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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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Related in: MedlinePlus

A graphical explanation of the predictions for the inducer types (dark, light, and mixed).The red arrows indicate the location of the highly influential key regions.
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pone-0062505-g003: A graphical explanation of the predictions for the inducer types (dark, light, and mixed).The red arrows indicate the location of the highly influential key regions.

Mentions: Our hypothesis was tested over the course of four experiments. In Experiment 1, ovals were either: all dark, to create a lightened figure surface; all light, to produce a darkened figure surface; or half dark and half light (mixed), to minimize lightness induction. Discriminated contours were either real or illusory (see Figure 2A). The real contours were the same contrast as the ovals, except for the mixed condition, where they were the same contrast as the light ovals. A Bayesian adaptive algorithm (QUEST) adjusted signal (oval) contrast to maintain 70% accuracy [13]. CIs were computed for each of the six conditions [4]. Two “multi-session” observers each performed 10000 trials per condition over the course of several weeks; 50 additional “one-session” observers each performed 200 trials/condition over the course of one hour. The predictions, which are illustrated in Figure 2B and explained more fully in Figure 3, are as follows: i) when inducers are dark, key region noise pixel contrast will positively correlate with a fat response producing light CI features; ii) when inducers are light, key region noise will negatively correlate with a fat response producing dark CI features; and iii) when the inducing edges are light and dark over the course of a trial, there will be little, if any, correlation between noise and response (producing uniform gray CIs).


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

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

A graphical explanation of the predictions for the inducer types (dark, light, and mixed).The red arrows indicate the location of the highly influential key regions.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0062505-g003: A graphical explanation of the predictions for the inducer types (dark, light, and mixed).The red arrows indicate the location of the highly influential key regions.
Mentions: Our hypothesis was tested over the course of four experiments. In Experiment 1, ovals were either: all dark, to create a lightened figure surface; all light, to produce a darkened figure surface; or half dark and half light (mixed), to minimize lightness induction. Discriminated contours were either real or illusory (see Figure 2A). The real contours were the same contrast as the ovals, except for the mixed condition, where they were the same contrast as the light ovals. A Bayesian adaptive algorithm (QUEST) adjusted signal (oval) contrast to maintain 70% accuracy [13]. CIs were computed for each of the six conditions [4]. Two “multi-session” observers each performed 10000 trials per condition over the course of several weeks; 50 additional “one-session” observers each performed 200 trials/condition over the course of one hour. The predictions, which are illustrated in Figure 2B and explained more fully in Figure 3, are as follows: i) when inducers are dark, key region noise pixel contrast will positively correlate with a fat response producing light CI features; ii) when inducers are light, key region noise will negatively correlate with a fat response producing dark CI features; and iii) when the inducing edges are light and dark over the course of a trial, there will be little, if any, correlation between noise and response (producing uniform gray CIs).

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