Hyperacuity in time: A CNN model of a time-coding pathway of sound localization

This paper discusses a new multilayer one-dimensional (1-D) cellular neural network model of the time-coding pathway of sound localization. The key fe ature of the model is lateral inhibition, which is supposed to play a cruci al role in sound localization. The possible role of this inhibition is exam ined on the basis of our model and several conlusions are drawn concerning the expected nature of inhibition. It is also shown that by use of inhibiti on, a group of neurons may be much more sensitive to interaural time differ ence than one individual neuron. Thus, our model of the first stage of the sound localization system solves a hyperacuity in time problem. The second part of the paper introduces a CNN model of that part of the sound localiza tion system which is characterized by a massive convergence of different fr equency channels to resolve the so-called phase ambiguity problem. We show that with inhibition good results can be achieved here too. Quantitative st udies show the robustness of the model.