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Neural coding of autonomic functions in different states of consciousness

Detecting signs of residual neural activity in patients with altered states of consciousness is a crucial issue for the customization of neurorehabilitation treatments and clinical decision-making. With this large observational prospective study, we propose an innovative approach to detect residual...

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Autores principales: Liuzzi, Piergiuseppe, Hakiki, Bahia, Scarpino, Maenia, Burali, Rachele, Maiorelli, Antonio, Draghi, Francesca, Romoli, Anna Maria, Grippo, Antonello, Cecchi, Francesca, Mannini, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369699/
https://www.ncbi.nlm.nih.gov/pubmed/37491259
http://dx.doi.org/10.1186/s12984-023-01216-6
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author Liuzzi, Piergiuseppe
Hakiki, Bahia
Scarpino, Maenia
Burali, Rachele
Maiorelli, Antonio
Draghi, Francesca
Romoli, Anna Maria
Grippo, Antonello
Cecchi, Francesca
Mannini, Andrea
author_facet Liuzzi, Piergiuseppe
Hakiki, Bahia
Scarpino, Maenia
Burali, Rachele
Maiorelli, Antonio
Draghi, Francesca
Romoli, Anna Maria
Grippo, Antonello
Cecchi, Francesca
Mannini, Andrea
author_sort Liuzzi, Piergiuseppe
collection PubMed
description Detecting signs of residual neural activity in patients with altered states of consciousness is a crucial issue for the customization of neurorehabilitation treatments and clinical decision-making. With this large observational prospective study, we propose an innovative approach to detect residual signs of consciousness via the assessment of the amount of autonomic information coded within the brain. The latter was estimated by computing the mutual information (MI) between preprocessed EEG and ECG signals, to be then compared across consciousness groups, together with the absolute power and an international qualitative labeling. One-hundred seventy-four patients (73 females, 42%) were included in the study (median age of 65 years [IQR = 20], MCS +: 29, MCS −: 23, UWS: 29). Electroencephalography (EEG) information content was found to be mostly related to the coding of electrocardiography (ECG) activity, i.e., with higher MI (p < 0.05), in Unresponsive Wakefulness Syndrome and Minimally Consciousness State minus (MCS −). EEG-ECG MI, besides clearly discriminating patients in an MCS − and +, significantly differed between lesioned areas (sides) in a subgroup of unilateral hemorrhagic patients. Crucially, such an accessible and non-invasive measure of residual consciousness signs was robust across electrodes and patient groups. Consequently, exiting from a strictly neuro-centric consciousness detection approach may be the key to provide complementary insights for the objective assessment of patients' consciousness levels and for the patient-specific planning of rehabilitative interventions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12984-023-01216-6.
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spelling pubmed-103696992023-07-27 Neural coding of autonomic functions in different states of consciousness Liuzzi, Piergiuseppe Hakiki, Bahia Scarpino, Maenia Burali, Rachele Maiorelli, Antonio Draghi, Francesca Romoli, Anna Maria Grippo, Antonello Cecchi, Francesca Mannini, Andrea J Neuroeng Rehabil Research Detecting signs of residual neural activity in patients with altered states of consciousness is a crucial issue for the customization of neurorehabilitation treatments and clinical decision-making. With this large observational prospective study, we propose an innovative approach to detect residual signs of consciousness via the assessment of the amount of autonomic information coded within the brain. The latter was estimated by computing the mutual information (MI) between preprocessed EEG and ECG signals, to be then compared across consciousness groups, together with the absolute power and an international qualitative labeling. One-hundred seventy-four patients (73 females, 42%) were included in the study (median age of 65 years [IQR = 20], MCS +: 29, MCS −: 23, UWS: 29). Electroencephalography (EEG) information content was found to be mostly related to the coding of electrocardiography (ECG) activity, i.e., with higher MI (p < 0.05), in Unresponsive Wakefulness Syndrome and Minimally Consciousness State minus (MCS −). EEG-ECG MI, besides clearly discriminating patients in an MCS − and +, significantly differed between lesioned areas (sides) in a subgroup of unilateral hemorrhagic patients. Crucially, such an accessible and non-invasive measure of residual consciousness signs was robust across electrodes and patient groups. Consequently, exiting from a strictly neuro-centric consciousness detection approach may be the key to provide complementary insights for the objective assessment of patients' consciousness levels and for the patient-specific planning of rehabilitative interventions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12984-023-01216-6. BioMed Central 2023-07-26 /pmc/articles/PMC10369699/ /pubmed/37491259 http://dx.doi.org/10.1186/s12984-023-01216-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Liuzzi, Piergiuseppe
Hakiki, Bahia
Scarpino, Maenia
Burali, Rachele
Maiorelli, Antonio
Draghi, Francesca
Romoli, Anna Maria
Grippo, Antonello
Cecchi, Francesca
Mannini, Andrea
Neural coding of autonomic functions in different states of consciousness
title Neural coding of autonomic functions in different states of consciousness
title_full Neural coding of autonomic functions in different states of consciousness
title_fullStr Neural coding of autonomic functions in different states of consciousness
title_full_unstemmed Neural coding of autonomic functions in different states of consciousness
title_short Neural coding of autonomic functions in different states of consciousness
title_sort neural coding of autonomic functions in different states of consciousness
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369699/
https://www.ncbi.nlm.nih.gov/pubmed/37491259
http://dx.doi.org/10.1186/s12984-023-01216-6
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