Movement representation in human motor cortex and applications to brain-computer interface control

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Abstract/Contents

Abstract
Intracortical brain-computer interfaces (iBCIs) have largely built upon work investigating the neural representation of overt reaching movements in nonhuman primates (NHPs). However, in people with paralysis, iBCIs leverage neural features related to attempted movement of paralyzed limbs, which may differ substantially from that of overt movement of unparalyzed limbs. To understand how paralysis affects movement representation in the motor cortex, we first compared direction- and distance-related neural tuning of a human participant's attempted arm movements and overt head movements to that of NHP overt arm movements. The participant's neural activity during overt head movement was most similar to NHP overt arm movement with strongest tuning to distance. To further clarify how attempted movement-related neural activity translates into iBCI control, the participant controlled a cursor using a series of different attempted movement strategies. We found that neural activity changes during iBCI control, becoming more similar across different strategies. Applying these gained insights, we designed and demonstrated a discrete neural decoding system which leveraged the neural representation of both overt and attempted movements to enable classification of up to 32 discrete movements across the body. The attempt to move a paralyzed limb also differs from overt movement of an unparalyzed limb in that haptic feedback normally accompanying the movement is lost or diminished. To better understand how haptic stimulation affects motor cortical neurons and iBCI control, we integrated a haptic feedback device into our iBCI system, which provided skin-shear haptic stimulation at the back of the participant's neck. We found motor cortical units that exhibited sensory responses to the stimuli, some of which were significantly tuned to the stimuli and well modeled by cosine-shaped functions. We also demonstrated online iBCI cursor control with continuous skin-shear feedback driven by decoded command signals. Cursor control performance increased slightly but significantly when the participant was given haptic feedback as compared to the visual feedback condition. This work deepens our understanding of how paralysis affects movement representation, delivers a novel discrete neural decoding system leveraging the movement representation of both paralyzed and unparalyzed limbs, provides insight into how motor cortical units respond to haptic stimulation, and shows how this stimulation affects iBCI control performance. These results can help guide and inform the design of future neural prostheses.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2019; ©2019
Publication date 2019; 2019
Issuance monographic
Language English

Creators/Contributors

Author Deo, Darrel Rohit
Degree supervisor Okamura, Allison
Thesis advisor Okamura, Allison
Thesis advisor Follmer, Sean
Thesis advisor Shenoy, Krishna V. (Krishna Vaughn)
Degree committee member Follmer, Sean
Degree committee member Shenoy, Krishna V. (Krishna Vaughn)
Associated with Stanford University, Department of Mechanical Engineering.

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Darrel R. Deo.
Note Submitted to the Department of Mechanical Engineering.
Thesis Thesis Ph.D. Stanford University 2019.
Location electronic resource

Access conditions

Copyright
© 2019 by Darrel Rohit Deo
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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