Connectionists: From stereogram to surface: How the brain sees the world in depth

[Stephen Grossberg]

The following article is now available at 
http://www.cns.bu.edu/Profiles/Grossberg:

Fang, L. and Grossberg, S.
 From stereogram to surface: How the brain sees the world in depth.
Spatial Vision, Special issue on Unresolved Questions in Stereopsis, in press.

ABSTRACT
How do we consciously see surfaces infused with lightness and color 
at the correct depths? Random Dot Stereograms (RDS) probe how 
binocular disparity between the two eyes can generate conscious 
surface percepts. Dense RDS do so despite the fact that they include 
multiple false binocular matches. Sparse stereograms do so across 
large contrast-free regions with no binocular matches. Stereograms 
that define occluding and occluded surfaces lead to surface percepts 
wherein partially occluded textured surfaces are completed behind 
occluding textured surfaces at a spatial scale much larger than that 
of the texture elements themselves. Earlier models suggest how the 
brain detects binocular disparity, but not how RDS generate conscious 
percepts of 3D surfaces. This article proposes a neural model that 
predicts and simulates how the layered circuits of visual cortex 
generate 3D surface percepts using interactions between boundary and 
surface representations that obey complementary computational rules. 
The model clarifies how interactions between layers 4, 3B, and 2/3A 
in V1 and V2 contribute to stereopsis, and proposes how 3D perceptual 
grouping laws in V2 interact with 3D surface filling-in operations in 
V1, V2, and V4 to generate 3D surface percepts in which figures are 
separated from their backgrounds.

Keywords: stereopsis, visual cortex, surface perception, 
figure-ground separation, LAMINART model.