Adaptive boundary-surface alignment and the McCollough effect

[Stephen Grossberg]

The following article is now available at 
http://www.cns.bu.edu/Profiles/Grossberg in  PDF and  Gzipped 
Postscript.

Grossberg, S., Hwang, S., and Mingolla, E. (2002). Thalamocortical 
dynamics of the McCollough effect: Boundary-surface alignment through 
perceptual learning.
Vision Research, in press.

Abstract: 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 includes 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.