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Resting-state networks distinguish locked-in from vegetative state patients()
PURPOSE: Locked-in syndrome and vegetative state are distinct outcomes from coma. Despite their differences, they are clinically difficult to distinguish at the early stage and current diagnostic tools remain insufficient. Since some brain functions are preserved in locked-in syndrome, we postulated...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4913176/ https://www.ncbi.nlm.nih.gov/pubmed/27330978 http://dx.doi.org/10.1016/j.nicl.2016.06.003 |
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author | Roquet, Daniel Foucher, Jack R. Froehlig, Pierre Renard, Félix Pottecher, Julien Besancenot, Hortense Schneider, Francis Schenck, Maleka Kremer, Stéphane |
author_facet | Roquet, Daniel Foucher, Jack R. Froehlig, Pierre Renard, Félix Pottecher, Julien Besancenot, Hortense Schneider, Francis Schenck, Maleka Kremer, Stéphane |
author_sort | Roquet, Daniel |
collection | PubMed |
description | PURPOSE: Locked-in syndrome and vegetative state are distinct outcomes from coma. Despite their differences, they are clinically difficult to distinguish at the early stage and current diagnostic tools remain insufficient. Since some brain functions are preserved in locked-in syndrome, we postulated that networks of spontaneously co-activated brain areas might be present in locked-in patients, similar to healthy controls, but not in patients in a vegetative state. METHODS: Five patients with locked-in syndrome, 12 patients in a vegetative state and 19 healthy controls underwent a resting-state fMRI scan. Individual spatial independent component analysis was used to separate spontaneous brain co-activations from noise. These co-activity maps were selected and then classified by two raters as either one of eight resting-state networks commonly shared across subjects or as specific to a subject. RESULTS: The numbers of spontaneous co-activity maps, total resting-state networks, and resting-state networks underlying high-level cognitive activity were shown to differentiate controls and locked-in patients from patients in a vegetative state. Analyses of each common resting-state network revealed that the default mode network accurately distinguished locked-in from vegetative-state patients. The frontoparietal network also had maximum specificity but more limited sensitivity. CONCLUSIONS: This study reinforces previous reports on the preservation of the default mode network in locked-in syndrome in contrast to vegetative state but extends them by suggesting that other networks might be relevant to the diagnosis of locked-in syndrome. The aforementioned analysis of fMRI brain activity at rest might be a step in the development of a diagnostic biomarker to distinguish locked-in syndrome from vegetative state. |
format | Online Article Text |
id | pubmed-4913176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-49131762016-06-21 Resting-state networks distinguish locked-in from vegetative state patients() Roquet, Daniel Foucher, Jack R. Froehlig, Pierre Renard, Félix Pottecher, Julien Besancenot, Hortense Schneider, Francis Schenck, Maleka Kremer, Stéphane Neuroimage Clin Regular Article PURPOSE: Locked-in syndrome and vegetative state are distinct outcomes from coma. Despite their differences, they are clinically difficult to distinguish at the early stage and current diagnostic tools remain insufficient. Since some brain functions are preserved in locked-in syndrome, we postulated that networks of spontaneously co-activated brain areas might be present in locked-in patients, similar to healthy controls, but not in patients in a vegetative state. METHODS: Five patients with locked-in syndrome, 12 patients in a vegetative state and 19 healthy controls underwent a resting-state fMRI scan. Individual spatial independent component analysis was used to separate spontaneous brain co-activations from noise. These co-activity maps were selected and then classified by two raters as either one of eight resting-state networks commonly shared across subjects or as specific to a subject. RESULTS: The numbers of spontaneous co-activity maps, total resting-state networks, and resting-state networks underlying high-level cognitive activity were shown to differentiate controls and locked-in patients from patients in a vegetative state. Analyses of each common resting-state network revealed that the default mode network accurately distinguished locked-in from vegetative-state patients. The frontoparietal network also had maximum specificity but more limited sensitivity. CONCLUSIONS: This study reinforces previous reports on the preservation of the default mode network in locked-in syndrome in contrast to vegetative state but extends them by suggesting that other networks might be relevant to the diagnosis of locked-in syndrome. The aforementioned analysis of fMRI brain activity at rest might be a step in the development of a diagnostic biomarker to distinguish locked-in syndrome from vegetative state. Elsevier 2016-06-06 /pmc/articles/PMC4913176/ /pubmed/27330978 http://dx.doi.org/10.1016/j.nicl.2016.06.003 Text en © 2016 Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Regular Article Roquet, Daniel Foucher, Jack R. Froehlig, Pierre Renard, Félix Pottecher, Julien Besancenot, Hortense Schneider, Francis Schenck, Maleka Kremer, Stéphane Resting-state networks distinguish locked-in from vegetative state patients() |
title | Resting-state networks distinguish locked-in from vegetative state patients() |
title_full | Resting-state networks distinguish locked-in from vegetative state patients() |
title_fullStr | Resting-state networks distinguish locked-in from vegetative state patients() |
title_full_unstemmed | Resting-state networks distinguish locked-in from vegetative state patients() |
title_short | Resting-state networks distinguish locked-in from vegetative state patients() |
title_sort | resting-state networks distinguish locked-in from vegetative state patients() |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4913176/ https://www.ncbi.nlm.nih.gov/pubmed/27330978 http://dx.doi.org/10.1016/j.nicl.2016.06.003 |
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