Towards an integrated model of feedforward-feedback processing in the visual cortex

Abstract

The goal of this work is to explore a potential improvement on a visual recognition system. The system is a biologically-plausible computational model of the feedforward part of the ventral stream in the visual cortex and successfully models human performance on visual recognition tasks for the first 50-100 milliseconds since the presentation of the visual stimulus. We make the first steps to a possible augmentation of the system that will account for both feedforward and feedback processes in the ventral stream. We explore the plausibility of Bayesian network models for feedback. Our results show that although the resulting system under performs the original, it has a better rate of improvement as more and more training examples are added to it.