grouping component
Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex
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.
Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex
Zemel, Richard S., Sejnowski, Terrence J.
Previous investigators have suggested that these cells may represent self-motion. Spiral patterns can also be generated 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 describe a model based on the hypothesis that the selective tuning of MST cells reflects the grouping of object components undergoing coherent motion. Inputs to the model were generated from sequences of ray-traced images that simulated realistic motion situations, combining observer motion, eye movements, and independent object motion. The input representation was modeled after response properties of neurons in area MT, which provides the primary 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.
Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex
Zemel, Richard S., Sejnowski, Terrence J.
Previous investigators have suggested that these cells may represent self-motion. Spiral patterns can also be generated 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 describe a model based on the hypothesis that the selective tuning of MST cells reflects the grouping of object components undergoing coherent motion. Inputs to the model were generated from sequences of ray-traced images that simulated realistic motion situations, combining observer motion, eye movements, and independent object motion. The input representation was modeled after response properties of neurons in area MT, which provides the primary 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.
Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex
Zemel, Richard S., Sejnowski, Terrence J.
A number of studies have described neurons in the dorsal part of the medial superior temporal (MSTd) monkey cortex that respond best to large expanding/contracting, rotating, or shifting patterns (Tanaka et al., 1986; Duffy & Wurtz, 1991a). Recently Graziano et al. (1994) found that MSTd cell responses correspond to a point in a multidimensional space of spiral motions, where the dimensions are these motion types. Combinationsof these motions are generated as an animal moves through its environment, whichsuggests that area MSTd could playa role in optical flow analysis. When an observer moves through a static environment, a singularity in the flow field known as the focus of expansion may be used to determine the direction of heading (Gibson, 1950; Warren & Hannon, 1988). Previous computational models of MSTd (Lappe & Rauschecker, 1993; Perrone & Stone, 1994) have shown how navigational information related to heading may be encoded by these cells.