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EEG Evidence Reveals Zolpidem-Related Alterations and Prognostic Value in Disorders of Consciousness

Effective treatment and accurate long-term prognostication of patients with disorders of consciousness (DOC) remain pivotal clinical issues and challenges in neuroscience. Previous studies have shown that zolpidem produces paradoxical recovery and induces similar change patterns in specific electrop...

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Autores principales: Hao, Zexuan, Xia, Xiaoyu, Bai, Yang, Wang, Yong, Dou, Weibei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9093050/
https://www.ncbi.nlm.nih.gov/pubmed/35573300
http://dx.doi.org/10.3389/fnins.2022.863016
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author Hao, Zexuan
Xia, Xiaoyu
Bai, Yang
Wang, Yong
Dou, Weibei
author_facet Hao, Zexuan
Xia, Xiaoyu
Bai, Yang
Wang, Yong
Dou, Weibei
author_sort Hao, Zexuan
collection PubMed
description Effective treatment and accurate long-term prognostication of patients with disorders of consciousness (DOC) remain pivotal clinical issues and challenges in neuroscience. Previous studies have shown that zolpidem produces paradoxical recovery and induces similar change patterns in specific electrophysiological features in some DOC (∼6%). However, whether these specific features are neural markers of responders, and how neural features evolve over time remain unclear. Here, we capitalized on static and dynamic EEG analysis techniques to fully uncover zolpidem-induced alterations in eight patients with DOC and constructed machine-learning models to predict long-term outcomes at the single-subject level. We observed consistent patterns of change across all patients in several static features (e.g., decreased relative theta power and weakened alpha-band functional connectivity) after zolpidem administration, albeit none zolpidem responders. Based on the current evidence, previously published electrophysiological features are not neural markers for zolpidem responders. Moreover, we found that the temporal dynamics of the brain slowed down after zolpidem intake. Brain states before and after zolpidem administration could be completely characterized by the EEG features. Furthermore, long-term outcomes were accurately predicted using connectivity features. Our findings suggest that EEG neural signatures have huge potential to assess consciousness states and predict fine-grained outcomes. In summary, our results extend the understanding of the effects of zolpidem on the brain and open avenues for the application prospect of zolpidem and EEG in patients with DOC.
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spelling pubmed-90930502022-05-12 EEG Evidence Reveals Zolpidem-Related Alterations and Prognostic Value in Disorders of Consciousness Hao, Zexuan Xia, Xiaoyu Bai, Yang Wang, Yong Dou, Weibei Front Neurosci Neuroscience Effective treatment and accurate long-term prognostication of patients with disorders of consciousness (DOC) remain pivotal clinical issues and challenges in neuroscience. Previous studies have shown that zolpidem produces paradoxical recovery and induces similar change patterns in specific electrophysiological features in some DOC (∼6%). However, whether these specific features are neural markers of responders, and how neural features evolve over time remain unclear. Here, we capitalized on static and dynamic EEG analysis techniques to fully uncover zolpidem-induced alterations in eight patients with DOC and constructed machine-learning models to predict long-term outcomes at the single-subject level. We observed consistent patterns of change across all patients in several static features (e.g., decreased relative theta power and weakened alpha-band functional connectivity) after zolpidem administration, albeit none zolpidem responders. Based on the current evidence, previously published electrophysiological features are not neural markers for zolpidem responders. Moreover, we found that the temporal dynamics of the brain slowed down after zolpidem intake. Brain states before and after zolpidem administration could be completely characterized by the EEG features. Furthermore, long-term outcomes were accurately predicted using connectivity features. Our findings suggest that EEG neural signatures have huge potential to assess consciousness states and predict fine-grained outcomes. In summary, our results extend the understanding of the effects of zolpidem on the brain and open avenues for the application prospect of zolpidem and EEG in patients with DOC. Frontiers Media S.A. 2022-04-27 /pmc/articles/PMC9093050/ /pubmed/35573300 http://dx.doi.org/10.3389/fnins.2022.863016 Text en Copyright © 2022 Hao, Xia, Bai, Wang and Dou. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Hao, Zexuan
Xia, Xiaoyu
Bai, Yang
Wang, Yong
Dou, Weibei
EEG Evidence Reveals Zolpidem-Related Alterations and Prognostic Value in Disorders of Consciousness
title EEG Evidence Reveals Zolpidem-Related Alterations and Prognostic Value in Disorders of Consciousness
title_full EEG Evidence Reveals Zolpidem-Related Alterations and Prognostic Value in Disorders of Consciousness
title_fullStr EEG Evidence Reveals Zolpidem-Related Alterations and Prognostic Value in Disorders of Consciousness
title_full_unstemmed EEG Evidence Reveals Zolpidem-Related Alterations and Prognostic Value in Disorders of Consciousness
title_short EEG Evidence Reveals Zolpidem-Related Alterations and Prognostic Value in Disorders of Consciousness
title_sort eeg evidence reveals zolpidem-related alterations and prognostic value in disorders of consciousness
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9093050/
https://www.ncbi.nlm.nih.gov/pubmed/35573300
http://dx.doi.org/10.3389/fnins.2022.863016
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