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Tytuł pozycji:

Neurophysiologic Characterization of Resting State Connectivity Abnormalities in Schizophrenia Patients.

Tytuł:
Neurophysiologic Characterization of Resting State Connectivity Abnormalities in Schizophrenia Patients.
Autorzy:
Koshiyama D; Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
Miyakoshi M; Swartz Center for Neural Computation, University of California, San Diego, La Jolla, CA, United States.
Tanaka-Koshiyama K; Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
Joshi YB; Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
Molina JL; Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
Sprock J; Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
Braff DL; Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
Light GA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.; VISN-22 Mental Illness, Research, Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, United States.
Źródło:
Frontiers in psychiatry [Front Psychiatry] 2020 Nov 27; Vol. 11, pp. 608154. Date of Electronic Publication: 2020 Nov 27 (Print Publication: 2020).
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Original Publication: Switzerland : Frontiers Research Foundation, 2010-
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Contributed Indexing:
Keywords: biomarker; effective connectivity; frontal cortex; resting-state electroencephalography (EEG); schizophrenia; source level analysis; temporal cortex
Entry Date(s):
Date Created: 20201217 Latest Revision: 20201218
Update Code:
20240105
PubMed Central ID:
PMC7729083
DOI:
10.3389/fpsyt.2020.608154
PMID:
33329160
Czasopismo naukowe
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.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2020 Koshiyama, Miyakoshi, Tanaka-Koshiyama, Joshi, Molina, Sprock, Braff and Light.)

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