Book contents
- Frontmatter
- Contents
- List of contributors
- Preface
- Neurons and neural networks: general principles
- Synaptic plasticity, topological and temporal features, and higher cortical processing
- Spin glass models and cellular automata
- Cyclic phenomena and chaos in neural networks
- The cerebellum and the hippocampus
- Olfaction, vision and cognition
- 26 Neural computations and neural systems
- 27 Development of feature-analyzing cells and their columnar organization in a layered self-adaptive network
- 28 Reafferent stimulation: a mechanism for late vision and cognitive processes
- 29 Mathematical model and computer simulation of visual recognition in retina and tectum opticum of amphibians
- 30 Pattern recognition with modifiable neuronal interactions
- 31 Texture description in the time domain
- Applications to experiment, communication and control
- Author index
- Subject index
29 - Mathematical model and computer simulation of visual recognition in retina and tectum opticum of amphibians
from Olfaction, vision and cognition
Published online by Cambridge University Press: 05 February 2012
- Frontmatter
- Contents
- List of contributors
- Preface
- Neurons and neural networks: general principles
- Synaptic plasticity, topological and temporal features, and higher cortical processing
- Spin glass models and cellular automata
- Cyclic phenomena and chaos in neural networks
- The cerebellum and the hippocampus
- Olfaction, vision and cognition
- 26 Neural computations and neural systems
- 27 Development of feature-analyzing cells and their columnar organization in a layered self-adaptive network
- 28 Reafferent stimulation: a mechanism for late vision and cognitive processes
- 29 Mathematical model and computer simulation of visual recognition in retina and tectum opticum of amphibians
- 30 Pattern recognition with modifiable neuronal interactions
- 31 Texture description in the time domain
- Applications to experiment, communication and control
- Author index
- Subject index
Summary
The retina
Mathematical model of amphibian retina
The retina is composed of a variety of cell types including the photoreceptors, horizontal cells, bipolar cells, amacrine cells, and retina ganglion cells (for a review see Grüsser & Grüsser-Cornehls, 1976). Only the retina ganglion cells (RGCs) send axons to the brain of the animals. Therefore any visual information the brain may rely on is mediated by cells of this type.
According to their response properties the RGCs are usually divided into four classes, which here for simplicity are called R1, R2, R3, and R4. We have restricted our attention to the classes R2 and R3 because these form the majority (about 93%) of cells projecting to the tectum opticum, which is that area in the brain where recognition of prey objects is supposed to be centered.
The recognition process starts in the retina. The overall operation of the ganglion cells (R2, R3) and their precursors (photoreceptors, etc.) on some arbitrary visual scene can be decomposed into the following more primitive operational components:
(1) Let x(s, t) be any distribution of light in the visual field, where x denotes light intensity (we do not consider colored scenes), s = (s1, s2) some point in the visual field, and t is time.
(2) These ganglion cells do not respond to stationary, but only to transitory, illumination.
- Type
- Chapter
- Information
- Computer Simulation in Brain Science , pp. 455 - 468Publisher: Cambridge University PressPrint publication year: 1988