Classification of schizophrenia patients and healthy controls using p100 event-related potentials for visual processing

Abstract

The study of event-related potentials (ERPs) is capable of elucidating the abnormalities in brain network dynamics relevant to the information-processing deficits in schizophrenia patients. In contrast to P50 and P300 ERPs, however, the results of P100 ERP studies in schizophrenia patients are less consistent. We have previously reported that P100 amplitudes did not differ significantly between patients with schizophrenia and healthy subjects. This result raised a question as to whether P100 ERPs carry information on brain network dynamics in schizophrenia patients that is distinct from normal controls. To answer this question, in this study we performed discrimination analysis on the P100 data. The rate of correct classification of patients and controls was high (80-90% depending on stimulus categories), indicating that patients have spatial patterns of P100 amplitudes that are distinguishable from those in healthy subjects. To further explore this possibility, we performed principal component analysis on the P100 data. For the patients, the first principal component represented global activity, the second component represented the reciprocal anterior-posterior activation, and the third component represented the hemispheric reciprocity in activity. The first and second components were similar to those of the control group; however, the third component in control subjects showed activation of the center versus anterior and posterior regions. This result is consistent with the notion of abnormalities in hemispheric asymmetries during the processing of sensory information in schizophrenia. In conclusion, this ERP study demonstrated that P100 amplitudes have information that can successfully classify patients and controls.