Multimodal and multidomain lesion network mapping enhances prediction of sensorimotor behavior in stroke patients.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
27 12 2022
Historique:
received: 10 05 2022
accepted: 22 12 2022
entrez: 27 12 2022
pubmed: 28 12 2022
medline: 30 12 2022
Statut: epublish

Résumé

Beyond the characteristics of a brain lesion, such as its etiology, size or location, lesion network mapping (LNM) has shown that similar symptoms after a lesion reflects similar dis-connectivity patterns, thereby linking symptoms to brain networks. Here, we extend LNM by using a multimodal strategy, combining functional and structural networks from 1000 healthy participants in the Human Connectome Project. We apply multimodal LNM to a cohort of 54 stroke patients with the aim of predicting sensorimotor behavior, as assessed through a combination of motor and sensory tests. Results are two-fold. First, multimodal LNM reveals that the functional modality contributes more than the structural one in the prediction of sensorimotor behavior. Second, when looking at each modality individually, the performance of the structural networks strongly depended on whether sensorimotor performance was corrected for lesion size, thereby eliminating the effect that larger lesions generally produce more severe sensorimotor impairment. In contrast, functional networks provided similar performance regardless of whether or not the effect of lesion size was removed. Overall, these results support the extension of LNM to its multimodal form, highlighting the synergistic and additive nature of different types of network modalities, and their corresponding influence on behavioral performance after brain injury.

Identifiants

pubmed: 36575263
doi: 10.1038/s41598-022-26945-x
pii: 10.1038/s41598-022-26945-x
pmc: PMC9794717
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

22400

Informations de copyright

© 2022. The Author(s).

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Auteurs

Antonio Jimenez-Marin (A)

Computational Neuroimaging Group, Biocruces-Bizkaia Health Research Institute, Biocruces Bizkaia, Plaza de Cruces S/N, 48903, Barakaldo, Spain.
Biomedical Research Doctorate Program, University of the Basque Country (UPV/EHU), Leioa, Spain.

Nele De Bruyn (N)

Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium.

Jolien Gooijers (J)

Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven, Belgium.
LBI-KU Leuven Brain Institute, Leuven, Belgium.

Alberto Llera (A)

Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands.
Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands.
LIS Data Solutions, Machine Learning Group, Santander, Spain.

Sarah Meyer (S)

Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium.

Kaat Alaerts (K)

Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium.

Geert Verheyden (G)

Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium.

Stephan P Swinnen (SP)

Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven, Belgium.
LBI-KU Leuven Brain Institute, Leuven, Belgium.

Jesus M Cortes (JM)

Computational Neuroimaging Group, Biocruces-Bizkaia Health Research Institute, Biocruces Bizkaia, Plaza de Cruces S/N, 48903, Barakaldo, Spain. jesus.m.cortes@gmail.com.
Cell Biology and Histology Department, University of the Basque Country (UPV/EHU), Leioa, Spain. jesus.m.cortes@gmail.com.
IKERBASQUE, The Basque Foundation for Science, Bilbao, Spain. jesus.m.cortes@gmail.com.

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