illusory contour
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2021 ◽  
Vol 168 ◽  
pp. S170
Author(s):  
Hang Fan ◽  
Yafei Wang ◽  
Hui Chu ◽  
Ling Wang
Keyword(s):  


Author(s):  
Stephen Grossberg

Multiple paradoxical visual percepts are explained using boundary completion and surface filling-in properties, including discounting the illuminant; brightness constancy, contrast, and assimilation; the Craik-O’Brien-Cornsweet Effect; and Glass patterns. Boundaries act as both generators and barriers to filling-in using specific cooperative and competitive interactions. Oriented local contrast detectors, like cortical simple cells, create uncertainties that are resolved using networks of simple, complex, and hypercomplex cells, leading to unexpected insights such as why Roman typeface letter fonts use serifs. Further uncertainties are resolved by interactions with bipole grouping cells. These simple-complex-hypercomplex-bipole networks form a double filter and grouping network that provides unified explanations of texture segregation, hyperacuity, and illusory contour strength. Discounting the illuminant suppresses illumination contaminants so that feature contours can hierarchically induce surface filling-in. These three hierarchical resolutions of uncertainty explain neon color spreading. Why groupings do not penetrate occluding objects is explained, as are percepts of DaVinci stereopsis, the Koffka-Benussi and Kanizsa-Minguzzi rings, and pictures of graffiti artists and Mooney faces. The property of analog coherence is achieved by laminar neocortical circuits. Variations of a shared canonical laminar circuit have explained data about vision, speech, and cognition. The FACADE theory of 3D vision and figure-ground separation explains much more data than a Bayesian model can. The same cortical process that assures consistency of boundary and surface percepts, despite their complementary laws, also explains how figure-ground separation is triggered. It is also explained how cortical areas V2 and V4 regulate seeing and recognition without forcing all occluders to look transparent.



2021 ◽  
Vol 12 ◽  
Author(s):  
Junkai Yang ◽  
Lisen Sui ◽  
Hongyuan Wu ◽  
Qian Wu ◽  
Xiaolin Mei ◽  
...  

The visual system is capable of recognizing objects when object information is widely separated in space, as revealed by the Kanizsa-type illusory contours (ICs). Attentional involvement in perception of ICs is an important topic, and the present study examined whether and how the processing of ICs is interfered with by a distractor. Discrimination between thin and short deformations of an illusory circle was investigated in the absence or presence of a central dynamic patch, with difficulty of discrimination varied in three levels (easy, medium, and hard). Reaction time (RT) was significantly shorter in the absence compared to the presence of the distractor in the easy and medium conditions. Correct rate (CR) was significantly higher in the absence compared to the presence of the distractor in the easy condition, and the magnitude of the difference between CRs of distracted and non-distracted responses significantly reduced as task difficulty increased. These results suggested that perception of ICs is more likely to be vulnerable to distraction when more attentional resources remain available. The present finding supports that attention is engaged in perception of ICs and that distraction of IC processing is associated with perceptual load.



2019 ◽  
Vol 19 (10) ◽  
pp. 270a
Author(s):  
Nicholas C Duggan ◽  
Emily C Blakley ◽  
Alecia Moser ◽  
Sarah Olsen ◽  
Peter Gerhardstein


2019 ◽  
Vol 19 (10) ◽  
pp. 241a
Author(s):  
Philip J Kellman ◽  
Gennady Erlikhman ◽  
Nicholas Baker ◽  
Hongjing Lu


2019 ◽  
Vol 26 (5) ◽  
pp. 1641-1649 ◽  
Author(s):  
Sarah-Elizabeth Byosiere ◽  
Philippe A. Chouinard ◽  
Tiffani J. Howell ◽  
Pauleen C. Bennett


2019 ◽  
Vol 81 (5) ◽  
pp. 1522-1531 ◽  
Author(s):  
William J. Harrison ◽  
Reuben Rideaux


2019 ◽  
Vol 128 (1) ◽  
pp. 57-68 ◽  
Author(s):  
Brian P. Keane ◽  
Danielle Paterno ◽  
Sabine Kastner ◽  
Bart Krekelberg ◽  
Steven M. Silverstein


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