Constraints on long range interactions mediating contour detection.

Abstract

Contour detection may be mediated by lateral interactions between neighboring cortical neurons whose receptive fields have collinear axes of preferred orientation. This hypothesis was tested in psychophysical experiments and computer simulations using a contour detection task in which observers searched for groups of Gabor patches that followed spatially extended contour paths embedded in noise consisting of several hundred Gabor patches with random positions and orientations. The orientation-selective units in the simulated neural network were linked by facilitatory interconnections whose strength depended on the geometry (distance, curvature, change in curvature) of smooth curves connecting the orientation axes of units in a pairwise fashion. Psychophysical detection performance was much higher for contour signal groups that followed closed rather than open-ended paths. However, just two sudden changes in orientation of neighboring Gabor patch elements in closed-path contours reduced detection performance to the same levels obtained with open-ended contours. These psychophysical data agreed with the results of the neural network simulations. Furthermore, the simulations also accounted for previous findings that removal of a single Gabor patch element from a closed-path contour group significantly degraded detection performance. We conclude that closure alone is not sufficient to enhance the visibility of a contour. However, if a closed contour meets certain geometric constraints, then lateral interactions based on these constraints can generate facilitation that reverberates around the closed path, thereby enhancing the contour's visibility.