CNBC Seminar: An Adaptive Morphing Approach to Complex 2D and 3D Shape Coding

Ed Connor
Associate Professor and DirectorZanvyl Krieger Mind-Brain Institute Johns Hopkins University

4:00, Monday, October 1

Mellon Institute, Third Floor Social Room
Bellefield Street entrance

The major obstacle to understanding neural representation of complex shape is the sampling problem. Shape space is so vast that standard stimulus strategies typically undersample or entirely miss a neuron's tuning region. Also, any a priori choice of a stimulus set biases and limits the experimental results. To overcome these problems, we implemented an adaptive morphing procedure in which neural responses provide online feedback to guide evolution of stimuli from random starting points. We evaluated this new technique in studies of 2D and 3D shape coding in monkey areas V4 and IT. Each cell was initially tested with one or more starting generations of 50 random shape stimuli. Response rates determined the probability with which ancestor stimuli gave rise to morphed descendants in subsequent stimulus generations. We fit geometric shape coding models that showed strong cross-validation between separate lineages, thus confirming the robustness of the method. The radical efficiency gain and freedom from bias of adaptive sampling could enable detailed exploration of previously intractable issues in visual, tactile, and auditory shape coding.

http://www.mb.jhu.edu/connor.asp