Brain dynamic organization at the acute stage of severe brain injury

Autores
Della Bella, Gabriel Alejandro; Sarton, Benjamine; Mattia, Giulia Maria; Peran, Patrice; Lamberti, Pedro Walter; Barttfeld, Pablo; Silva, Stein
Año de publicación
2026
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Acute Disorders of consciousness (DoC) poses significant clinical challenges, including early and accurate prognostication of neurological outcomes. Current assessment tools are limited in their predictive power, leaving many patients in a "gray zone" of uncertainty. While acute DoC are traditionally associated with structural brain damage, emerging evidence suggests that they are primarily driven by a withdrawal of excitatory synaptic activity across key cortical and subcortical regions, which can be captured through the dynamic analysis of resting-state brain activity. This study investigates the temporal dynamics of brain connectivity, shortly after severe brain injury (average of 13.9 days from onset), hypothesizing that acute DoC is marked by a global reorganization of functional connectivity and a shift toward less informative brain states, with distinct patterns emerging based on the underlying injury mechanism. Using functional magnetic resonance imaging (fMRI), we identify six distinct brain states across severely brain injured patients and healthy controls. These states, when sorted by decreasing entropy, span a continuum from state 1, characterized by high entropy, widespread positive long-distance coordination, and high global connectivity, predominantly observed in healthy controls, to state 6, which exhibits low entropy and minimal functional connectivity, and is predominantly associated with acute DoC. We demonstrate that the probability of occurrence of the more complex brain state correlates with improved neurological recovery at 3 months, as assessed by the Coma Recovery Scale–Revised (CRS-R). Hence, we were able to train a classifier based on brain state dynamics that achieved an accuracy of 78.5% in predicting patients' recovery potential (AUC = 0.864). Overall, our findings suggest that dynamic brain connectivity, particularly the entropy of brain states, can be a reliable early predictor of recovery from acute DoC, bridging the divide between theoretical advances and bedside medical decision-making.
Fil: Della Bella, Gabriel Alejandro. Universidad Nacional de Córdoba. Instituto de Investigaciones Psicológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Psicológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina
Fil: Sarton, Benjamine. Universite de Toulose - Le Mirail; Francia. University Teaching Hospital of Purpan; Francia
Fil: Mattia, Giulia Maria. Universite de Toulose - Le Mirail; Francia
Fil: Peran, Patrice. Universite de Toulose - Le Mirail; Francia
Fil: Lamberti, Pedro Walter. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina
Fil: Barttfeld, Pablo. Universidad Nacional de Córdoba. Instituto de Investigaciones Psicológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Psicológicas; Argentina
Fil: Silva, Stein. Universite de Toulose - Le Mirail; Francia. University Teaching Hospital of Purpan; Francia
Materia
FMRI
Consciousness
Coma
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/289310
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Brain dynamic organization at the acute stage of severe brain injuryDella Bella, Gabriel AlejandroSarton, BenjamineMattia, Giulia MariaPeran, PatriceLamberti, Pedro WalterBarttfeld, PabloSilva, SteinFMRIConsciousnessComahttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Acute Disorders of consciousness (DoC) poses significant clinical challenges, including early and accurate prognostication of neurological outcomes. Current assessment tools are limited in their predictive power, leaving many patients in a "gray zone" of uncertainty. While acute DoC are traditionally associated with structural brain damage, emerging evidence suggests that they are primarily driven by a withdrawal of excitatory synaptic activity across key cortical and subcortical regions, which can be captured through the dynamic analysis of resting-state brain activity. This study investigates the temporal dynamics of brain connectivity, shortly after severe brain injury (average of 13.9 days from onset), hypothesizing that acute DoC is marked by a global reorganization of functional connectivity and a shift toward less informative brain states, with distinct patterns emerging based on the underlying injury mechanism. Using functional magnetic resonance imaging (fMRI), we identify six distinct brain states across severely brain injured patients and healthy controls. These states, when sorted by decreasing entropy, span a continuum from state 1, characterized by high entropy, widespread positive long-distance coordination, and high global connectivity, predominantly observed in healthy controls, to state 6, which exhibits low entropy and minimal functional connectivity, and is predominantly associated with acute DoC. We demonstrate that the probability of occurrence of the more complex brain state correlates with improved neurological recovery at 3 months, as assessed by the Coma Recovery Scale–Revised (CRS-R). Hence, we were able to train a classifier based on brain state dynamics that achieved