Modeling constant best delay-sensitive neurons and tracking neurons in the auditory cortex of the FM bat with a back-propagation neural network

Constant delay-sensitive neurons (CDNs) and tracking neurons (TNs) function as delay-dependent multipliers for cross-correlation processing of biosonar signals in the auditory cortex of the FM bat, Myotis lucifugus. Models of these two kinds of neurons using artificial neural networks (ANNs) which implement the back-propagation algorithm are presented. The ANNs were trained using data collected from neurophysiological experiments with an awake bat. Nonlinear transformations and parameters used in the models are discussed. An ANN model is presented for CDNs and another for TNs. The dynamic responses obtained from these models are observed to be comparable with the recorded signals of FM bats during actual hunting.<>