Computational Differences Between
Asymmetrical and Symmetrical Networks.
Zhaoping Li Peter Dayan
In NIPS 11.
Abstract
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.
compressed postscript pdf