)

61.9 I68

(5.3) (28)

69.0 154

(7.0) (34)

All differences are non-significant ([I’S > 0.30). a Based on the Classification of Occupations (Office of Population Censuses and Surveys, 1980). with lower scores indicating higher social class.

T. Lencz rt al. / International

Journal

right-handed as assessed by the Edinburgh Inventory (Oldfield, 197 1). Age, sex, parental social class, years of education, height, and weight are shown in Table 2. Social class was based on the Classification of Occupations (Office of Population Censuses and Surveys, 1980), with lower scores indicating higher social class. One-way ANOVAs indicated no significant group difference on any of these variables (all p’s > 0.33). The 15 schizophrenic patients were recruited from in-patient (n = 5) day patient (4) and out-patient (6) facilities at Queen’s Medical Centre, Nottingham. All received a diagnostic interview by a psychiatrist using the Present State Examination (PSE, Wing et al., 1974). A diagnosis of schizophrenia was arrived at using DSM-III-R criteria (American Psychiatric Association, 1987) on the basis of symptoms rated at interview, and lifetime-ever symptoms recorded from casenotes. Using the DSM-III-R subtypes, 13 were paranoid, one was disorganized type, and one was classified as residual type. Mean age was 35.0 years (S.D. = 10.1, range = 22 to 58) mean duration of the illness was 8.0 years (S.D. 7.6, range 1 to 23) and mean age at onset of illness was 26.1 (S.D. 10.0). Exclusion criteria for all subjects in the study consisted of (a) evidence of mental retardation, (b) history of serious drug or alcohol abuse, and (c) history of neurologic illness. All patients were taking neuroleptic medication at the time of testing. Medications included trifluoperazine, haloperidol, chlorpromazine, and fluphenazine. Schizophrenics were rated for negative symptoms by a psychiatrist using the SANS (Scale for the Assessment of Negative Symptoms, Andreasen and Olsen, 1982). Positive symptoms of delusions and hallucinations were assessed by the DAH (delusions and hallucinations) subscale of the PSE as derived from the CATEGO program associated with the PSE (Wing and Sturt, 1978). Frontal lobe findings for the samples used in this study have previously been reported (Raine et al., 1992a). Fifteen psychiatric controls were diagnosed by psychiatrists on the basis of symptoms recorded in patients’ psychiatric case notes according to DSMIII-R criteria. Specific DSM-III-R diagnoses were as follows: major depressive illness (n = 9), bipolar disorder (5) and panic disorder (1). Seven were inpatients, four were day patients, and four were

of Psychophysiology

145

22 C3996) 141-153

outpatients. Mean age at onset of illness was 29.8 years (S.D. = 12.1). Ten were taking anti-depressants, three were taking lithium, and seven were additionally taking neuroleptics. Two patients were unmedicated. Four schizophrenic and four psychiatric controls were additionally taking anticholinergic medication (procyclidine). None had previously received ECT treatment. Normal controls consisted of 15 subjects selected from part-time and full-time staff at the hospital, but faculty members, graduates, and medical students were excluded and efforts were made to recruit subjects of similar social and educational backgrounds to schizophrenics. Examples of occupations held by the normal controls were domestic supervisor, part-time nursery teacher, and part-time radiography helper. The same exclusion criteria as outlined for the patients were applied to normal controls. Normal controls were administered the STA (Claridge and Broks, 1984) a measure tapping

Fig. 1. Coronal MRI scan showing gem of the corpus callosum.

pre-frontal

area anterior

to

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Journal qf’Psychophwiology

schizotypal personality traits. These normal control subjects are essentially the same as those examined in the studies reported by Raine et al. (1991) and Raine et al. (1992b). The latter paper demonstrates a relationship between STA scores and reduced prefrontal area in this sample. All subjects were paid &20 for participation in the study. A chlorpromazine equivalent dosage was calculated for each patient and the relationship of this measure to the structural MRI measures, as well as number of orienting responses, was examined using correlational analysis. All resulting correlations were low and non-significant (all p’s > 0.05). Schizophrenics (mean = 601) and psychiatric controls (mean = 738) did not differ significantly on chlorpromazine equivalents, (F = 0.19, p > 0.66).

