Low-dimensional neural features reflect central features of muscle activation

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Abstract/Contents

Abstract
Any time we move, our brains solve the difficult problem of translating our motor intentions to muscle commands. Understanding how this computation takes place, and in particular, what role the motor cortex plays in movement generation, has been a central issue in systems neuroscience that remains unresolved. In this thesis, we took an unconventional approach to the analysis of cortical neural activity and its relationship to executed movements. We used dimensionality reduction to extract the salient patterns of neural population activity, and related those to the muscle activity patterns generated during arm reaches to a grid of targets. We found that salient neural activity patterns appeared to tightly reflect muscle activity patterns with a biologically-plausible lag. We also applied our analyses to movements that were planned before being executed, and found that a muscle-framework view of the cortical activity was consistent with previously-described predictions of movement kinematics based on the state of the cortical population activity. Overall, our results elucidate remarkable simplicity of the motor-cortical activity at the population level, despite the complexity and heterogeneity of individual cell's activities.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2011
Issuance monographic
Language English

Creators/Contributors

Associated with Rivera Alvidrez, Zuley
Associated with Stanford University, Department of Electrical Engineering
Primary advisor Shenoy, Krishna V. (Krishna Vaughn)
Thesis advisor Shenoy, Krishna V. (Krishna Vaughn)
Thesis advisor Newsome, William T
Thesis advisor Ng, Andrew Y, 1976-
Advisor Newsome, William T
Advisor Ng, Andrew Y, 1976-

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Zuley Rivera Alvidrez.
Note Submitted to the Department of Electrical Engineering.
Thesis Thesis (Ph.D.)--Stanford University, 2011.
Location electronic resource

Access conditions

Copyright
© 2011 by Zuley Rivera Alvidrez
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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