Context-Sensitive Binding by the Laminar Circuits of V1 and V2

[Stephen Grossberg]

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

Raizada, R.D.S. and Grossberg, S. (2001). Context-Sensitive Binding 
by the Laminar Circuits of V1 and V2: A Unified Model of Perceptual 
Grouping, Attention, and Orientation Contrast. Visual Cognition, in 
press. Preliminary version available as Technical Report CAS/CNS 
TR-2000-008

  ABSTRACT:

A detailed neural model is presented of how the laminar circuits of 
visual cortical areas V1 and V2 implement context-sensitive binding 
processes such as perceptual grouping and attention. The model 
proposes how specific laminar circuits allow the responses of visual 
cortical neurons to be determined not only by the stimuli within 
their classical receptive fields, but also to be strongly influenced 
by stimuli in the extra-classical surround. This context-sensitive 
visual processing can greatly enhance the analysis of visual scenes, 
especially those containing targets that are low contrast, partially 
occluded, or crowded by
distractors. We show how interactions of feedforward, feedback and 
horizontal circuitry can implement several types of contextual 
processing simultaneously, using shared laminar circuits. In 
particular, we present computer simulations which suggest how 
top-down attention and preattentive perceptual grouping, two 
processes that are fundamental for visual binding, can interact, with 
attentional enhancement selectively propagating along groupings of 
both real and illusory contours, thereby showing how attention can 
selectively enhance object representations. These simulations also 
illustrate how attention may have a stronger facilitatory effect on 
low contrast than on high contrast stimuli, and how
pop-out from orientation contrast may occur. The specific functional 
roles which the model proposes for the cortical layers allow several 
testable  neurophysiological predictions to be made. The results 
presented here simulate only the boundary grouping system of adult 
cortical architecture. However, we also discuss how this model 
contributes to a larger neural theory of vision which suggests how 
intracortical and intercortical feedback help to stabilize 
development and learning within these cortical circuits. Although 
feedback plays a key role, fast feedforward processing is possible in 
response to unambiguous information. Model circuits are capable of 
synchronizing quickly, but  context-sensitive persistence of previous 
events can influence how synchrony develops. Although these results 
focus on how the interblob cortical processing stream controls 
boundary grouping and attention, related modeling of the blob 
cortical processing stream suggests how visible surfaces are formed, 
and modeling of the motion stream suggests how transient responses to 
scenic changes can control long-range apparent motion and also 
attract spatial attention.