A recurrent network model for range processing of the mustached bat

A computational model, which simulates the neural processing of range information in the mustached bat is proposed. The internal states and the learning characteristics of the neural model as well as the mechanism for the processing of range information are explored. The neural model is capable of interpolation, so it can simulate the range information processing in bat´s auditory system. The following important properties are found in the trained network: (1) five types of hidden units are created, and they have their counterparts in the bat´s brain based on the similarity of the response patterns; (2) the hidden units show characteristics of plasticity; and (3) a dis-inhibition mechanism is found, which has not yet been found in neurophysiological study