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Reinterpreting behavioral receptive fields: lightness induction alters visually completed shape.

Keane BP, Lu H, Papathomas TV, Silverstein SM, Kellman PJ - PLoS ONE (2013)

Bottom Line: This pattern arose when pixels immediately adjacent to the discriminated boundaries were excluded from the analysis (Experiment 2) and also when the noise was restricted to the key regions so that the noise never overlapped with the physically visible edges (Experiment 3).Moreover, behavioral receptive fields derived in CI studies do not correspond to contours per se but to filled-in surface regions contained by those contours.The relevance of lightness to two-dimensional shape completion supplies a new constraint for models of object perception.

View Article: PubMed Central - PubMed

Affiliation: Center for Cognitive Science, Rutgers University, New Brunswick, Piscataway, New Jersey, USA. Brian.Keane@gmail.com

ABSTRACT

Background: A classification image (CI) technique has shown that static luminance noise near visually completed contours affects the discrimination of fat and thin Kanizsa shapes. These influential noise regions were proposed to reveal "behavioral receptive fields" of completed contours-the same regions to which early cortical cells respond in neurophysiological studies of contour completion. Here, we hypothesized that 1) influential noise regions correspond to the surfaces that distinguish fat and thin shapes (hereafter, key regions); and 2) key region noise biases a "fat" response to the extent that its contrast polarity (lighter or darker than background) matches the shape's filled-in surface color.

Results: To test our hypothesis, we had observers discriminate fat and thin noise-embedded rectangles that were defined by either illusory or luminance-defined contours (Experiment 1). Surrounding elements ("inducers") caused the shapes to appear either lighter or darker than the background-a process sometimes referred to as lightness induction. For both illusory and luminance-defined rectangles, key region noise biased a fat response to the extent that its contrast polarity (light or dark) matched the induced surface color. When lightness induction was minimized, luminance noise had no consistent influence on shape discrimination. This pattern arose when pixels immediately adjacent to the discriminated boundaries were excluded from the analysis (Experiment 2) and also when the noise was restricted to the key regions so that the noise never overlapped with the physically visible edges (Experiment 3). The lightness effects did not occur in the absence of enclosing boundaries (Experiment 4).

Conclusions: Under noisy conditions, lightness induction alters visually completed shape. Moreover, behavioral receptive fields derived in CI studies do not correspond to contours per se but to filled-in surface regions contained by those contours. The relevance of lightness to two-dimensional shape completion supplies a new constraint for models of object perception.

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Convolved CIs for human and ideal observers computed from 30,000 and 3,000 trials per condition, respectively.The superimposed translucent ovals show the position of an average rectangle (neither fat nor thin). Human CIs are shown with and without superimposed key regions (dotted red lines).
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pone-0062505-g004: Convolved CIs for human and ideal observers computed from 30,000 and 3,000 trials per condition, respectively.The superimposed translucent ovals show the position of an average rectangle (neither fat nor thin). Human CIs are shown with and without superimposed key regions (dotted red lines).

Mentions: CIs computed from all observers are shown in Figure 4. It can be seen that in the absence of lightness induction, there were no noticeable CI features and in the presence of lightness induction, the key regions were employed in the way predicted. To quantify lightness effects, we performed a region-of-interest (ROI) analysis on the “raw” CIs (viz., those which have not undergone blurring or any other processing.) The ROI was centered within the two key regions and did not overlap with physically visible edges (see Figure 5A and the Analysis section of the Methods for ROI dimensions). The average CI pixel value within the ROI strongly depended on inducer polarity for both one-session and multi-session observers (ps<.001). This dependence was comparable for real and illusory contours (ps>.09). More specifically, for both contour types, the average ROI value was always positive when the inducers were dark, always negative when inducers were light, and intermediate, otherwise.


Reinterpreting behavioral receptive fields: lightness induction alters visually completed shape.

Keane BP, Lu H, Papathomas TV, Silverstein SM, Kellman PJ - PLoS ONE (2013)

Convolved CIs for human and ideal observers computed from 30,000 and 3,000 trials per condition, respectively.The superimposed translucent ovals show the position of an average rectangle (neither fat nor thin). Human CIs are shown with and without superimposed key regions (dotted red lines).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3672097&req=5

pone-0062505-g004: Convolved CIs for human and ideal observers computed from 30,000 and 3,000 trials per condition, respectively.The superimposed translucent ovals show the position of an average rectangle (neither fat nor thin). Human CIs are shown with and without superimposed key regions (dotted red lines).
Mentions: CIs computed from all observers are shown in Figure 4. It can be seen that in the absence of lightness induction, there were no noticeable CI features and in the presence of lightness induction, the key regions were employed in the way predicted. To quantify lightness effects, we performed a region-of-interest (ROI) analysis on the “raw” CIs (viz., those which have not undergone blurring or any other processing.) The ROI was centered within the two key regions and did not overlap with physically visible edges (see Figure 5A and the Analysis section of the Methods for ROI dimensions). The average CI pixel value within the ROI strongly depended on inducer polarity for both one-session and multi-session observers (ps<.001). This dependence was comparable for real and illusory contours (ps>.09). More specifically, for both contour types, the average ROI value was always positive when the inducers were dark, always negative when inducers were light, and intermediate, otherwise.

Bottom Line: This pattern arose when pixels immediately adjacent to the discriminated boundaries were excluded from the analysis (Experiment 2) and also when the noise was restricted to the key regions so that the noise never overlapped with the physically visible edges (Experiment 3).Moreover, behavioral receptive fields derived in CI studies do not correspond to contours per se but to filled-in surface regions contained by those contours.The relevance of lightness to two-dimensional shape completion supplies a new constraint for models of object perception.

View Article: PubMed Central - PubMed

Affiliation: Center for Cognitive Science, Rutgers University, New Brunswick, Piscataway, New Jersey, USA. Brian.Keane@gmail.com

ABSTRACT

Background: A classification image (CI) technique has shown that static luminance noise near visually completed contours affects the discrimination of fat and thin Kanizsa shapes. These influential noise regions were proposed to reveal "behavioral receptive fields" of completed contours-the same regions to which early cortical cells respond in neurophysiological studies of contour completion. Here, we hypothesized that 1) influential noise regions correspond to the surfaces that distinguish fat and thin shapes (hereafter, key regions); and 2) key region noise biases a "fat" response to the extent that its contrast polarity (lighter or darker than background) matches the shape's filled-in surface color.

Results: To test our hypothesis, we had observers discriminate fat and thin noise-embedded rectangles that were defined by either illusory or luminance-defined contours (Experiment 1). Surrounding elements ("inducers") caused the shapes to appear either lighter or darker than the background-a process sometimes referred to as lightness induction. For both illusory and luminance-defined rectangles, key region noise biased a fat response to the extent that its contrast polarity (light or dark) matched the induced surface color. When lightness induction was minimized, luminance noise had no consistent influence on shape discrimination. This pattern arose when pixels immediately adjacent to the discriminated boundaries were excluded from the analysis (Experiment 2) and also when the noise was restricted to the key regions so that the noise never overlapped with the physically visible edges (Experiment 3). The lightness effects did not occur in the absence of enclosing boundaries (Experiment 4).

Conclusions: Under noisy conditions, lightness induction alters visually completed shape. Moreover, behavioral receptive fields derived in CI studies do not correspond to contours per se but to filled-in surface regions contained by those contours. The relevance of lightness to two-dimensional shape completion supplies a new constraint for models of object perception.

Show MeSH
Related in: MedlinePlus