Optimal models of sound localization by barn owls

Sound localization by barn owls is commonly modeled as a matching procedure where localization cues derived from auditory inputs are compared to stored templates. While the matching models can explain properties of neural responses, no model explains how the owl resolves spatial ambiguity in the localization cues to produce accurate localization for sources near the center of gaze. Here, I examine two models for the barn owl’s sound localization behavior. First, I consider a maximum likelihood estimator in order to further evaluate the cue matching model. Second, I consider a maximum a posteriori estimator to test whether a Bayesian model with a prior that emphasizes directions near the center of gaze can reproduce the owl’s localization behavior. I show that the maximum likelihood estimator can not reproduce the owl’s behavior, while the maximum a posteriori estimator is able to match the behavior. This result suggests that the standard cue matching model will not be sufficien...

• Type: Conference
• Year: 2007
• Where: NIPS
• Authors: Brian Fischer
• Keywords: Barn Owl, Information Technology, Localization Behavior, NIPS 2007, Sound Localization