A model of the computations leading to a representation of auditory space in the midbrain of the barn owl

A model was developed for the computations performed in the auditory system of the barn owl that lead to a representation of auditory space in the external nucleus of the inferior colliculus (ICx). The goal of the study was to better understand the role of nonlinear processing of interaural time difference (ITD) and interaural level difference (ILD) cues in creating a representation of auditory space. To achieve this goal, a high-level model of the barn owl's auditory localization system was developed that assigned systems-level variables and functions to each of the neurobiological substrates that process time and level difference cues. The computational model was then implemented in neurobiologically realistic model circuits that matched the currently available neurophysiological data.; At the systems level we showed that a likelihood function model fails as a model of auditory space representation in the barn owl's ICx. The likelihood function model required a multiplication of signals across frequencies that would not produce side peaks in ITD tuning curves, as is observed experimentally. We found that a model where interaural time difference and interaural level difference cues are combined nonlinearly within frequency channels and then summed across frequency channels is a neurobiologically consistent model of auditory space representation in the barn owl's ICx.; At the neuronal level we showed that AND-like sensitivity to ITD and ILD can arise in a network where inputs to each neuron are summed linearly. Our model supposes that a subset of neurons in the lateral shell of the central nucleus of the inferior colliculus (ICcl) encode ITD and ILD additively at the subthreshold level. Using population coding ideas we show that subsequent neurons in ICx can show multiplicative tuning to ITD and ILD at the subthreshold level where inputs to each neuron are summed linearly. This model provides a specific implementation of the experimentally observed nonlinear selectivity for ITD and ILD in ICx neurons.