Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling.

Détails

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Etat: Public
Version: de l'auteur
ID Serval
serval:BIB_13392BAF89C6
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling.
Périodique
Plos Computational Biology
Auteur(s)
Ponce-Alvarez A., He B.J., Hagmann P., Deco G.
ISSN
1553-7358 (Electronic)
ISSN-L
1553-734X
Statut éditorial
Publié
Date de publication
2015
Peer-reviewed
Oui
Volume
11
Numéro
8
Pages
e1004445
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, N.I.H., Intramural ; Research Support, Non-U.S. Gov't Publication Status: epublish
Résumé
How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model's prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information.
Mots-clé
Adolescent, Adult, Cerebral Cortex/physiology, Computational Biology/methods, Entropy, Female, Humans, Magnetic Resonance Imaging/methods, Male, Models, Neurological, Rest/physiology, Task Performance and Analysis, Young Adult
Pubmed
Web of science
Open Access
Oui
Création de la notice
05/10/2015 13:54
Dernière modification de la notice
20/08/2019 13:41
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