DeSIPhER: developing schizophrenia identification using physiological EEG responses

Schizophrenia is a serious mental illness that manifests itself with inconsistent, complex, and challenging to diagnose clinical symptoms. This study aimed to combine neurophysiological (electroencephalography or EEG), behavioural, and cognitive tests in one diagnostic protocol to probe the heterogeneous aspects of schizophrenia. Four experiments were conducted with 19 healthy control subjects and 6 schizophrenia spectrum disorder patients (3 schizophrenia, 3 schizoaffective disorder). In the auditory odd-ball task, patients showed diminished mismatch negativity (MMN) to all the 5 deviant types. Schizophrenia patients had a longer location MMN peak latency compared to both control subjects and schizoaffective disorder patients. The computerized Stroop task did not elicit traditional Stroop effect. However, this task in patients showed high error rates and response latencies. The significant difference in the EEG response to the congruent and incongruent stimuli was absent in patients. The schizophrenia and schizoaffective disorder patients also showed a difference in task-specific neural mechanisms. Cambridge Neurophysiological Test Automated Battery (CANTAB) tests revealed significant deficits in motor response, visuo-spatial association, spatial working memory, and verbal recognition memory in patients. In the facial emotion recognition task, patients had significantly higher error rates and response latencies. Schizophrenia patients showed the highest error rate for angry and sad stimuli. The patients showed a deficit in the early face processing EEG response at the occipito-temporal electrode, and an elevated frontal EEG response relative to the healthy subjects. This was an explorative study that conducted a diverse set of experiments with same group of healthy subjects and patients. It uncovered significant differences between the control and patient groups, and between the schizophrenia and schizoaffective disorder patients. These results exhibited a proof-of-concept for the importance of a combined protocol which could potentially lead to a discovery of biomarkers for diagnosis using a larger, diverse group of schizophrenia spectrum disorder patients.Schizophrenia is a serious mental illness that manifests itself with inconsistent, complex, and challenging to diagnose clinical symptoms. This study aimed to combine neurophysiological (electroencephalography or EEG), behavioural, and cognitive tests in one diagnostic protocol to probe the heterogeneous aspects of schizophrenia. Four experiments were conducted with 19 healthy control subjects and 6 schizophrenia spectrum disorder patients (3 schizophrenia, 3 schizoaffective disorder). In the auditory odd-ball task, patients showed diminished mismatch negativity (MMN) to all the 5 deviant types. Schizophrenia patients had a longer location MMN peak latency compared to both control subjects and schizoaffective disorder patients. The computerized Stroop task did not elicit traditional Stroop effect. However, this task in patients showed high error rates and response latencies. The significant difference in the EEG response to the congruent and incongruent stimuli was absent in patients. The schizophrenia and schizoaffective disorder patients also showed a difference in task-specific neural mechanisms. Cambridge Neurophysiological Test Automated Battery (CANTAB) tests revealed significant deficits in motor response, visuo-spatial association, spatial working memory, and verbal recognition memory in patients. In the facial emotion recognition task, patients had significantly higher error rates and response latencies. Schizophrenia patients showed the highest error rate for angry and sad stimuli. The patients showed a deficit in the early face processing EEG response at the occipito-temporal electrode, and an elevated frontal EEG response relative to the healthy subjects. This was an explorative study that conducted a diverse set of experiments with same group of healthy subjects and patients. It uncovered significant differences between the control and patient groups, and between the schizophrenia and schizoaffective disorder patients. These results exhibited a proof-of-concept for the importance of a combined protocol which could potentially lead to a discovery of biomarkers for diagnosis using a larger, diverse group of schizophrenia spectrum disorder patients