an accuracy of 78.5% in predicting patients' recovery potential (AUC = 0.864). Overall, our findings suggest that dynamic brain connectivity, particularly the entropy of brain states, can be a reliable early predictor of recovery from acute DoC, bridging the divide between theoretical advances and bedside medical decision-making.Fil: Della Bella, Gabriel Alejandro. Universidad Nacional de Córdoba. Instituto de Investigaciones Psicológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Psicológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; ArgentinaFil: Sarton, Benjamine. Universite de Toulose - Le Mirail; Francia. University Teaching Hospital of Purpan; FranciaFil: Mattia, Giulia Maria. Universite de Toulose - Le Mirail; FranciaFil: Peran, Patrice. Universite de Toulose - Le Mirail; FranciaFil: Lamberti, Pedro Walter. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; ArgentinaFil: Barttfeld, Pablo. Universidad Nacional de Córdoba. Instituto de Investigaciones Psicológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Psicológicas; ArgentinaFil: Silva, Stein. Universite de Toulose - Le Mirail; Francia. University Teaching Hospital of Purpan; FranciaElsevier2026-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/289310Della Bella, Gabriel Alejandro; Sarton, Benjamine; Mattia, Giulia Maria; Peran, Patrice; Lamberti, Pedro Walter; et al.; Brain dynamic organization at the acute stage of severe brain injury; Elsevier; Journal Neuroimag; 325; 1-2026; 1-81053-8119CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S1053811925006603info:eu-repo/semantics/altIdentifier/doi/10.1016/j.neuroimage.2025.121657info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-08-25T14:35:04Zoai:ri.conicet.gov.ar:11336/289310instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982026-08-25 14:35:05.182CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Brain dynamic organization at the acute stage of severe brain injury
title Brain dynamic organization at the acute stage of severe brain injury
spellingShingle Brain dynamic organization at the acute stage of severe brain injury
Della Bella, Gabriel Alejandro
FMRI
Consciousness
Coma
title_short Brain dynamic organization at the acute stage of severe brain injury
title_full Brain dynamic organization at the acute stage of severe brain injury
title_fullStr Brain dynamic organization at the acute stage of severe brain injury
title_full_unstemmed Brain dynamic organization at the acute stage of severe brain injury
title_sort Brain dynamic organization at the acute stage of severe brain injury
dc.creator.none.fl_str_mv Della Bella, Gabriel Alejandro
Sarton, Benjamine
Mattia, Giulia Maria
Peran, Patrice
Lamberti, Pedro Walter
Barttfeld, Pablo
Silva, Stein
author Della Bella, Gabriel Alejandro
author_facet Della Bella, Gabriel Alejandro
Sarton, Benjamine
Mattia, Giulia Maria
Peran, Patrice
Lamberti, Pedro Walter
Barttfeld, Pablo
Silva, Stein
author_role author
author2 Sarton, Benjamine
Mattia, Giulia Maria
Peran, Patrice
Lamberti, Pedro Walter
Barttfeld, Pablo
Silva, Stein
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv FMRI
Consciousness
Coma
topic FMRI
Consciousness
Coma
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.1
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Acute Disorders of consciousness (DoC) poses significant clinical challenges, including early and accurate prognostication of neurological outcomes. Current assessment tools are limited in their predictive power, leaving many patients in a "gray zone" of uncertainty. While acute DoC are traditionally associated with structural brain damage, emerging evidence suggests that they are primarily driven by a withdrawal of excitatory synaptic activity across key cortical and subcortical regions, which can be captured through the dynamic analysis of resting-state brain activity. This study investigates the temporal dynamics of brain connectivity, shortly after severe brain injury (average of 13.9 days from onset), hypothesizing that acute DoC is marked by a global reorganization of functional connectivity and a shift toward less informative brain states, with distinct patterns emerging based on the underlying injury mechanism. Using functional magnetic resonance imaging (fMRI), we identify six distinct brain states across severely brain injured patients and healthy controls. These states, when sorted by decreasing entropy, span a continuum from state 1, characterized by high entropy, widespread positive long-distance coordination, and high global connectivity, predominantly observed in healthy controls, to state 6, which exhibits low entropy and minimal functional connectivity, and is predominantly associated with acute DoC. We demonstrate that the probability of occurrence of the more complex brain state correlates with improved neurological recovery at 3 months, as assessed by the Coma Recovery Scale–Revised (CRS-R). Hence, we were able to train a classifier based on brain state dynamics that achieved an accuracy of 78.5% in predicting patients' recovery potential (AUC = 0.864). Overall, our findings suggest that dynamic brain connectivity, particularly the entropy of brain states, can be a reliable early predictor of recovery from acute DoC, bridging the divide between theoretical advances and bedside medical decision-making.
