Intrinsic dynamics and topography of sensory input systems.
criticality
entropy
input processing
power-law
scale-free
Journal
Cerebral cortex (New York, N.Y. : 1991)
ISSN: 1460-2199
Titre abrégé: Cereb Cortex
Pays: United States
ID NLM: 9110718
Informations de publication
Date de publication:
08 10 2022
08 10 2022
Historique:
received:
13
10
2021
revised:
07
12
2021
accepted:
08
12
2021
pubmed:
31
1
2022
medline:
19
10
2022
entrez:
30
1
2022
Statut:
ppublish
Résumé
The brain is continuously bombarded by external stimuli, which are processed in different input systems. The intrinsic features of these sensory input systems remain yet unclear. Investigating topography and dynamics of input systems is the goal of our study in order to better understand the intrinsic features that shape their neural processing. Using a functional magnetic resonance imaging dataset, we measured neural topography and dynamics of the input systems during rest and task states. Neural dynamics were probed by scale-free activity, measured with the power-law exponent (PLE), as well as by order/disorder as measured with sample entropy (SampEn). Our main findings during both rest and task states are: 1) differences in neural dynamics (PLE, SampEn) between regions within each of the three sensory input systems 2) differences in topography and dynamics among the three input systems; 3) PLE and SampEn correlate and, as demonstrated in simulation, show non-linear relationship in the critical range of PLE; 4) scale-free activity during rest mediates the transition of SampEn from rest to task as probed in a mediation model. We conclude that the sensory input systems are characterized by their intrinsic topographic and dynamic organization which, through scale-free activity, modulates their input processing.
Identifiants
pubmed: 35094077
pii: 6517436
doi: 10.1093/cercor/bhab504
pmc: PMC9614113
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4592-4604Informations de copyright
© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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