Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.

Détails

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Etat: Public
Version: Final published version
Licence: Non spécifiée
ID Serval
serval:BIB_A3CDEE3FC2CD
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.
Périodique
Brain : a journal of neurology
Auteur⸱e⸱s
Adhikari M.H., Hacker C.D., Siegel J.S., Griffa A., Hagmann P., Deco G., Corbetta M.
ISSN
1460-2156 (Electronic)
ISSN-L
0006-8950
Statut éditorial
Publié
Date de publication
01/04/2017
Peer-reviewed
Oui
Volume
140
Numéro
4
Pages
1068-1085
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to represent stimuli and task states, and that information capacity measured through whole brain models is a theory-driven measure of processing capacity that could be used as a biomarker of injury for outcome prediction or target for rehabilitation intervention.
Mots-clé
Adult, Brain/diagnostic imaging, Brain Mapping, Cognition Disorders/diagnostic imaging, Cognition Disorders/etiology, Cognition Disorders/psychology, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Mental Processes, Models, Neurological, Nerve Net/diagnostic imaging, Neuropsychological Tests, Prospective Studies, Rest, Stroke/diagnostic imaging, Stroke/psychology, Stroke Rehabilitation
Pubmed
Open Access
Oui
Création de la notice
31/03/2017 14:22
Dernière modification de la notice
14/07/2023 6:54
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