A computational model of the responses of octopus neurons in the PVCN

Acoustic information can be detected and processed through the auditory pathway in a very fast and complicated way. A large number of studies have investigated sound encoding at different levels of the auditory system by recording direct neural responses to different types of stimuli. However, processing of more complex stimuli at higher auditory centres is not well understood yet. Computational modeling has emerged as a new approach in order to obtain at least some insight into mechanisms underlying processing of complex sounds such as speech, animal vocalization, and music. In this study, the main goal is to develop a phenomenological and computer-based model of octopus neurons in the posterior ventral cochlear nucleus to simulate the physiological responses to simple and complex stimuli. Octopus cells receive synaptic inputs from a number of auditory nerve (AN) fibers; as a result, an AN model developed by Zilany and colleagues has been used to provide input to the proposed model. The summation of weighted outputs from the AN model has been subjected to a power-law adaptation function to simulate octopus cell responses. Model responses are compared to the actual physiological data recorded from octopus neurons. Output of the proposed model can be applied as an excitatory input to model responses of superior paraolivary nucleus neurons located in the superior olivary complex and also in the model of sound localization.