Mapping grip force to motor networks.

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State: Public
Version: Final published version
License: CC BY-NC-ND 4.0
Serval ID
serval:BIB_9A913C074FDF
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Mapping grip force to motor networks.
Journal
NeuroImage
Author(s)
Weitnauer L., Frisch S., Melie-Garcia L., Preisig M., Schroeter M.L., Sajfutdinow I., Kherif F., Draganski B.
ISSN
1095-9572 (Electronic)
ISSN-L
1053-8119
Publication state
Published
Issued date
01/04/2021
Peer-reviewed
Oui
Volume
229
Pages
117735
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Abstract
There is ongoing debate about the role of cortical and subcortical brain areas in force modulation. In a whole-brain approach, we sought to investigate the anatomical basis of grip force whilst acknowledging interindividual differences in connectivity patterns. We tested if brain lesion mapping in patients with unilateral motor deficits can inform whole-brain structural connectivity analysis in healthy controls to uncover the networks underlying grip force.
Using magnetic resonance imaging (MRI) and whole-brain voxel-based morphometry in chronic stroke patients (n=55) and healthy controls (n=67), we identified the brain regions in both grey and white matter significantly associated with grip force strength. The resulting statistical parametric maps (SPMs) provided seed areas for whole-brain structural covariance analysis in a large-scale community dwelling cohort (n=977) that included beyond volume estimates, parameter maps sensitive to myelin, iron and tissue water content.
The SPMs showed symmetrical bilateral clusters of correlation between upper limb motor performance, basal ganglia, posterior insula and cortico-spinal tract. The covariance analysis with the seed areas derived from the SPMs demonstrated a widespread anatomical pattern of brain volume and tissue properties, including both cortical, subcortical nodes of motor networks and sensorimotor areas projections.
We interpret our covariance findings as a biological signature of brain networks implicated in grip force. The data-driven definition of seed areas obtained from chronic stroke patients showed overlapping structural covariance patterns within cortico-subcortical motor networks across different tissue property estimates. This cumulative evidence lends face validity of our findings and their biological plausibility.
Keywords
Brain lesion, Grip force, Magnetic resonance imaging, Multi-parameter mapping, Relaxometry, Stroke, Structural covariance, Voxel-based morphometry, Voxel-based quantification
Pubmed
Web of science
Open Access
Yes
Create date
26/01/2021 15:06
Last modification date
24/04/2021 6:33
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