Frontiers in Psychiatry (Nov 2020)

Neurophysiologic Characterization of Resting State Connectivity Abnormalities in Schizophrenia Patients

  • Daisuke Koshiyama,
  • Makoto Miyakoshi,
  • Kumiko Tanaka-Koshiyama,
  • Yash B. Joshi,
  • Juan L. Molina,
  • Joyce Sprock,
  • David L. Braff,
  • Gregory A. Light,
  • Gregory A. Light

DOI
https://doi.org/10.3389/fpsyt.2020.608154
Journal volume & issue
Vol. 11

Abstract

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Background: Patients with schizophrenia show abnormal spontaneous oscillatory activity in scalp-level electroencephalographic (EEG) responses across multiple frequency bands. While oscillations play an essential role in the transmission of information across neural networks, few studies have assessed the frequency-specific dynamics across cortical source networks at rest. Identification of the neural sources and their dynamic interactions may improve our understanding of core pathophysiologic abnormalities associated with the neuropsychiatric disorders.Methods: A novel multivector autoregressive modeling approach for assessing effective connectivity among cortical sources was developed and applied to resting-state EEG recordings obtained from n = 139 schizophrenia patients and n = 126 healthy comparison subjects.Results: Two primary abnormalities in resting-state networks were detected in schizophrenia patients. The first network involved the middle frontal and fusiform gyri and a region near the calcarine sulcus. The second network involved the cingulate gyrus and the Rolandic operculum (a region that includes the auditory cortex).Conclusions: Schizophrenia patients show widespread patterns of hyper-connectivity across a distributed network of the frontal, temporal, and occipital brain regions. Results highlight a novel approach for characterizing alterations in connectivity in the neuropsychiatric patient populations. Further mechanistic characterization of network functioning is needed to clarify the pathophysiology of neuropsychiatric and neurological diseases.

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