Richard Zemel, Terrence J. Sejnowski
Many cells in the dorsal part of the medial superior temporal (MST) area of visual cortex respond selectively to spiral flow patterns-specific combinations of expansion/ contraction and ro(cid:173) tation motions. Previous investigators have suggested that these cells may represent self-motion. Spiral patterns can also be gener(cid:173) ated by the relative motion of the observer and a particular object. An MST cell may then account for some portion of the complex flow field, and the set of active cells could encode the entire flow; in this manner, MST effectively segments moving objects. Such a grouping operation is essential in interpreting scenes containing several independent moving objects and observer motion. We de(cid:173) scribe a model based on the hypothesis that the selective tuning of MST cells reflects the grouping of object components undergo(cid:173) ing coherent motion. Inputs to the model were generated from sequences of ray-traced images that simulated realistic motion sit(cid:173) uations, combining observer motion, eye movements, and indepen(cid:173) dent object motion. The input representation was modeled after response properties of neurons in area MT, which provides the pri(cid:173) mary input to area MST. After applying an unsupervised learning algorithm, the units became tuned to patterns signaling coherent motion. The results match many of the known properties of MST cells and are consistent with recent studies indicating that these cells process 3-D object motion information.
Richard S. Zemel, Terrence J. Sejnowski