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Artículo

Computational modelling in disorders of consciousness: Closing the gap towards personalised models for restoring consciousness

Luppi, Andrea I.; Cabral, Joana; Cofre, Rodrigo; Mediano, Pedro A. M.; Rosas, Fernando E.; Qureshi, Abid Y.; Kuceyeski, Amy; Tagliazucchi, Enzo RodolfoIcon ; Raimondo, FedericoIcon ; Deco, Gustavo; Shine, James M.; Kringelbach, Morten L.; Orio, Patricio; Ching, ShiNung; Sanz Perl Hernandez, YonatanIcon ; Diringer, Michael N.; Stevens, Robert D.; Sitt, Jacobo DiegoIcon
Fecha de publicación: 07/2023
Editorial: Academic Press Inc Elsevier Science
Revista: Journal Neuroimag
ISSN: 1053-8119
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Otras Ciencias Físicas

Resumen

Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma Campaign, here we provide our framework and vision to understand the diverse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state-of-the-art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness; which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges.
Palabras clave: BIOPHYSICAL MODELS , COMPUTATIONAL MODELS , DISORDERS OF CONSCIOUSNESS , GENERATIVE MODELS , MACHINE LEARNING , STATISTICAL MODELS
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info:eu-repo/semantics/restrictedAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/228643
URL: https://www.sciencedirect.com/science/article/pii/S1053811923003130
DOI: http://dx.doi.org/10.1016/j.neuroimage.2023.120162
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Articulos(INFINA)
Articulos de INST.DE FISICA DEL PLASMA
Citación
Luppi, Andrea I.; Cabral, Joana; Cofre, Rodrigo; Mediano, Pedro A. M.; Rosas, Fernando E.; et al.; Computational modelling in disorders of consciousness: Closing the gap towards personalised models for restoring consciousness; Academic Press Inc Elsevier Science; Journal Neuroimag; 275; 120162; 7-2023; 1-16
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