paper available: Self-Regulation Mechanism of TAH

[Narihisa MATSUMOTO]

Apologies if you receive this e-mail multiple times.

Dear, colleagues.

I would like to announce the following paper available on the web site:
http://www.mns.brain.riken.go.jp/~xmatumo/paper/NComp02.pdf

``Self-Regulation Mechanism of Temporally Asymmetric Hebbian Plasticity''
by N. Matsumoto & M. Okada
Neural Computation, vol. 14, no. 12, pp. 2883-2902, 2002

Abstract---------------------------------------------------------
Recent biological experimental findings have shown that synaptic plasticity
depends on the relative timing of the pre- and postsynaptic spikes. This
determines whether long-term potentiation (LTP) or long-term depression
(LTD) is induced. This synaptic plasticity has been called temporally asymmetric
Hebbian plasticity (TAH). Many authors have numerically demonstrated that
neural networks are capable of storing spatiotemporal patterns. However, the
mathematical mechanism of the storage of spatiotemporal patterns is still
unknown, and the effect of LTD is particularly unknown. In this article, we
employ a simple neural network model and show that interference between
LTP and LTD disappears in a sparse coding scheme. On the other hand, the
covariance learning rule is known to be indispensable for the storage of sparse
patterns. We also show that TAH has the same qualitative effect as the
covariance rule when spatiotemporal patterns are embedded in the network.
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This shorter version is in
Advances in Neural Information Processing Systems 14, pp. 245-252

Sincerely Yours,

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Narihisa MATSUMOTO
Junior Research Associate
Lab. for Mathematical Neuroscience,RIKEN Brain Science Institute,Japan
e-mail: xmatumo at brain.riken.go.jp
URL: http://www.mns.brain.riken.go.jp/~xmatumo/index.html
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