Summary
2023
Session Number:B4L-3
Session:
Number:B4L-35
Memory State Evaluation of Spatio-Temporal Contextual Learning Memory Network Based on Output Spike Rate
Orima Takemori, Tsuji Takeru, Horio Yoshihiko, Moriya Satoshi, Sato Shigeo,
pp.378-381
Publication Date:2023-09-21
Online ISSN:2188-5079
Summary:
The spatio-temporal contextual learning memory network model was proposed as a hippocampal memory model. This model has spatio-temporal learning rule synapses and Hebbian learning rule synapses, and is able to embed spatio-temporal information into the synaptic weight space in the network as memory. However, no method has been proposed to evaluate embedded memory by using the output of the network. Therefore, we propose a method to confirm the embedding of memory based on the output spike rate. In this paper, we construct an extended spatio-temporal contextual learning memory network using two-variable spiking neurons. We evaluate memory state from output spike rates in a minimal extended spatio-temporal contextual learning momery network model.