A spiking network of hippocampal model including neurogenesis

Authors:
Yusuke Tabata;Masaharu Adachi
Affiliations:
Graduate School of Engineering, Tokyo Denki University, Tokyo, Japan;Graduate School of Engineering, Tokyo Denki University, Tokyo, Japan
Venue:
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Year:
2008

Citing 4
Cited 0

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A theoretical network model to analyse neurogenesis and synaptogenesis in the dentate gyrus

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Self-organization of spiking neurons using action potential timing

IEEE Transactions on Neural Networks
Simple model of spiking neurons

IEEE Transactions on Neural Networks

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Abstract

In this paper, we construct a spiking network model based on the firing-rate coding hippocampal model proposed by Becker. Basal training patterns are presented to the model network and spiking self organizing map learning is applied to the network in order to store the training patterns. We then apply a morphogenesis model in the dentate gyrus region to generate new neurons and investigate the influence of such neurogenesis on the storage and recall of novel memory. As a result, the storage capacity is essentially unchanged by the morphogenetic algorithm even when the number of training patterns is changed.