The features that control discrimination of an isodipole texture pair

Abstract

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 co mputations. We focus on two canonical isodipole textures, the "even" and "odd" textures: any 2×2 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 = 2×2, 2×3, 2×4 and 3×3, 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 2×4 and 3×3 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.

Learning complex texture discrimination

“…These suggested that the lower bound on the number of those mechanisms is between 4 and 7 [7]. That being said larger patch sizes than 2×2 seem to be needed to fully explain discrimination of isotrigon textures [16] and their visual salience [2], implying the possible involvement of 5 th and higher-order correlations. As we [6] and others [7] have recognized, considering 2×2 block correlations is related to the Minkowski functionals (MFs).…”

“…Not surprisingly then, humans and primates have been shown to be acutely sensitive to such correlations in a number of psychophysical [3][4][5][6][7], electrophysiological [8][9][10][11], and brain imaging [12][13][14] studies. A range of synthetic texture stimuli that have well-controlled correlation structure have been designed to probe our sensitivity to such image structure [3,7,15,16]. It has also been reported that the image structure that makes some of these synthetic textures visually salient also makes natural textures salient, and that this structure represents non-redundant correlation content in these images [2].…”

“…Not surprisingly then, humans and primates have been shown to be acutely sensitive to such correlations in a number of psychophysical [3][4][5][6][7], electrophysiological [8][9][10][11], and brain imaging [12][13][14] studies. A range of synthetic texture stimuli that have well-controlled correlation structure have been designed to probe our sensitivity to such image structure [3,7,15,16]. It has also been reported that the image structure that makes some of these synthetic textures visually salient also makes natural textures salient, and that this structure represents non-redundant correlation content in these images [2].…”