Biomedical subjects
Publications and source records attributed to W C Corning.
Schizophrenic subjects performed significantly worse on neuropsychological tests of frontal lobe function but not on tests of non-frontal lobe function when compared to a matched group of normal subjects. Correlations expected between frontal lobe neuropsychological test performance and negative symptoms were not found.
Thirty schizophrenic patients (20 medicated, 10 off medication) were compared with 30 normal control subjects matched for age, sex, handedness, and intelligence. During the performance of left-hemisphere cognitive activation tasks, normal subjects had significantly increased EEG alpha coherence in areas related to left focal frontal sites, with decreases in temporal and posterior areas. Schizophrenic patients did not show the same degree of focal activation of left frontal areas. During the performance of right-hemisphere cognitive activation tasks, normal subjects and schizophrenic patients had similar patterns of right posterior increases in alpha coherence. Discriminant analyses were able to classify 81.4% of all subjects correctly. It is suggested that the findings indicate an aberrant functional organisation of the brain in schizophrenia, particularly affecting the left hemisphere.
Nineteen children who had EEG diffuse slow frequency profiles suggesting a maturational lag were retested 1 to 2 years later receiving both EEG and psychometric assessments. They were compared to 18 children who also had been tested previously but did not have the slow frequency profile. Children with the maturational lag profile displayed varying degrees of EEG developmental change upon retest; i.e., some showed the expected developmental change while others remained the same. Within this group, there were significant relationships between the degree of EEG change and psychometric scores. Those that demonstrated the most EEG change had higher psychometric indices, and these relationships were not obtained in the comparison group. These findings suggest developmental heterogeneity with respect to brain maturation as measured by the EEG and also suggest that test-retest EEG data can clarify a maturational lag diagnosis.
This article discusses limitations inherent in using unilevel behavioral descriptors as the basis for the construction of psychiatric classifications. As an alternative we consider the advantages of the polythetic classification strategy as suggested by Sokal and Sneath (1963) in their description of a "numerical taxonomic" approach. They argue for the development of naturally occurring, empirically defined classes rather than categories based on single domains of behaviors such as psychiatric symptoms. Typically the research into a topic such as schizophrenia starts with a behaviorally defined class of individuals who show schizophrenic symptoms, contrasted with a nonschizophrenic control group. These groups are then tested for aberrations in other systems of functioning (blood, neurophysiological, hormonal, attentional functioning, and the like). The approach offered here requires a classificatory strategy that treats data from all levels of functioning as equivalent in forming the classes of individuals rather than as secondary to the defining symptomatic attributes. Particular emphasis is given to the choice of measures with sufficiently broad and sensitive features to find natural classes. A set of standards is given for the selection of a test battery that might be used in a polythetic approach to the investigation of schizophrenia. Finally, the utility and limits of statistical clustering techniques for handling multilevel data banks are discussed.