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  Mapping grip force to motor networks

Weitnauer, L., Frisch, S., Melie-Garcia, L., Preisig, M., Schroeter, M. L., Sajfutdinow, I., et al. (2021). Mapping grip force to motor networks. NeuroImage, 229: 117735. doi:10.1016/j.neuroimage.2021.117735.

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 Creators:
Weitnauer, Ladina1, Author
Frisch, Stefan2, 3, 4, Author           
Melie-Garcia, Lester1, Author
Preisig, Martin5, Author
Schroeter, Matthias L.2, Author           
Sajfutdinow, Ines6, Author
Kherif, Ferath1, Author
Draganski, Bogdan1, 2, Author           
Affiliations:
1Laboratoire de Recherche en Neuroimagerie (LREN), Centre hospitalier universitaire vaudois, Lausanne, Switzerland, ou_persistent22              
2Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
3Department of Gerontopsychiatry, Psychosomatic Medicine, and Psychotherapy, Pfalzklinikum, Klingenmünster, Germany, ou_persistent22              
4Department of Psychology, Goethe University, Frankfurt, Germany, ou_persistent22              
5Department of Psychiatry, Centre hospitalier universitaire vaudois, Lausanne, Switzerland, ou_persistent22              
6Clinic for Cognitive Neurology, University of Leipzig, Germany, ou_persistent22              

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Free keywords: Stroke; Brain lesion; Magnetic resonance imaging; Voxel-based morphometry; Voxel-based quantification; Grip force; Structural covariance; Relaxometry; Multi-parameter mapping
 Abstract: Aim



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.

Methods

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.

Results

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.

Conclusion

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.

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Language(s): eng - English
 Dates: 2020-12-302020-10-222021-01-042021-01-142021-04-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.neuroimage.2021.117735
Other: epub 2021
PMID: 33454401
 Degree: -

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Project name : -
Grant ID : 32003B_135679; 32003B_159780; 324730_192755; CRSK-3_190185; 3200B0_105993; 3200B0_118308; 33CSCO_122661; 33CS30_139468; 33CS30_14840
Funding program : -
Funding organization : Swiss National Science Foundation (SNSF)
Project name : H2020-EU Morphemic project
Grant ID : 871643
Funding program : -
Funding organization : European Union

Source 1

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 229 Sequence Number: 117735 Start / End Page: - Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166