Physics Dept., Drew University
Characterizing responses of translation-invariant neurons to natural stimuliThe human visual system is capable of recognizing complex objects even when their appearances change drastically under various viewing conditions. Especially in the higher cortical areas, the sensory neurons reflect such functional capacity in their selectivity for complex visual features and invariance to certain object transformations, such as image translation. Due to the strong nonlinearities necessary to achieve both the selectivity and invariance, characterizing and predicting the response patterns of these neurons represents a formidable computational challenge. I will describe a two-step information optimization technique that can characterize both the shape selectivity and the range of position invariance from neural responses to natural stimuli.