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Clin Neurophysiol. 2017 Sep;128(9):1719-1736. doi: 10.1016/j.clinph.2017.06.246. Epub 2017 Jul 8.

Measuring alterations in oscillatory brain networks in schizophrenia with resting-state MEG: State-of-the-art and methodological challenges.

Author information

1
Department of Psychology, University of Montreal, QC, Canada. Electronic address: golnoush.alamian@umontreal.ca.
2
Department of Psychology, University of Montreal, QC, Canada; Department of Computer Science, Pontificia Universidad Católica de Chile, Santiago de Chile, Chile; School of Psychology, Pontificia Universidad Católica de Chile, and Interdisciplinary Center for Neurosciences, Pontificia Universidad Católica de Chile, Santiago de Chile, Chile.
3
Italian National Research Council, Rome, Italy.
4
Department of Psychology, University of Montreal, QC, Canada.
5
Department of Psychology, University of Montreal, QC, Canada; Inter-University Laboratory of Human Movement Biology, University Claude Bernard Lyon 1, France; DyCog Team, Lyon Neuroscience Research Center, INSERM U1028, CNRS UMR 5292 Centre Hospitalier Le Vinatier, Université Claude Bernard Lyon 1, Bron, France.
6
Department of Psychology, University of Montreal, QC, Canada; Computer Science Department, National Research Institution Higher School of Economics, Moscow, Russia; MEG Center, Moscow State University of Pedagogics and Education, Moscow, Russia.
7
PSYR2 Team, Lyon Neuroscience Research Center, INSERM U1028, CNRS UMR5292, Centre Hospitalier Le Vinatier, Université Claude Bernard Lyon 1, Bron, France; Centre Interdisciplinaire de Recherche en Réadaptation et en Intégration Sociale, Centre de Recherche de l'Institut Universitaire en Santé Mentale, Université Laval, QC, Canada.
8
Department of Psychology, University of Montreal, QC, Canada; MEG Core Facility, Department of Psychology, University of Montreal, QC, Canada.

Abstract

OBJECTIVE:

Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia (SZ). However, untangling the neuronal mechanisms that subserve these baseline alterations requires measurement of their electrophysiological underpinnings. This systematic review specifically investigates the contributions of resting-state Magnetoencephalography (MEG) in elucidating abnormal neural organization in SZ patients.

METHOD:

A systematic literature review of resting-state MEG studies in SZ was conducted. This literature is discussed in relation to findings from resting-state fMRI and EEG, as well as to task-based MEG research in SZ population. Importantly, methodological limitations are considered and recommendations to overcome current limitations are proposed.

RESULTS:

Resting-state MEG literature in SZ points towards altered local and long-range oscillatory network dynamics in various frequency bands. Critical methodological challenges with respect to experiment design, and data collection and analysis need to be taken into consideration.

CONCLUSION:

Spontaneous MEG data show that local and global neural organization is altered in SZ patients. MEG is a highly promising tool to fill in knowledge gaps about the neurophysiology of SZ. However, to reach its fullest potential, basic methodological challenges need to be overcome.

SIGNIFICANCE:

MEG-based resting-state power and connectivity findings could be great assets to clinical and translational research in psychiatry, and SZ in particular.

KEYWORDS:

Connectivity; Magnetoencephalography (MEG); Oscillations; Psychiatry; Resting-state; Schizophrenia; Synchronization

PMID:
28756348
DOI:
10.1016/j.clinph.2017.06.246
[Indexed for MEDLINE]

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