Fig. 2. Axial MRI scan showing cerebral hemispheres

22 (19961 141-153

2.2. Electrodermal

recording

All subjects were presented with six orienting tones of 75 dB intensity, 13 11 Hz frequency, 25 ms rise time, and l-s duration. Subjects were tested in a sound-proof, darkened room. SC was recorded from the medial phalanges of the first and second fingers of the left hand using silver/silver chloride electrodes. SC was measured using a computerized system for amplification and scoring developed by York Electronics. The present study examined the total number of orienting responses elicited. Orienting responses were defined as those occurring within a latency window of l-3 s post-stimulus and with a minimal amplitude of 0.01 microsiemens. The 0.01 window was used because computer scoring pro-

and ventricles at the level of their maximum enlargement.

T. Lencz et al./International

Journal of Psychophysiology 22 (1996) 141-153

vided a good signal-to-noise ratio to reliably detect nonartifactual responses below the 0.05 threshold. 2.3. Magnetic

resonance

imaging

Subjects were examined using a Picker MRI system with a 0.15 Tesla resistive magnet. Three inversion recovery scanning sequences were used; brain images were obtained in the coronal, axial and sagittal planes. The coronal scanning sequence consisted of a series of 12 coronal cuts of 10 mm thickness. The fifth cut passed through the optic chiasm, with four cuts anterior and seven cuts posterior to this reference point. The most anterior of these cuts (for all subjects) passed through pre-frontal area lying anterior to the genu of the corpus callosum, and this cut was used to assess pre-frontal area. TR (repetition time) between pulses was 2450 ms while TI (inversion time) was 400 ms. This pulse sequence was chosen in order to produce a Tl-weighted image which would maximize anatomical resolution. An example of an image of pre-frontal area is given in Fig. 1. The lateral ventricles were assessed on an axial cut taken at the level of maximal size of the lateral ventricles. TR between pulses was 1660 ms and TI was 400 ms; using this Tl-weighted sequence, the ventricles and cerebral borders were well visualized, appearing black against the gray of the brain matter. Total area of the lateral ventricles was measured on this axial image. This axial cut is shown in Fig. 2. A mid-sagittal cut of TR 1660 ms and TI 400 ms was obtained to measure total cerebral area for the computation of ventricle/brain ratios (VBRS). A coronal pilot scan was used to position the central slice, while correct head positioning in the scanner was achieved using three orthogonal laser beams. Field of view for all scans was 30 cm, and data were averaged from two excitations with 192 phase encoding steps. All regions were measured blind to diagnosis. MRI films were scored using a computerized image digitization and analysis system (Seescan) incorporating LINK Electronics camera with a zoom lens. Ventricular and hemispheric borders were traced on the computer monitor using a mouse and areas computed by the computer. The computer then calculated the number of pixels enclosed within the region of

147

interest. All analyses in the present study are reported using these pixel totals. VBRs were calculated by dividing the number of pixels in the ventricle by the total number of pixels in the cerebrum as viewed on the midsagittal cut and multiplying by 100. Interrater reliability was assessed for the frontal measures, and the Pearson correlation coefficients were 0.92 for left frontal area and 0.88 for right frontal area.

3. Statistical

analyses

3.1. Initial diagnostic

and results group comparisons

Prior to cluster analysis, the three diagnostic groups (schizophrenic, psychiatric control, healthy control) were compared using analysis of variance on the three variables of interest. The schizophrenics and psychiatric controls had significantly fewer orienting responses than the healthy controls [F = 7.49, in parentheses) = for p < 0.01; means (S.D. schizophrenics, 1.07 (1.49); for psychiatric controls, 0.87 (1.41); for healthy controls, 2.80 (1.6113. There were no significant differences in ventricle-brain ratio (F = 2.55, p = 0.091, but there was a trend toward the schizophrenic group having larger VBR [means (S.D.) = 0.163 (0.0591, 0.133 (0.0321, 0.133 (0.024), respectively]. As has been previously reported (Raine et al., 1992a), the schizophrenics had significantly smaller frontal lobes relative to the two other groups. 3.2. Cluster analysis In the first cluster analytic stage, the 45 subjects (15 schizophrenics, 15 psychiatric controls, and 15 normal controls) were entered into a cluster analysis. Three clustering variables were used: frequency of SC orienting responses, prefrontal area, and lateral VBR. The three clustering variables were z-transformed and entered into an agglomerative hierarchical cluster analysis using Ward’s clustering method and squared Euclidean distances (performed in SPSS-X, Norusis, 1990). Based on the dendrogram and a plot of the fusion coefficients (Afifi and Clark, 1990; Aldenderfer and Blashfield, 19841, three clusters were identified. One-way ANOVAs were con-

