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Spectral signatures of reorganised brain networks in disorders of consciousness

Chennu, Srivas, Finoia, Paola, Kamau, Evelyn, Allanson, Judith, Williams, Guy B., Monti, Martin M., Noreika, Valdas, Arnatkeviciute, Aurina, Canales-Johnson, Andrés, Olivares, Francisco, and others. (2014) Spectral signatures of reorganised brain networks in disorders of consciousness. PLoS Computational Biology, 10 (10). e1003887. ISSN 1553-734X. E-ISSN 1553-7358. (doi:10.1371/journal.pcbi.1003887)

Abstract

Theoretical advances in the science of consciousness have proposed that it is concomitant with balanced cortical integration and differentiation, enabled by efficient networks of information transfer across multiple scales. Here, we apply graph theory to compare key signatures of such networks in high-density electroencephalographic data from 32 patients with chronic disorders of consciousness, against normative data from healthy controls. Based on connectivity within canonical frequency bands, we found that patient networks had reduced local and global efficiency, and fewer hubs in the alpha band. We devised a novel topographical metric, termed modular span, which showed that the alpha network modules in patients were also spatially circumscribed, lacking the structured long-distance interactions commonly observed in the healthy controls. Importantly however, these differences between graph-theoretic metrics were partially reversed in delta and theta band networks, which were also significantly more similar to each other in patients than controls. Going further, we found that metrics of alpha network efficiency also correlated with the degree of behavioural awareness. Intriguingly, some patients in behaviourally unresponsive vegetative states who demonstrated evidence of covert awareness with functional neuroimaging stood out from this trend: they had alpha networks that were remarkably well preserved and similar to those observed in the controls. Taken together, our findings inform current understanding of disorders of consciousness by highlighting the distinctive brain networks that characterise them. In the significant minority of vegetative patients who follow commands in neuroimaging tests, they point to putative network mechanisms that could support cognitive function and consciousness despite profound behavioural impairment.

Item Type: Article
DOI/Identification number: 10.1371/journal.pcbi.1003887
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Sciences > School of Computing
Depositing User: S. Chennu
Date Deposited: 27 Mar 2016 11:20 UTC
Last Modified: 29 May 2019 17:07 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/54636 (The current URI for this page, for reference purposes)
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