Name
Abstract | ||
|---|---|---|
In a previous study, we calculated the resolution obtained by a population of overlapping receptive fields, as- suming a coarse coding mechanism. The results, which fa- vor large receptive fields, are applied to the visual system of tongue-projecting salamanders. An analytical calculation gives the number of neurons necessary to determine the di- rection of their prey. Direction localization and distance de- termination are studied in neural network simulations of the orienting movement and the tongue projection, respectively. In all cases, large receptive fields are found to be essential to yield a high sensory resolution. The results are in good agreement with anatomical, electrophysiological and behav- ioral data. sitions and sizes of receptive fields of neurons in the op- tic tectum of the tongue-projecting salamander Hydromantes italicus. In Sect. 3, the resolving capability of large recep- tive fields for direction determination is tested with a neural network model called Simulander I which tracks prey with head movements. Since the model has been described in de- tail elsewhere (Eurich et al. 1995), it is evaluated only with respect to its coarse coding properties. In Sect. 4, a coarse coding scheme for depth perception is developed comprised of large, overlapping three-dimensional receptive fields in the binocular visual field. The scheme is implemented in Simulander II, which is a neural network model for the con- trol of the projectile tongue of salamanders. The results are discussed in Sect. 5, where we also address the question of the coding and decoding of information in the nervous system and the problem of relating special tasks to certain neurons in distributed information-processing systems. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1007/s004220050365 | Biological Cybernetics |
Keywords | Field | DocType |
Neural Network,Visual System,Receptive Field,Analytical Calculation,Behavioral Data | Receptive field,Population,Surround suppression,Computer science,Coding (social sciences),Behavioral data,Artificial intelligence,Artificial neural network,Sensory system,Machine learning | Journal |
Volume | Issue | ISSN |
77 | 1 | 0340-1200 |
Citations | PageRank | References |
2 | 1.31 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian W. Eurich | 1 | 103 | 22.51 |
| Helmut Schwegler | 2 | 46 | 16.45 |
| R Woesler | 3 | 36 | 8.24 |