Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2007. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Includes bibliographical references (p. 162-170). / To achieve any motor behavior, the central nervous system (CNS) must coordinate the many degrees of freedom in the musculoskeletal apparatus. It has been suggested that the CNS simplifies this formidable task of coordination by grouping multiple muscles together into units of activation, or muscle synergies. Previous studies have shown that electromyogram (EMG) signals collected from many muscles during natural behaviors can be reconstructed by linearly combining a few synergies, identified by the non-negative matrix factorization algorithm. But to what extent synergies are neural constraints, or merely structures reflecting experimental constraints, has remained an open question. I address this question with the hypothesis that, muscle synergies are robust neural patterns constraining motor outputs. The strategy adopted was that of analyzing EMGs collected before and after delivery of a perturbation to the motor system. In my first experiment, EMGs from bullfrog muscles were recorded during locomotor behaviors before and after deafferentation. Systematic comparison of intact and deafferented synergies suggests that most of the synergies remained unchanged after afferent removal. / (cont.) In my second experiment, the frog hindlimb was perturbed by either an inertial load or an elastic load. Using a novel algorithm capable of simultaneously extracting shared and specific synergies, I demonstrate that, most synergies were shared between the different conditions, but their activation patterns were reversibly altered by loading. Overall, my results suggest that muscle synergies are robust, centrally organized structures, and descending and afferent signals cooperate in modulating their activations so that the resulting motor commands can be efficiently adapted to the external environment. / by Vincent Chi-Kwan Cheung. / Ph.D.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/38519 |
| Date | January 2007 |
| Creators | Cheung, Vincent Chi-Kwan |
| Contributors | Emilio Bizzi., Harvard University--MIT Division of Health Sciences and Technology., Harvard University--MIT Division of Health Sciences and Technology. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 170 p., application/pdf |
| Rights | M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission., http://dspace.mit.edu/handle/1721.1/7582 |
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