The features that control discrimination of an isodipole texture pair.

Visual features such as edges and corners are carried by high-order statistics. Previous analysis of discrimination of "isodipole" textures, which isolate specific high-order statistics, demonstrates visual sensitivity to these statistics but stops short of analyzing the underlying computations. Here we use a new "texture centroid" paradigm to probe these computations. We focus on two canonical isodipole textures, the "even" and "odd" textures: any 2x2 block of even (odd) texture contains an even (odd) number of black (and white) checks. Each stimulus comprised a spatially random array of black-and-white texture-disks (background = mean gray) that varied in their fourth-order statistics. In the Even (Odd) condition, disks varied along the continuum between random "coinflip" texture and pure (highly structured) even (odd) target texture. The task was to mouse-click the centroid of the disk array, weighting each disk location by the target structure level of the disk-texture (ranging from 0 for coinflip to 1 for even or odd). For each of block-sizes S= 2x2, 2x3, 2x4 and 3x3, a linear model was used to estimate the weight exerted on the subject's responses by the differently patterned blocks of size S. Only the results with 2x4 and 3x3 blocks were consistent with the data. In the Even condition, homogeneous blocks exerted the most weight; in the odd condition, block-pattern symmetry was important. These findings show that visual mechanisms sensitive to four-point correlations do not compute "evenness" or "oddness" per se, but rather are activated selectively by features whose frequency varies across isodipole textures.