Rapid Learning of Spatial Representations for Goal-Directed Navigation Based on a Novel Model of Hippocampal Place Fields

• URL: http://arxiv.org/abs/2206.02249v2
• Date: Tue, 7 Jun 2022 13:19:40 GMT
• Title: Rapid Learning of Spatial Representations for Goal-Directed Navigation Based on a Novel Model of Hippocampal Place Fields
• Authors: Adedapo Alabi, Dieter Vanderelst and Ali Minai
• Abstract summary: We develop a self-organized model incorporating place cells and replay. We demonstrate its utility for rapid one-shot learning in non-trivial environments with obstacles.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The discovery of place cells and other spatially modulated neurons in the hippocampal complex of rodents has been crucial to elucidating the neural basis of spatial cognition. More recently, the replay of neural sequences encoding previously experienced trajectories has been observed during consummatory behavior potentially with implications for quick memory consolidation and behavioral planning. Several promising models for robotic navigation and reinforcement learning have been proposed based on these and previous findings. Most of these models, however, use carefully engineered neural networks and are tested in simple environments. In this paper, we develop a self-organized model incorporating place cells and replay, and demonstrate its utility for rapid one-shot learning in non-trivial environments with obstacles.

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