Patient, interrupted: MEG oscillation dynamics reveal temporal dysconnectivity in schizophrenia

Alamian, Golnoush, Pascarella, Annalisa, Tarek, Lajnef, Knight, Laura, Walters, James ORCID: https://orcid.org/0000-0002-6980-4053, Singh, Kirsh D. ORCID: https://orcid.org/0000-0002-3094-2475 and Jerbi, Karim 2020. Patient, interrupted: MEG oscillation dynamics reveal temporal dysconnectivity in schizophrenia. NeuroImage: Clinical 28 , 102485. 10.1016/j.nicl.2020.102485

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Abstract

Current theories of schizophrenia emphasize the role of altered information integration as the core dysfunction of this illness. While ample neuroimaging evidence for such accounts comes from investigations of spatial connectivity, understanding temporal disruptions is important to fully capture the essence of dysconnectivity in schizophrenia. Recent electrophysiology studies suggest that long-range temporal correlation (LRTC) in the amplitude dynamics of neural oscillations captures the integrity of transferred information in the healthy brain. Thus, in this study, 25 schizophrenia patients and 25 controls (8 females/group) were recorded during two five-minutes of resting-state magnetoencephalography (once with eyes-open and once with eyes-closed). We used source-level analyses to investigate temporal dysconnectivity in patients by characterizing LRTCs across cortical and sub-cortical brain regions. In addition to standard statistical assessments, we applied a machine learning framework using support vector machine to evaluate the discriminative power of LRTCs in identifying patients from healthy controls. We found that neural oscillations in schizophrenia patients were characterized by reduced signal memory and higher variability across time, as evidenced by cortical and subcortical attenuations of LRTCs in the alpha and beta frequency bands. Support vector machine significantly classified participants using LRTCs in key limbic and paralimbic brain areas, with decoding accuracy reaching 82%. Importantly, these brain regions belong to networks that are highly relevant to the symptomology of schizophrenia. These findings thus posit temporal dysconnectivity as a hallmark of altered information processing in schizophrenia, and help advance our understanding of this pathology.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) Cardiff University Brain Research Imaging Centre (CUBRIC) Medicine Psychology
Additional Information:	Licensed under Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Publisher:	Elsevier
ISSN:	2213-1582
Date of First Compliant Deposit:	1 December 2020
Date of Acceptance:	24 October 2020
Last Modified:	07 May 2023 13:59
URI:	https://orca.cardiff.ac.uk/id/eprint/136694

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