Dynamic Characteristics of Micro-state Transition Defined by Instantaneous Frequency in the Electroencephalography of Schizophrenia Patients

Abstract

Recently proposed dynamic functional connectivity (dFC) approach, which focuses on the degree of spatial-temporal variability in regional-pair-wise functional connectivity (FC), is able to detect neural network alternations as the core neural basis of schizophrenia (SZ). Moreover, from the perspective of “emergence” in complex network science, the importance of the establishment of a method to evaluate the neural interactions in the whole brain network, not separating each pair-wise interaction, is emphasized. We proposed the micro-state approach based on the whole-brain instantaneous frequency distribution as one of these methods; this approach opens a new avenue as an evaluation method to detect cognitive function impairment and pathology. Thus, we hypothesized that the application of this micro-state approach to neural activity could detect the other aspects of brain network alterations for SZ previously elucidated in conventional FC and dFC. We applied the micro-state approach to electroencephalography (EEG) signals of SZ patients and healthy controls. The results revealed the alternation of dynamical leading phase transitions between the frontal and occipital regions and right and left hemispheric regions at the beta and gamma bands. This alternation suggested the corpus callosum impairments and abnormal enhancement of functional hub structure at the fast bands as topology of whole brain functional network. Thus, our proposed micro-state approach succeeded in detecting the state transition alternations concerning SZ pathology. This approach might contribute in elucidating new aspects of dFC, thereby resulting in the discovery of a biomarker for SZ.