148

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rt al. /lr~tenztrtionul

Jvumul

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22 (19961 141-153

Table 3 Cluster means (and SD.) for the three variables entered into cluster analvais No. of SC responses Cluster 1: Cluster 2: Cluster 3:

0.42 (0.79) 0.50 (0.89) 3.41 (1.06)

ANOVA:

F=52.13,

Post-hoc:

1<3;2<3

Prefrontal

p
Also reported are the F statistic and significance comparisons (least-squared difference statistic)

41.24 (3.86) 50.34 (4.62) 49.68 (4.72) F= 16.98, p < 0.001 1<2;1<3

2>1

level for between-group

of clusters

Results of the ANOVAs in defining the three clusters are reported in Tables 3 and 4. Table 3 lists the cluster means of the three input variables (SC, frontal area, and VBR); as expected, ANOVAs for each of the three input variables were significant. Post-hoc paired comparisons revealed that each cluster had a distinctive profile of scores on the three variables. These profiles are described in Table 4. The first two clusters showed significant SC hyporesponding relative to the third cluster. Consequently these two clusters of subjects have been labelled as ‘hypo-responding’ clusters; that is, the subjects in these groups had signicantly fewer electrodermal orienting responses as compared to subjects classified into the third cluster. However, these two hypo-

Table 4 Identity of three clusters with respect to skin conductance pre-frontal area, and lateral ventricle/brain ratio

activity,

N

Skin conductance

Pre-frontal

Ventricles

Cluster 1 Cluster 2

I2 I6

Hypo-responsivity Hypo-responsivity

Reduced area Normal

Cluster 3

17

Normal

Normal

Normal Ventriculomegaly Normal

Lateral VBR 0. I2 (0.03) 0. I6 (0.05) 0.14 (0.03)

ducted on the clustering variables in order to determine the defining characteristics. It should be noted that ANOVAs on the clustering variables are expected to be significant as a result of the clustering process. Consequently, resultant statistics are not presented as a test of signficance, but merely to define the clusters that have been created through the clustering algorithm. 3.3. D@nition

area

comparisons,

F = 4.32, p < 0.02

and significant

(p

< 0.05) results of post-hoc

paired

responding clusters had different neuroanatomical features. It can be seen from Tables 3 and 4 that Cluster 1 consisted of subjects with significantly reduced SC orienting, significantly reduced pre-frontal area, but normal ventricles. Cluster 2 also had significantly reduced SC orienting, but had significant ventricular enlargement and normal pre-frontal area. Cluster 3, by contrast, showed normal values on all three measures. It should be noted that the terms ‘normal’ and ‘reduced’ are relative terms, determined by ANOVAs reported in Table 3. Consequently, this cluster analysis indicates that there may be at least two different structural brain abnormalities (pre-frontal deficits and ventricular enlargement) associated with SC orienting deficits in different clusters of patients. 3.4. Potential confounds The clusters did not significantly differ with respect to either chlorpromazine equivalent (F = 2.47, p > 0.10) or distribution of patients taking anticholnergic medication (X2 = 3.33, p > 0.18). Further, the three clusters did not significantly differ on overall axial brain size (F = 1.26, p > 0.281, thus suggesting that these variables did not confound the results. Finally, means of the three clusters did not significantly differ on any of the demographic variables listed in Table 2 (all p’s > 0.05). 3.5. Relation of clusters to clinical diagnosis The next question concerns whether these three clusters bear any relationship to psychiatric diagnosis. Since diagnostic status was not a variable entered

T. L.encz et al./Intemational

Journal

into the cluster analysis, this analysis constitutes a form of external validation of the cluster analytic solution. The chi-square statistic (X” = 11.18, p < 0.05) indicated a significant relationship between psychiatric group classification and cluster membership. Results of this chi-square are shown in Table 5. It can be seen that in Cluster 1 (N = 12, marked by reduced SC orienting and reduced pre-frontal area> half the subjects (N = 6) were schizophrenic. Interestingly, the three normals who fell into Cluster 1 were among the top four scorers on a measure of schizotypal personality (STA). Cluster means on the STA were 17.7, 8.0, and 9.3, respectively. Although cell sizes were small, Kruskal-Wallis analysis indicated that there was a trend towards significance in this result (X’ = 4.8, p = 0.09). It should be noted that there was no significant correlation between STA and number of orienting responses in the total sample of controls (Spearmans rho = -0.35, p > 0.20). Cluster 2 (N = 16, characterized by reduced orienting with enlarged ventricles) was overrepresented by the psychiatric controls (specifically, six unipolar depression and three bipolar patients). Cluster 3 (N = 17, normal SC, normal MRI) contained a majority of the normal controls. Consequently, these analyses suggest an association between schizophrenia-spectrum disorder, reduced SC orienting, and prefrontal deficits on the one hand, and affective disorders, reduced SC orienting, and ventricular enlargement on the other. 3.6. Heterogeneity

of schizophrenia

However, Table 5 also shows that schizophrenics were fairly evenly spread across the three clustering groups, illustrative of the heterogeneity of schizo-

