Citation
Annau, Thomas Mark (1996) Models of visual feature detection and spike coding in the nervous system. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/CN6R-WE94. https://resolver.caltech.edu/CaltechETD:etd-09212006-152641
Abstract
We propose mathematical models to analyze two nervous system phenomena. The first is a model of the development and function of simple cell receptive fields in mammalian primary visual cortex. The model assumes that images are composed of combinations of a limited set of specific visual features and that the goal of simple cells is to detect the presence or absence of these features. Based on a presumed statistical character of images and their visual features, the model uses a constrained Hebbian learning rule to discover the structure of the features, and thus the appropriate response properties of simple cells, by training on a database of photographs. The response properties of the model simple cells agree qualitatively with neurophysiological observation. The second is a model of the coding of information in the nervous system by the rate of axonal voltage spikes. Assuming an integrate-and-fire mechanism for spike generation, we develop a quantization-based model of rate coding and use it to derive the mathematical relationship between the amplitude and temporal resolution of a rate encoded signal. We elaborate the model to include integrator leak in the spike generation mechanism and show that it compactly combines coding and the computation of a threshold function.
Item Type: | Thesis (Dissertation (Ph.D.)) |
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Degree Grantor: | California Institute of Technology |
Division: | Biology |
Major Option: | Computation and Neural Systems |
Thesis Availability: | Public (worldwide access) |
Research Advisor(s): |
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Defense Date: | 20 May 1996 |
Non-Caltech Author Email: | tom (AT) tomannau.com |
Record Number: | CaltechETD:etd-09212006-152641 |
Persistent URL: | https://resolver.caltech.edu/CaltechETD:etd-09212006-152641 |
DOI: | 10.7907/CN6R-WE94 |
Default Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. |
ID Code: | 3681 |
Collection: | CaltechTHESIS |
Deposited By: | Imported from ETD-db |
Deposited On: | 22 Sep 2006 |
Last Modified: | 27 Aug 2024 22:39 |
Thesis Files
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