Moving in on human motor cortex. Characterizing the relationship between body parts with non-rigid population response fields

Publication date

2022-04

Authors

Schellekens, W
Bakker, Carlijn
Ramsey, Nick F.ORCID 0000-0002-7136-259XISNI 0000000399572879
Petridou, NataliaORCID 0000-0002-0783-0387ISNI 0000000392331001

Editors

Advisors

Supervisors

Document Type

Article

Collections

Open Access logo

License

cc_by

Abstract

For cortical motor activity, the relationships between different body part representations is unknown. Through reciprocal body part relationships, functionality of cortical motor areas with respect to whole body motor control can be characterized. In the current study, we investigate the relationship between body part representations within individual neuronal populations in motor cortices, following a 7 Tesla fMRI 18-body-part motor experiment in combination with our newly developed non-rigid population Response Field (pRF) model and graph theory. The non-rigid pRF metrics reveal somatotopic structures in all included motor cortices covering frontal, parietal, medial and insular cortices and that neuronal populations in primary sensorimotor cortex respond to fewer body parts than secondary motor cortices. Reciprocal body part relationships are estimated in terms of uniqueness, clique-formation, and influence. We report unique response profiles for the knee, a clique of body parts surrounding the ring finger, and a central role for the shoulder and wrist. These results reveal associations among body parts from the perspective of the central nervous system, while being in agreement with intuitive notions of body part usage.

Keywords

Genetics, Ecology, Evolution, Behavior and Systematics, Cellular and Molecular Neuroscience, Molecular Biology, Ecology, Computational Theory and Mathematics, Modelling and Simulation, Journal Article

Citation

Schellekens, W, Bakker, C, Ramsey, N F & Petridou, N 2022, 'Moving in on human motor cortex. Characterizing the relationship between body parts with non-rigid population response fields', PLoS Computational Biology, vol. 18, no. 4, e1009955, pp. 1-31. https://doi.org/10.1371/journal.pcbi.1009955