Spatial representations in related environments in a recurrent model of area CA3 of the rat
Spatial representations in related environments in a recurrent model of area CA3 of the rat
- Author(s): S. Kali and P. Dayan
- DOI: 10.1049/cp:19991098
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- Author(s): S. Kali and P. Dayan Source: 9th International Conference on Artificial Neural Networks: ICANN '99, 1999 p. 138 – 143
- Conference: 9th International Conference on Artificial Neural Networks: ICANN '99
- DOI: 10.1049/cp:19991098
- ISBN: 0 85296 721 7
- Location: Edinburgh, UK
- Conference date: 7-10 Sept. 1999
- Format: PDF
Recurrent network models of area CA3 in the hippocampus capture faithfully many of the properties of place cells. However, they seem ill suited to explaining the substantial experimental data on place cells in environments with particular visual or geometrical similarities. We show that a model in which the activities of CA3 place cells are determined mainly by modifiable recurrent connections (together with global inhibitory feedback) is capable of reproducing the major classes of behavior that are observed. In visually similar environments, the patterns of place cell activities have the appropriate degree of similarity; after geometric transformations to the environment, the model place fields undergo geometric transformations, and also remapping, induced (or uncovered) directionality and disappearance.
Inspec keywords: recurrent neural nets; brain models
Subjects: Biology and medical computing; Brain models; Neural computing techniques; Systems theory applications in biology and medicine; General, theoretical, and mathematical biophysics
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