Synaptic learning models of map separation in the hippocampus - Robotics Institute Carnegie Mellon University

Synaptic learning models of map separation in the hippocampus

M. C. Fuhs and David S. Touretzky
Journal Article, Neurocomputing, Vol. 32, pp. 379 - 384, June, 2000

Abstract

When rats trained to forage in one environment are exposed to a second, highly similar environment, their hippocampal place code exhibits a partial remapping in the new environment that becomes more complete with repeated exposures (Shapiro, Tanila, Eichenbaum, Hippocampus 7 (6) (1997) 624–642, Bostock, Muller, Kubie, Hippocampus 1 (2) (1991) 193–206). If the perforant path projection to CA3 functions as a pattern completion mechanism, and the DG projection via the mossy fibers performs pattern separation (O'Reilly, McClelland, Hippocampal conjunctive encoding, storage, and recall: avoiding a trade-off, Hippocampus 4 (6) (1994) 661–682), then partial remapping can be understood as the combined effect of these two projections. We investigated learning rules that could be responsible for the gradual separation of two maps, and found that, while simple Hebbian learning and Hebbian covariance learning would not produce the separation effect, BCM learning was one rule that would.

BibTeX

@article{Fuhs-2000-16748,
author = {M. C. Fuhs and David S. Touretzky},
title = {Synaptic learning models of map separation in the hippocampus},
journal = {Neurocomputing},
year = {2000},
month = {June},
volume = {32},
pages = {379 - 384},
}