Fil: Della Bella, Gabriel Alejandro. Universidad Nacional de Córdoba. Instituto de Investigaciones Psicológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Psicológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina
Fil: Sarton, Benjamine. Universite de Toulose - Le Mirail; Francia. University Teaching Hospital of Purpan; Francia
Fil: Mattia, Giulia Maria. Universite de Toulose - Le Mirail; Francia
Fil: Peran, Patrice. Universite de Toulose - Le Mirail; Francia
Fil: Lamberti, Pedro Walter. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina
Fil: Barttfeld, Pablo. Universidad Nacional de Córdoba. Instituto de Investigaciones Psicológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Psicológicas; Argentina
Fil: Silva, Stein. Universite de Toulose - Le Mirail; Francia. University Teaching Hospital of Purpan; Francia
description Acute Disorders of consciousness (DoC) poses significant clinical challenges, including early and accurate prognostication of neurological outcomes. Current assessment tools are limited in their predictive power, leaving many patients in a "gray zone" of uncertainty. While acute DoC are traditionally associated with structural brain damage, emerging evidence suggests that they are primarily driven by a withdrawal of excitatory synaptic activity across key cortical and subcortical regions, which can be captured through the dynamic analysis of resting-state brain activity. This study investigates the temporal dynamics of brain connectivity, shortly after severe brain injury (average of 13.9 days from onset), hypothesizing that acute DoC is marked by a global reorganization of functional connectivity and a shift toward less informative brain states, with distinct patterns emerging based on the underlying injury mechanism. Using functional magnetic resonance imaging (fMRI), we identify six distinct brain states across severely brain injured patients and healthy controls. These states, when sorted by decreasing entropy, span a continuum from state 1, characterized by high entropy, widespread positive long-distance coordination, and high global connectivity, predominantly observed in healthy controls, to state 6, which exhibits low entropy and minimal functional connectivity, and is predominantly associated with acute DoC. We demonstrate that the probability of occurrence of the more complex brain state correlates with improved neurological recovery at 3 months, as assessed by the Coma Recovery Scale–Revised (CRS-R). Hence, we were able to train a classifier based on brain state dynamics that achieved an accuracy of 78.5% in predicting patients' recovery potential (AUC = 0.864). Overall, our findings suggest that dynamic brain connectivity, particularly the entropy of brain states, can be a reliable early predictor of recovery from acute DoC, bridging the divide between theoretical advances and bedside medical decision-making.
publishDate 2026
dc.date.none.fl_str_mv 2026-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/289310
Della Bella, Gabriel Alejandro; Sarton, Benjamine; Mattia, Giulia Maria; Peran, Patrice; Lamberti, Pedro Walter; et al.; Brain dynamic organization at the acute stage of severe brain injury; Elsevier; Journal Neuroimag; 325; 1-2026; 1-8
1053-8119
CONICET Digital
CONICET
url http://hdl.handle.net/11336/289310
identifier_str_mv Della Bella, Gabriel Alejandro; Sarton, Benjamine; Mattia, Giulia Maria; Peran, Patrice; Lamberti, Pedro Walter; et al.; Brain dynamic organization at the acute stage of severe brain injury; Elsevier; Journal Neuroimag; 325; 1-2026; 1-8
1053-8119
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S1053811925006603
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.neuroimage.2025.121657
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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