Table 5 Relationship

between clusters and psychiatric

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22 (1996)

phrenia. Specifically, a third of the schizophrenics fell into Cluster 2. As such, while some schizophrenics may have SC orienting deficits associated with pre-frontal deficits, others have orienting deficits which may be more associated with ventricular enlargement. Four of the schizophrenics (28%) fell into the ‘normal’ cluster. This is consistent with the notion that brain deficits and psychophysiological deficits have rarely if ever been found to characterize all schizophrenics. Interestingly, 60% of the female schizophrenics fell into this third cluster, while 90% of male schizophrenics fell into the more ‘pathological’ Clusters 1 and 2. Furthermore, Cluster 3 schizophrenics had significantly higher scores on positive symptoms (as rated on the delusions and hallucinations subscale of the PSE) than schizophrenics in the other two clusters (F = 4.01, p < 0.05). However, there were no significant differences across clusters on measures of negative symptoms. Still, the schizophrenics falling into the ‘normal’ cluster (Cluster 3) are characterized by female gender and positive symptomatology.

4. Discussion The present study utilized cluster analytic techniques to examine the neuroanatomical correlates of SC hypo-responding in a mixed sample of psychiatric patients and controls. To the authors’ knowledge, this is the first study employing magnetic resonance imaging techniques to examine this question. Given the nature of cluster analysis and the small sample size of the present study, results cannot be considered to be definitive until replicated on independent samples; rather, they are intended to

group status (X2 = I I. 18, JJ i 0.05)

SC hypo-responding Reduced pre-frontal Cluster Schizophrenics Psychiatric controls Normals

6 3 3

149

141-153

1

Normal SC Enlarged ventricles

Normal MRI

Cluster 2

Cluster 3

5 9 2

4 3 10

150

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promote further inquiry in this important area of research, which has been marked by largely negative findings (Table 1). Results of the present study revealed two potentially important findings. First, the study indicated that there may exist two distinct subgroups of patients with SC hypo-responding. For one group, SC hypo-responding is associated with frontal lobe deficits. These subjects tend to be a subgroup of schizophrenics or controls with schizophrenia-spectrum symptomatology. For the other group, composed primarily of subjects with affective disorders, SC hypo-responding is associated with enlarged ventricles but not frontal lobe deficits. The second important finding was that the schizophrenics demonstrated a pattern of heterogeneity at the biological level. Despite the fact that one cluster was dominated by schizophrenia-spectrum subjects, a non-negligible number of schizophrenics fell into the other two clusters. Further, the schizophrenics who did not have biological deficits were predominately female and marked by more positive symptoms. The presence of this subgroup is consistent with two other findings reported in the schizophrenia literature: schizophrenia may be less severe in women, with less of a biological loading (e.g. Goldstein et al., 1989), and that schizophrenics with predominately positive symptoms may have fewer structural brain abnormalities than subjects with predominately negative symptoms (Cannon and Marco, 1994; Crow, 1980). On the basis of these prior reports, it is possible that schizophrenics in the ‘normal’ cluster may have better prognosis than others, and that this clustering technique may be a useful way of identifying this subgroup. Such a hypothesis would require a future longitudinal study for validation. In addition, one third of the schizophrenics fell into Cluster 2, which was mostly populated by affective disorder patients. Despite the differences in their clinical diagnoses, patients in this cluster were all characterized by electrodermal hypo-responding and enlarged ventricles. Additionally, three of the psychiatric control patients were found in Cluster 1. These findings are not inconsistent with the hypothesis that (at least some) schizophrenic patients may lie on the same etiopathological continuum with (at least some) affective disordered patients (e.g. Crow, 1990).

