[Comp-neuro] spiking laminar cortical circuits for 3D vision

Stephen Grossberg steve at cns.bu.edu
Thu Dec 1 17:45:38 CET 2011


The following article is now available at http://cns.bu.edu/~steve about how spiking neurons in laminar cortical circuits may carry out 3D vision. This spiking LAMINART model shows how spiking laminar cortical circuits can compute key visual processes without a loss of analog sensitiivity, such as binocular fusion, 3D boundary completion, and 3D surface filling-in.

Cao, Y., and Grossberg, S. (2011). Stereopsis and 3D surface perception by spiking neurons in laminar cortical circuits: A method of converting neural rate models into spiking models. Neural Networks, in press. 

Abstract
A laminar cortical model of stereopsis and 3D surface perception is developed and simulated. The model shows how spiking neurons that interact in hierarchically organized laminar circuits of the visual cortex can generate analog properties of 3D visual percepts. The model describes how monocular and binocular oriented filtering interact with later stages of 3D boundary formation and surface filling-in in the LGN and cortical areas V1, V2, and V4. It proposes how interactions between layers 4, 3B, and 2/3 in V1 and V2 contribute to stereopsis, and how binocular and monocular information combine to form 3D boundary and surface representations. The model suggests how surface-to-boundary feedback from V2 thin stripes to pale stripes helps to explain how computationally complementary boundary and surface formation properties lead to a single consistent percept, eliminate redundant 3D boundaries, and trigger figure-ground perception. The model also shows how false binocular boundary matches may be eliminated by Gestalt grouping properties. In particular, the disparity filter, which helps to solve the correspondence problem by eliminating false matches, is realized using inhibitory interneurons as part of the perceptual grouping process by horizontal connections in layer 2/3 of cortical area V2. The 3D sLAMINART model simulates 3D surface percepts that are consciously seen in 18 psychophysical experiments. These percepts include contrast variations of dichoptic masking and the correspondence problem, the effect of interocular contrast differences on stereoacuity, Panum's limiting case, the Venetian blind illusion, stereopsis with polarity-reversed stereograms, da Vinci stereopsis, and perceptual closure. The model hereby illustrates a general method of unlumping rate-based models that use the membrane equations of neurophysiology into models that use spiking neurons, and which may be embodied in VLSI chips that use spiking neurons to minimize heat production.


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