Electrophysiological signatures of resting state networks predict cognitive deficits in stroke.


Journal

Cortex; a journal devoted to the study of the nervous system and behavior
ISSN: 1973-8102
Titre abrégé: Cortex
Pays: Italy
ID NLM: 0100725

Informations de publication

Date de publication:
05 2021
Historique:
received: 21 03 2020
revised: 28 09 2020
accepted: 29 01 2021
pubmed: 8 3 2021
medline: 10 7 2021
entrez: 7 3 2021
Statut: ppublish

Résumé

Localized damage to different brain regions can cause specific cognitive deficits. However, stroke lesions can also induce modifications in the functional connectivity of intrinsic brain networks, which could be responsible for the behavioral impairment. Though resting state networks (RSNs) are typically mapped using fMRI, it has been recently shown that they can also be detected from high-density EEG. We build on a state-of-the-art approach to extract RSNs from 64-channels EEG activity in a group of right stroke patients and to identify neural predictors of their cognitive performance. Fourteen RSNs previously found in fMRI and high-density EEG studies on healthy participants were successfully reconstructed from our patients' EEG recordings. We then correlated EEG-RSNs functional connectivity with neuropsychological scores, first considering a wide frequency band (1-80 Hz) and then specific frequency ranges in order to examine the association between each EEG rhythm and the behavioral impairment. We found that visuo-spatial and motor impairments were primarily associated with the dorsal attention network, with contribution dependent on the specific EEG band. These findings are in line with the hypothesis that there is a core system of brain networks involved in specific cognitive domains. Moreover, our results pave the way for low-cost EEG-based monitoring of intrinsic brain networks' functioning in neurological patients to complement clinical-behavioral measures.

Identifiants

pubmed: 33677328
pii: S0010-9452(21)00054-X
doi: 10.1016/j.cortex.2021.01.019
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

59-71

Informations de copyright

Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors report no competing interests.

Auteurs

Zaira Romeo (Z)

IRCCS San Camillo Hospital, Venice, Italy.

Dante Mantini (D)

IRCCS San Camillo Hospital, Venice, Italy; Laboratory of Movement Control and Neuroplasticity, Department of Movement Sciences, KU Leuven, Belgium.

Eugenia Durgoni (E)

IRCCS San Camillo Hospital, Venice, Italy.

Laura Passarini (L)

IRCCS San Camillo Hospital, Venice, Italy.

Francesca Meneghello (F)

IRCCS San Camillo Hospital, Venice, Italy.

Marco Zorzi (M)

IRCCS San Camillo Hospital, Venice, Italy; Department of General Psychology and Padova Neuroscience Center, University of Padova, Italy. Electronic address: marco.zorzi@unipd.it.

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