| Type of Document |
Dissertation |
| Author |
Meeker, Daniella Elena Patricia
|
| URN |
etd-06032005-170438 |
| Persistent URL |
http://resolver.caltech.edu/CaltechETD:etd-06032005-170438 |
| Title |
Cognitive neural prosthetics: brain machine interfaces based in parietal cortex |
| Degree |
PhD |
| Option |
Computation and Neural Systems |
| Advisory Committee |
| Advisor Name |
Title |
| Joel Wakeman Burdick |
Committee Chair |
| Masakazu Konishi |
Committee Member |
| Pietro Perona |
Committee Member |
| Richard Andersen |
Committee Member |
| Shinsuke Shimojo |
Committee Member |
|
| Keywords |
- neural prosthetics
- plasticity
- parietal cortex
- cognitive neuroscience
|
| Date of Defense |
2005-02-21 |
| Availability |
unrestricted |
Abstract
Systems neuroscience has recently emerged as an applied field in the form of neural prosthetic development. This integration of empirical systems neuroscience with engineering in order to develop functional interfaces between external devices and the brain has not only been beneficial in its applied goal, but has resulted in observations of scientific interest. The body of work presented here demonstrates the efficacy of two varieties of brain machine interfaces (BMIs) based in Parietal Cortex. The first using information about intended reaches present in action potentials, the second using local field potentials (LFPs). Both studies were predicated and succeeded with offline analyses demonstrating feasibility and novel insight to the function and neural coding properties of Parietal Cortex. We found that using BMIs resulted in adaptive change which tended to improve performance. LFPs, though less successful than spikes for BMI control under these experimental conditions, appear to have a multiplexing of different types of information that might aid in BMIs as well as providing a different way of looking at the neural processing. A preliminary exploration of relative timing of spikes and LFPs might result in some of the adaptive properties observed during BMI use via spike timing dependent plasticity concludes the research presented here.
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ISDN (64 Kb) |
ISDN (128 Kb) |
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final.pdf |
1.38 Mb |
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