Speaker
Description
Recent research, grounded in experiments (notably by Iain Couzin and collaborators), has connected neural ring models of vision to how animals navigate a complex landscape of attractive targets. In this talk we investigate the mathematical and biological implications of a three-stage model where animals pre-process visual stimuli to identify a discrete set of targets, process this input to select the dominant targets, and then post-process this information to navigate the landscape. Incorporating finite target sizes and a neural density allows consistent target acquisition and pursuit reflecting what is seen in nature. Mathematically, we show this model corresponds to an energy minimization problem, simplifying both its analysis and numerical implementation. Biologically, we argue that the model reproduces experimental observations and presents a fairly direct pathway to decoding neural geometry via empirical data.
