204. Components of Neural Connectivity in Relation to the Symptom Dimensions of Psychotic Psychopathology

Abstract

Abstract Background: Resting state neural activity accounts for a majority of metabolic energy consumed by the brain. Although functional magnetic resonance imaging has been useful for identifying neuroanatomical networks active during resting state, the dynamic activity within these networks is more richly described through electroencephalography (EEG) which captures high frequency oscillations cycling through cortical networks and subcortical nuclei. In order to better understand how resting-state activity may explain the phenomenology of psychotic psychopathology, we mapped the dynamics of resting state networks onto dimensions of symptomatology typically noted in schizophrenia, schizoaffective, and bipolar disorder. Subthreshold symptomatology was also examined in first-degree biological relatives of patients. Methods: Participants were enrolled in a family study of schizophrenia. Families affected by bipolar disorder and healthy controls were included for comparison. Resting EEG data were acquired during eyes open and eyes closed states. Dynamics of neural connectivity were operationalized through computing phase locking values for a broad range of EEG frequencies (1–55 Hz) for recordings across the scalp. Participants also completed diagnostic interviews, symptom rating assessments, measures of schizotypal personality factors, and cognitive testing. Results: Principal component analysis (PCA) of phase-locking values yielded 4 fundamental frequencies around which neural synchronization occurred (Delta/Theta, Alpha, Beta, Gamma). Spatial PCAs revealed four resting state oscillatory networks for each of the frequency components. The oscillatory networks were highly similar across the frequency components suggesting the existence of neuroanatomical pathways shared by frequencies during resting state cycles. The four spatial networks were identified as frontal–central–parietal, frontal interhemispheric, posterior interhemispheric, and generalized long range. A diagnosis of schizophrenia was associated with increased interhemispheric frontal synchronization in delta/theta and alpha frequency components. The frontal low frequency abnormalities were associated with lifetime negative symptoms, reality distortion, and positive formal disorder. Frontal interhemispheric delta/theta synchronization was also associated with cluster A symptoms in biological family members of individuals with schizophrenia. Conclusion: Evidence suggests that different oscillatory frequencies share neuroanatomical structures in resting state networks. Psychosis is associated with increased low frequency synchronization between frontal brain regions. The low frequency abnormalities are also predictive of psychotic symptomatology and genetic liability for schizophrenia.