Abstract
We first present mathematical analysis about the relation between the parameters and the behavior of the basic module in the neural network model for viSual motion detection proposed by one of the authors[1]. Based on the analytical results, a learning rule is proposed that can develop the velocity selectivity of directionally selective cells. The proposed learning rule is simple and plausible in the actual nervous system in that it is described only with local information. Numerical simulation results showed that the basic module learned self-organizingly to acquire the selectivity for velocity of an input stimulus.
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© 1994 Springer-Verlag London Limited
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Miura, Ki., Kurata, K., Nagano, T. (1994). A Learning Rule for Self-organization of The Velocity Selectivity of Directionally Selective Cells. In: Marinaro, M., Morasso, P.G. (eds) ICANN ’94. ICANN 1994. Springer, London. https://doi.org/10.1007/978-1-4471-2097-1_11
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DOI: https://doi.org/10.1007/978-1-4471-2097-1_11
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