Spectral signatures of reorganised brain networks in disorders of consciousness.
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 hi...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2014-10-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1003887 |
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| author | Srivas Chennu Paola Finoia Evelyn Kamau Judith Allanson Guy B Williams Martin M Monti Valdas Noreika Aurina Arnatkeviciute Andrés Canales-Johnson Francisco Olivares Daniela Cabezas-Soto David K Menon John D Pickard Adrian M Owen Tristan A Bekinschtein |
| author_facet | Srivas Chennu Paola Finoia Evelyn Kamau Judith Allanson Guy B Williams Martin M Monti Valdas Noreika Aurina Arnatkeviciute Andrés Canales-Johnson Francisco Olivares Daniela Cabezas-Soto David K Menon John D Pickard Adrian M Owen Tristan A Bekinschtein |
| author_sort | Srivas Chennu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e0223bc6af4f426ea89eb287fb6bdb3c |
| institution | Kabale University |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2014-10-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-e0223bc6af4f426ea89eb287fb6bdb3c2025-08-20T03:46:12ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582014-10-011010e100388710.1371/journal.pcbi.1003887Spectral signatures of reorganised brain networks in disorders of consciousness.Srivas ChennuPaola FinoiaEvelyn KamauJudith AllansonGuy B WilliamsMartin M MontiValdas NoreikaAurina ArnatkeviciuteAndrés Canales-JohnsonFrancisco OlivaresDaniela Cabezas-SotoDavid K MenonJohn D PickardAdrian M OwenTristan A BekinschteinTheoretical 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.https://doi.org/10.1371/journal.pcbi.1003887 |
| spellingShingle | Srivas Chennu Paola Finoia Evelyn Kamau Judith Allanson Guy B Williams Martin M Monti Valdas Noreika Aurina Arnatkeviciute Andrés Canales-Johnson Francisco Olivares Daniela Cabezas-Soto David K Menon John D Pickard Adrian M Owen Tristan A Bekinschtein Spectral signatures of reorganised brain networks in disorders of consciousness. PLoS Computational Biology |
| title | Spectral signatures of reorganised brain networks in disorders of consciousness. |
| title_full | Spectral signatures of reorganised brain networks in disorders of consciousness. |
| title_fullStr | Spectral signatures of reorganised brain networks in disorders of consciousness. |
| title_full_unstemmed | Spectral signatures of reorganised brain networks in disorders of consciousness. |
| title_short | Spectral signatures of reorganised brain networks in disorders of consciousness. |
| title_sort | spectral signatures of reorganised brain networks in disorders of consciousness |
| url | https://doi.org/10.1371/journal.pcbi.1003887 |
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