How long range is contour integration in human color vision?

We quantified and compared the effect of element spacing on contour integration between the achromatic (Ach), red-green (RG), and blue-yellow (BY) mechanisms. The task requires the linking of orientation across space to detect a contour in a stimulus composed of randomly oriented Gabor elements (1.5 cpd, sigma = 0.17 deg), measured using a temporal 2AFC method. A contour of ten elements was pasted into a 10 x 10 cells array, a ndbackground elements were randomly positioned within the available cells. The effect of element spacing was investigated by varying the mean interelement distance between two and six times the period of the Gabor elements (lambda = 0.66 deg) while the total number of elements was fixed. Contour detection was measured as a function of its curvature for jagged contours and for closed contours. At all curvatures, we found that performance for chromatic mechanisms declines more steeply with the increase in element separation than does performance for the achromatic mechanism. Averaged critical element separations were 4.6 +/- 0.7, 3.6 +/- 0.4, and 2.9 +/- 0.2 deg for Ach, BY, and RG mechanisms, respectively. These results suggest that contour integration by the chromatic mechanisms relies more on short-range interactions in comparison to the achromatic mechanism. In a further experiment, we looked at the combined effect of element size and element separation in contour integration for the Ach mechanism. We found that the critical separation decreases linearly with the spatial frequency, from about 5 deg at low spatial frequency (larger elements) to about 1 deg at high spatial frequency (smaller elements) suggesting a scale invariance in contour integration. In both experiments we also found no differences between closed and open jagged contours detection in terms of element separation. The neuroanatomical implications of these findings relatively to area V1 are discussed.