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Duality of Rate Coding and Temporal Coding in Multilayered Feedforward Networks

masuda{at}sat.t.u-tokyo.ac.jp, Department of Mathematical Engineering and Information Physics, Graduate School of Engineering, University of Tokyo, Tokyo, Japan

Kazuyuki Aihara

aihara{at}sat.t.u-tokyo.ac.jp, Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan

A functional role for precise spike timing has been proposed as an alternative hypothesis to rate coding. We show in this article that both the synchronous firing code and the population rate code can be used dually in a common framework of a single neural network model. Furthermore, these two coding mechanisms are bridged continuously by several modulatable model parameters, including shared connectivity, feedback strength, membrane leak rate, and neuron heterogeneity. The rates of change of these parameters are closely related to the response time and the timescale of learning.

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