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学術論文

Mapping grip force to motor networks

MPS-Authors
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Frisch,  Stefan
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Department of Gerontopsychiatry, Psychosomatic Medicine, and Psychotherapy, Pfalzklinikum, Klingenmünster, Germany;
Department of Psychology, Goethe University, Frankfurt, Germany;

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Schroeter,  Matthias L.
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

/persons/resource/persons19617

Draganski,  Bogdan
Laboratoire de Recherche en Neuroimagerie (LREN), Centre hospitalier universitaire vaudois, Lausanne, Switzerland;
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Weitnauer_2021.pdf
(出版社版), 2MB

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引用

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


引用: https://hdl.handle.net/21.11116/0000-0008-0CFB-1
要旨
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.