Near Their Thresholds for Detection, Shapes Are Discriminated by the Angular Separation of Their Corners

Abstract

Observers make sense of scenes by parsing images on the retina into meaningful objects. This ability is retained for line drawings, demonstrating that critical information is concentrated at object boundaries. Information theoretic studies argue for further concentration at points of maximum curvature, or corners, on such boundaries [1]–[3] suggesting that the relative positions of such corners might be important in defining shape. In this study we use patterns subtly deformed from circular, by a sinusoidal modulation of radius, in order to measure threshold sensitivity to shape change. By examining the ability of observers to discriminate between patterns of different frequency and/or number of cycles of modulation in a 2x2 forced choice task we were able to show, psychophysically, that difference in a single cue, the periodicity of the corners (specifically the polar angle between two points of maximum curvature) was sufficient to allow discrimination of two patterns near their thresholds for detection. We conclude that patterns could be considered as labelled for this measure. These results suggest that a small number of such labels might be sufficient to identify an object.

Global shape processing involves feature-selective and feature-agnostic coding mechanisms

“…Moreover, the same pattern of results was obtained for two distinct global shapes, RF3 ( Figure 2) and RF4 (Figure 3), and for two different shape orientations, a square-like (08 rotated) and diamond-like (458 rotated) RF4 test ( Figure 5). Taken together with previous findings showing that RF shape aftereffects, under appropriate circumstances, are RF shape specific (Anderson et al, 2007;Bell, Wilkinson, et al, 2009) and that different RFs can be discriminated perfectly at their thresholds for detection, meaning separate mechanisms must exist (Dickinson, Bell, & Badcock, 2013), we conclude that there exist mechanisms that code for a given global contour shape at a given shape orientation.…”

Tolerance for local and global differences in the integration of shape information

“…Experiment 2 of this study demonstrates that, near detection threshold, the mechanisms encoding shape are indifferent to absolute measures of curvature and so, near detection threshold, the curvature versus polar angle space proposed by Connor et al collapses to the positions of curvature features on the polar angle axis. Dickinson, Bell, and Badcock (2013), using a discrimination at threshold for detection paradigm in a two-decision, two-interval, forced choice (2x2IFC) task (Watson & Robson, 1981), showed that RF patterns with different modulation frequencies could be discriminated at their thresholds for the detection of modulation if they contained two or more cycles of modulation. Patterns with the same frequency but different numbers of cycles of modulation, however, could not.…”

Enhanced global integration of closed contours in individuals with high levels of autistic-like traits

“…As mentioned above, the terms 'local' and 'global' are used here in a very specific sense, referring to clearly identified mechanisms with known neural bases (Gallant, Shoup, & Mazer, 2000;Wilkinson et al, 2000). The repeated findings of superior RF search task performance suggest that the high AQ group may have narrower RF channel bandwidths (Almeida et al, 2010a or higher sensitivity to the parameters underlying global processing of RF patterns (Dickinson, Bell, & Badcock, 2013). This implies that global pooling will be more selective for RF number and that global integration could be stronger, not weaker for high AQ individuals.…”