Neural network model for extracting optic flow

Abstract

In the MST area of the monkey, there are cells that respond selectively to specific motions of a large area of the visual field, such as rotation or expansion/contraction. They respond steadily even when the location of the center of optic flow shifts on the retina. They are thought to analyze optic flows of the retinal images. This paper proposes a neural network model for these cells. The model performs processing similar to mathematical operations called rot and div in the vector field analysis. It is a hierarchical multilayered network: retina, layer VI, layers MT and layer MST. Each MT cell extracts relative velocity between two adjoining small visual fields, and an MST cell adds the response of many MT cells to extract a specific optic flow. The difference in type of optic flows extracted by MST cells can be created simply by the difference in relative locations between inhibitory and excitatory areas in the receptive fields of the preceding MT cells. © Springer-Verlag Berlin Heidelberg 2005.