Connectionist networks in auditory system modeling

Understanding how complex sounds, such as speech, are processed and eventually perceived in the brain is essential for building more effective speech processors. The echolocating bat provides an animal model for complex-sound processing of identified stimulus features at higher levels of the auditory pathway. In this paper, we present the use of connectionist models for modeling cortical neurons that play a key role in our auditory system model of a species of FM bat, Myotis lucifugus. The influence of network related parameters on modeling accuracy is presented, and the response of these models is explained in a behavioral context.