Thalamocortical Dynamics of the Mccollough Effect: Boundary-Surface Alignment through Perceptual Learning
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This article further develops the FACADE neural model of 3-D vision and figure-ground perception to quantitatively explain properties of the McCollough effect. The model proposes that many McCollough effect data result from visual system mechanisms whose primary function is to adaptively align, through learning, boundary and surface representations that are positionally shifted, due to the process of binocular fusion. For example, binocular boundary representations are shifted by binocular fusion relative to monocular surface representations, yet the boundaries must become positionally aligned with the surfaces to control binocular surface capture and filling-in. The model also implicates perceptual reset mechanisms that use habituative transmitters in opponent processing circuits. Thus the model shows how McCollough effect data may arise from a combination of mechanisms that have a clear functional role in biological vision. Simulation results with a single set of parameters quantitatively fit data from thirteen experiments that probe the nature of achromatic/chromatic and monocular/binocular interactions during induction of the McCollough effect. The model proposes how perceptual learning, opponent processing, and habituation at both monocular and binocular surface representations are involved, including early thalamocortical sites. In particular it explains the anomalous McCollough effect utilizing these multiple processing sites. Alternative models of the McCollough effect are also summarized and compared with the present model.