Linear control model of the spinal processing of descending neural signals
Author(s)
Cajigas González, Iahn, 1980-![Thumbnail](/bitstream/handle/1721.1/28476/57136934-MIT.pdf.jpg?sequence=5&isAllowed=y)
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Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Steve G. Massaquoi.
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This thesis develops a physiological-control model of the spinal processing of descending neural kinematic motor control signals in the bullfrog (Rana Catesbeiana). The model encompasses the full nonlinear skeletal dynamics of the femur/tibiofibula/tarsus system in the horizontal plane, its muscles, and spinal monosynaptic stretch reflexes. In addition, it incorporates recent findings of muscle synergies encoded within the spinal cord and demonstrates that these muscle synergies can be reorganized into a set of Kinematic Control Synergies (KCS), which have simple, orthogonal kinematic functions. Activating these KCS with simple pulse-like signals allows for the formation of a wide range of behaviors. It is hypothesized that such signals might come from higher-level Central Nervous System (CNS) structures such as the brainstem or cerebellum. Furthermore, KCS present a simple mechanism whereby sensory information could be used by spinal interneurons to recruit the muscle groups required to correct limb movement in real-time, or to learn the correct combination of muscle groups required to perform a movement correctly. Lastly, the experimental findings of convergent, position-invariant ankle force fields observed in the frog are discussed in light of the muscle synergies encoded within the spinal cord and KCS. It is concluded that the control of ankle movement using linear combinations of KCS-derived ankle force fields, may be equivalent to movement control via linear combinations of convergent, position-invariant ankle force fields. Further research, however, is required to concretely establish their equivalence.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003. Includes bibliographical references (p. 135-139).
Date issued
2003Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.