Conference proceeding
Modeling and investigation of some spatio-temporal aspects of visual information processing in the retinal neural network
Proceedings of SPIE, v 2430(1), pp 100-109
07 Dec 1994
Abstract
A simplified retinal neural network (RNN) model has been considered. The main properties of this model are as follows: (1) primary transform of input raster simulates a decrease of resolution from the fovea to the retinal periphery; (2) the RNN consists of two layers, i.e., excitatory and inhibitory ones, each of them being formed by elements with identical properties excluding input transform; (3) each element of the excitatory layer is inhibited by the retinotopically corresponding element of the inhibitory layer; and (4) receptive field size and time constant of inhibitory neurons are more than those of excitatory ones. Two versions of the RNN differing in several aspects from each other were developed. In the first model the Gauss transform was used as a primary transform of the input raster. In addition, a wide range of the RNN and visual stimulus parameters was tested by computer simulation. The primary transform in the second model was performed by brightness averaging on neuron receptive fields. In the last case, qualitative behavior of the RNN was studied analytically. It was shown that neuron dynamics in response to moving stimuli and the preferable velocity of motion depended on neuron position in the RNN. In particular, foveal neurons were tuned to lower velocity as compared with peripheral ones.
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Details
- Title
- Modeling and investigation of some spatio-temporal aspects of visual information processing in the retinal neural network
- Creators
- Alain Faure - University of Le HavreIlya A Rybak - University of PennsylvaniaNatalia A Shevtsova - Southern Federal UniversityAlexander V Golovan - Southern Federal UniversityOlga Cachard - University of Le HavreValentina I Gusakova - Southern Federal UniversityLubov N Podladchikova - Southern Federal UniversityArkadi A Klepatch - Southern Federal University
- Publication Details
- Proceedings of SPIE, v 2430(1), pp 100-109
- Conference
- Optical Memory & Neural Networks '94: Optical Neural Networks (1994)
- Publisher
- Society of Photo-Optical Instrumentation Engineers (SPIE)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Neurobiology and Anatomy
- Web of Science ID
- WOS:A1994BC05A00012
- Scopus ID
- 2-s2.0-0028747330
- Other Identifier
- 991019231639704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Optics