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Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury
Tools assaying the neural networks that modulate consciousness may facilitate tracking of recovery after acute severe brain injury. The ABCD framework classifies resting-state EEG into categories reflecting levels of thalamocortical network function that correlate with outcome in post-cardiac arrest...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9759728/ https://www.ncbi.nlm.nih.gov/pubmed/35569326 http://dx.doi.org/10.1016/j.cortex.2022.04.007 |
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author | Curley, William H. Bodien, Yelena G. Zhou, David W. Conte, Mary M. Foulkes, Andrea S. Giacino, Joseph T. Victor, Jonathan D. Schiff, Nicholas D. Edlow, Brian L. |
author_facet | Curley, William H. Bodien, Yelena G. Zhou, David W. Conte, Mary M. Foulkes, Andrea S. Giacino, Joseph T. Victor, Jonathan D. Schiff, Nicholas D. Edlow, Brian L. |
author_sort | Curley, William H. |
collection | PubMed |
description | Tools assaying the neural networks that modulate consciousness may facilitate tracking of recovery after acute severe brain injury. The ABCD framework classifies resting-state EEG into categories reflecting levels of thalamocortical network function that correlate with outcome in post-cardiac arrest coma. In this longitudinal cohort study, we applied the ABCD framework to 20 patients with acute severe traumatic brain injury requiring intensive care (12 of whom were also studied at ≥6-months post-injury) and 16 healthy controls. We tested four hypotheses: 1) EEG ABCD classifications are spatially heterogeneous and temporally variable; 2) ABCD classifications improve longitudinally, commensurate with the degree of behavioral recovery; 3) ABCD classifications correlate with behavioral level of consciousness; and 4) the Coma Recovery Scale-Revised arousal facilitation protocol yields improved ABCD classifications. Channel-level EEG power spectra were classified based on spectral peaks within pre-defined frequency bands: ‘A’ = no peaks above delta (<4 Hz) range (complete thalamocortical disruption); ‘B’ = theta (4–8 Hz) peak (severe thalamocortical disruption); ‘C’ = theta and beta (13–24 Hz) peaks (moderate thalamocortical disruption); or ‘D’ = alpha (8–13 Hz) and beta peaks (normal thalamocortical function). Acutely, 95% of patients demonstrated ‘D’ signals in at least one channel but exhibited within-session temporal variability and spatial heterogeneity in the proportion of different channel-level ABCD classifications. By contrast, healthy participants and patients at follow-up consistently demonstrated signals corresponding to intact thalamocortical network function. Patients demonstrated longitudinal improvement in ABCD classifications (p < .05) and ABCD classification distinguished patients with and without command-following in the subacute-to-chronic phase of recovery (p < .01). In patients studied acutely, ABCD classifications improved after the Coma Recovery Scale-Revised arousal facilitation protocol (p < .05) but did not correspond with behavioral level of consciousness. These findings support the use of the ABCD framework to characterize channel-level EEG dynamics and track fluctuations in functional thalamocortical network integrity in spatial detail. |
format | Online Article Text |
id | pubmed-9759728 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-97597282022-12-18 Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury Curley, William H. Bodien, Yelena G. Zhou, David W. Conte, Mary M. Foulkes, Andrea S. Giacino, Joseph T. Victor, Jonathan D. Schiff, Nicholas D. Edlow, Brian L. Cortex Article Tools assaying the neural networks that modulate consciousness may facilitate tracking of recovery after acute severe brain injury. The ABCD framework classifies resting-state EEG into categories reflecting levels of thalamocortical network function that correlate with outcome in post-cardiac arrest coma. In this longitudinal cohort study, we applied the ABCD framework to 20 patients with acute severe traumatic brain injury requiring intensive care (12 of whom were also studied at ≥6-months post-injury) and 16 healthy controls. We tested four hypotheses: 1) EEG ABCD classifications are spatially heterogeneous and temporally variable; 2) ABCD classifications improve longitudinally, commensurate with the degree of behavioral recovery; 3) ABCD classifications correlate with behavioral level of consciousness; and 4) the Coma Recovery Scale-Revised arousal facilitation protocol yields improved ABCD classifications. Channel-level EEG power spectra were classified based on spectral peaks within pre-defined frequency bands: ‘A’ = no peaks above delta (<4 Hz) range (complete thalamocortical disruption); ‘B’ = theta (4–8 Hz) peak (severe thalamocortical disruption); ‘C’ = theta and beta (13–24 Hz) peaks (moderate thalamocortical disruption); or ‘D’ = alpha (8–13 Hz) and beta peaks (normal thalamocortical function). Acutely, 95% of patients demonstrated ‘D’ signals in at least one channel but exhibited within-session temporal variability and spatial heterogeneity in the proportion of different channel-level ABCD classifications. By contrast, healthy participants and patients at follow-up consistently demonstrated signals corresponding to intact thalamocortical network function. Patients demonstrated longitudinal improvement in ABCD classifications (p < .05) and ABCD classification distinguished patients with and without command-following in the subacute-to-chronic phase of recovery (p < .01). In patients studied acutely, ABCD classifications improved after the Coma Recovery Scale-Revised arousal facilitation protocol (p < .05) but did not correspond with behavioral level of consciousness. These findings support the use of the ABCD framework to characterize channel-level EEG dynamics and track fluctuations in functional thalamocortical network integrity in spatial detail. 2022-07 2022-04-15 /pmc/articles/PMC9759728/ /pubmed/35569326 http://dx.doi.org/10.1016/j.cortex.2022.04.007 Text en https://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/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ). |
spellingShingle | Article Curley, William H. Bodien, Yelena G. Zhou, David W. Conte, Mary M. Foulkes, Andrea S. Giacino, Joseph T. Victor, Jonathan D. Schiff, Nicholas D. Edlow, Brian L. Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury |
title | Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury |
title_full | Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury |
title_fullStr | Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury |
title_full_unstemmed | Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury |
title_short | Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury |
title_sort | electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9759728/ https://www.ncbi.nlm.nih.gov/pubmed/35569326 http://dx.doi.org/10.1016/j.cortex.2022.04.007 |
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