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Compartmentalized dynamics within a common multi-area mesoscale manifold represent a repertoire of human hand movements

Neuron. 2022 Jan 5;110(1):154-174.e12. doi: 10.1016/j.neuron.2021.10.002. | PubMed

Nikhilesh Natraj1, Daniel B Silversmith2, Edward F Chang3, Karunesh Ganguly4

  1. Department of Neurology, Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA; Neurology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA. Electronic address: nikhilesh.natraj@ucsf.edu.
  2. Department of Neurology, Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA; Neurology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA.
  3. Department of Neurosurgery, University of California, San Francisco, San Francisco, CA, USA.
  4. Department of Neurology, Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA; Neurology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA. Electronic address: karunesh.ganguly@ucsf.edu.

Abstract

The human hand is unique in the animal kingdom for unparalleled dexterity, ranging from complex prehension to fine finger individuation. How does the brain represent such a diverse repertoire of movements? We evaluated mesoscale neural dynamics across the human "grasp network," using electrocorticography and dimensionality reduction methods, for a repertoire of hand movements. Strikingly, we found that the grasp network represented both finger and grasping movements alike. Specifically, the manifold characterizing the multi-areal neural covariance structure was preserved during all movements across this distributed network. In contrast, latent neural dynamics within this manifold were surprisingly specific to movement type. Aligning latent activity to kinematics further uncovered distinct submanifolds despite similarities in synergistic coupling of joints between movements. We thus find that despite preserved neural covariance at the distributed network level, mesoscale dynamics are compartmentalized into movement-specific submanifolds; this mesoscale organization may allow flexible switching between a repertoire of hand movements.

Presented By Nikhilesh Natraj | ORCID iD