COMPUTATIONAL GRATING AND BAR CELL MODELS

摘要

Specific cells in the visual cortex serve to detect vertices, such as crossing lines and edges, or to construct illusory contours in the case of occlusion, as occurs with the Kanisza triangle. Computational models of these cells have already been published. Yet other cells serve to detect periodic gratings (textures) or isolated bars. Computational models of the latter cells have also been published, but they lack a precise localisation and the bar cell model is not really a bar detector because it detects anything that is not a periodic grating. We present improved models for grating and bar cells. These models employ a common frontend that consists of retinal ON and OFF channels (isotropic DOG filters) in combination with shunting networks for a contrast normalisation, followed by anisotropic filtering (Gabor fiters as a model for simple cells) and an edge sharpening. The resulting ON and OFF responses are then used with different neural grouping operators (dendritic combination fields) to detect either periodic gratings or individual bars. The models are very selective in terms of grating frequency, bar width and orientation, and result in a very precise boundary localisation. A complete cell assembly covers all frequencies, widths and orientations at each retinotopic position. Such an assembly, together with other functional units, can provide a computational framework for explaining at least low-level cognitive effects.