Citation
Horiuchi, Timothy Ken (1997) Analog VLSI-Based, Neuromorphic Sensorimotor Systems: Modeling the Primate Oculomotor System. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/nbm7-1361. https://resolver.caltech.edu/CaltechTHESIS:04092013-113114781
Abstract
Using neuromorphic analog VLSI techniques for modeling large neural systems has several advantages over software techniques. By designing massively-parallel analog circuit arrays which are ubiquitous in neural systems, analog VLSI models are extremely fast, particularly when local interactions are important in the computation. While analog VLSI circuits are not as flexible as software methods, the constraints posed by this approach are often very similar to the constraints faced by biological systems. As a result, these constraints can offer many insights into the solutions found by evolution. This dissertation describes a hardware modeling effort to mimic the primate oculomotor system which requires both fast sensory processing and fast motor control. A one-dimensional hardware model of the primate eye has been built which simulates the physical dynamics of the biological system. It is driven by analog VLSI circuits mimicking brainstem and cortical circuits that control eye movements. In this framework, a visually-triggered saccadic system is demonstrated which generates averaging saccades. In addition, an auditory localization system, based on the neural circuits of the barn owl, is used to trigger saccades to acoustic targets in parallel with visual targets. Two different types of learning are also demonstrated on the saccadic system using floating-gate technology allowing the non-volatile storage of analog parameters directly on the chip. Finally, a model of visual attention is used to select and track moving targets against textured backgrounds, driving both saccadic and smooth pursuit eye movements to maintain the image of the target in the center of the field of view. This system represents one of the few efforts in this field to integrate both neuromorphic sensory processing and motor control in a closed-loop fashion.
Item Type: | Thesis (Dissertation (Ph.D.)) |
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Subject Keywords: | Computation and Neural Systems |
Degree Grantor: | California Institute of Technology |
Division: | Engineering and Applied Science |
Major Option: | Computation and Neural Systems |
Thesis Availability: | Public (worldwide access) |
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Thesis Committee: |
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Defense Date: | 28 February 1997 |
Record Number: | CaltechTHESIS:04092013-113114781 |
Persistent URL: | https://resolver.caltech.edu/CaltechTHESIS:04092013-113114781 |
DOI: | 10.7907/nbm7-1361 |
Default Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. |
ID Code: | 7596 |
Collection: | CaltechTHESIS |
Deposited By: | Benjamin Perez |
Deposited On: | 10 Apr 2013 15:52 |
Last Modified: | 31 Aug 2022 00:11 |
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