22 (19%) 141-153

The findings described in the preceding paragraphs all support the suggestion that biological variables may provide a means of subtyping psychiatric disorders, particularly schizophrenia, that is more etiologically relevant than the traditional symptombased approach (Heinrichs, 1993). This possibility is underscored by the fact that nearly all (87%) of the schizophrenics in the present study received the same DSM-III-R diagnostic subtype (paranoid), but still displayed heterogeneous biology. However, one report suggests that paranoid schizophrenics may have different psychophysiological characteristics from other groups (Rippon, 19921, so the findings of the present study should be re-examined in future studies with non-paranoid schizophrenics, The cluster analysis also suggests that the strategy of researching individual differences in schizotypal personality as an alternative ‘high risk’ approach to schizophrenia may be justified. Trends in the present study indicate those normal controls scoring high on a schizotypy scale may be characterized by pre-frontal deficits and SC orienting deficits, similar to the largest sub-group of schizophrenics. As such, these data help to illustrate how research into the neuroanatomy of SC activity, while representing a ‘basic science’ approach, can also help inform more clinical research into psychopathology. To the authors’ knowledge, this study is the first to utilize cluster analytic techniques to address the issue of neuroanatomy of electrodermal responding. This approach was chosen because it takes into account: (1) the heterogeneity of the neuroanatomical influences on the electrodermal response (Sequeira and Roy, 1993); (2) the heterogeneity of electrodermal abnormalities across diagnostic groups (Iacono et al., 1993; Bernstein et al., 1988); (3) the well-documented pathophysiological heterogeneity within diagnostic groups (Gruzelier and Raine, 1994; Carpenter et al., 1993; Heinrichs, 1993; Rippon, 1992; Gruzelier, 1990; Crow, 1980). The findings of the present study support the suggestion by Heinrichs (1993) that schizophrenia researchers expand their data analytic techniques beyond group comparison on the basis of diagnosis, by employing a range of biological markers as potential tools for identifying more homogeneous subgroups. By contrast, the initial analyses reported in the present study, in which the diagnostic groups were compared by sim-

T. Lencz et al. /International Journal of Psychophysiology 22 (1996) 141-153

ple ANOVA, would be unable to detect the patterns reported in Table 5. The findings of the present study may be best viewed as heuristic in value given the relatively small sample size employed. Cluster analytic techniques are designed to separate groups, whether or not such groups exist ‘in nature’ (Aldenderfer and Blashfield, 1984). Replication in other samples will be necessary to confirm the validity of the clusters identified in the present study. Some support for the validity of the clusters identified in the present study was provided by the the examination of ‘external’ variables, i.e. the demonstration that the clusters significantly differed on variables that were not entered in the cluster analysis itself. In addition, it should be noted that there are limitations of the MRI techniques utilized in this study (e.g. use of single-slice techniques, slice thickness, magnet strength). However, the MRI in the present study is still somewhat superior in resolution and flexibility compared to the CT scanning which has been used in previous studies of electrodermal hypo-responding in psychiatric patients. It should also be noted that the relatively low sample size and relatively weak magnet should tend to produce Type II errors and therefore is not likely to account for the positive results in the present study. Still, future studies using gradient-echo MRI with whole-brain acquisitions will be very useful in the corroboration and extension of these findings. Given the heuristic and exploratory nature of the present study, it is hoped that the results will serve to promote the further needed research in this area. The present study has found significant relationships between electrodermal abnormalities and neuroanatomical deficits in a psychiatric population, whereas most previous CT studies of this question have produced largely negative results. It is possible that the non-significant findings from some of the CT studies listed in Table 1 may not only be a function of limitations in imaging technology, but also from the attempt to seek out continuous relationships within pathological groups which are heterogenous with respect to neural deficits. Additionally, those studies listed in Table 1 that examined heterogeneity did so using a priori dichotomizations based on a single variable, rather than statistical methods (e.g. cluster analysis), which take into account the coherence of

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multiple variables. It is possible that re-analyses of these data sets using cluster analytic techniques may result in clearer links between SC orienting measures and anatomical measures. Finally, future studies seeking etiological information on the substrate of electrodermal hypo-responsivity should also attempt to link electrodermal activity with other measures of brain function, such as positron emission tomography (e.g. Hazlett et al., 1993) and electroencephalography (e.g. Rippon, 1993).

Acknowledgements This research was supported by a grant from the Medical Research Council in England (Grant # G8607450N), by a National Service Award to the first author from the National Institute of Mental Health (NIMH, MH10463-Ol), and by a Research Scientist Development Award to the second author from NIMH (MHO1114-OlSl). The authors are grateful to Denis Bell and Steve Chipperfield for technical assistance, and to Deana S. Benishay and Dr. Michael Dawson for helpful comments.

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