Spectral Signatures of Reorganised Brain Networks in Disorders of Consciousness
Srivas Chennu, Paola Finoia, Evelyn Kamau, Judith Allanson, Guy B. Williams, Martin M. Monti, Valdas Noreika, Aurina Arnatkevičiūtė, Andrés Canales-Johnson, Francisco Javier Vidal Olivares, Daniela Cabezas-Soto, David K. Menon, John D. Pickard, Adrian M. Owen, Tristan A Bekinschtein
PLoS Computational Biology October 16, 2014 DOI: 10.1371/journal.pcbi.1003887 (opens in new tab) via OpenAlex
Summary
AI-generated from the abstractConsciousness is thought to require balanced integration and differentiation of brain activity, supported by efficient networks. Analyzing high-density EEG from 32 patients with chronic disorders of consciousness and healthy controls, the authors found that patient networks showed reduced local and global efficiency and fewer hubs in the alpha frequency band. A new metric, modular span, revealed that alpha network modules in patients were spatially limited, lacking the long-distance interactions seen in controls. However, delta and theta band networks were partially reversed and more similar to each other in patients. Alpha network efficiency correlated with behavioral awareness. Notably, some behaviorally unresponsive vegetative patients with covert awareness had well-preserved alpha networks resembling controls, suggesting network mechanisms that may support consciousness despite severe behavioral impairment.
Study at a glance
| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Sample size | 32 |
| Population | Patients with chronic disorders of consciousness |
| Keywords | Neuroimaging Consciousness Covert Cognition Cognitive psychology |
| Citations | 249 |
| Key finding | Patients with disorders of consciousness had reduced alpha network efficiency and modular span, but a subset of behaviorally unresponsive patients with covert awareness showed preserved alpha networks similar to healthy controls. |
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.