Abstract

The 3D LAMINART model of 3D vision and figure-ground perception is used to explain and simulate a key example of the Venetian blind effect and to show how it is related to other well-known perceptual phenomena such as Panum's limiting case. The model proposes how lateral geniculate nucleus (LGN) and hierarchically organized laminar circuits in cortical areas V1, V2, and V4 interact to control processes of 3D boundary formation and surface filling-in that simulate many properties of 3D vision percepts, notably consciously seen surface percepts, which are predicted to arise when filled-in surface representations are integrated into surface-shroud resonances between visual and parietal cortex. Interactions between layers 4, 3B, and 2/3 in V1 and V2 carry out stereopsis and 3D boundary formation. Both binocular and monocular information combine to form 3D boundary and surface representations. Surface contour surface-to-boundary feedback from V2 thin stripes to V2 pale stripes combines computationally complementary boundary and surface formation properties, leading to a single consistent percept, while also eliminating redundant 3D boundaries, and triggering figure-ground perception. False binocular boundary matches are eliminated by Gestalt grouping properties during boundary formation. In particular, a disparity filter, which helps to solve the Correspondence Problem by eliminating false matches, is predicted to be realized as part of the boundary grouping process in layer 2/3 of cortical area V2. The model has been used to simulate the consciously seen 3D surface percepts in 18 psychophysical experiments. These percepts include the Venetian blind effect, Panum's limiting case, contrast variations of dichoptic masking and the correspondence problem, the effect of interocular contrast differences on stereoacuity, stereopsis with polarity-reversed stereograms, da Vinci stereopsis, and perceptual closure. These model mechanisms have also simulated properties of 3D neon color spreading, binocular rivalry, 3D Necker cube, and many examples of 3D figure-ground separation.

Highlights

  • DESIGN PRINCIPLES FOR HOW THE BRAIN SEES THE WORLD IN DEPTH1.1

  • MODEL SIMULATIONS This section summarizes a simulation of the Venetian blind effect and of Panum’s limiting case to illustrate how monocular and binocular information may interact in the laminar circuits of visual cortex to generate 3D surface percepts

  • The filled-in surface representations in all of these articles have parametric properties that closely match visually perceived and reported surface percepts by human subjects. It is for this reason that the liberty is taken of calling them model representations of conscious percepts

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Summary

EXPLAINING 3D PERCEPTS USING LAMINAR CORTICAL NETWORKS

The 3D LAMINART model (Figure 1) predicts how the LGN and cortical areas V1, V2, and V4 computed monocular and binocular visual information to produce three-dimensional (3D) boundary groupings and conscious surface percepts. Among the percepts that the model can simulate is the Venetian blind percept that was described in Figure 6.21 of Howard and Rogers (1995). This Venetian blind stimulus consists of two gratings.

HOW THE BRAIN SEES IN DEPTH
Monocular and binocular information combine in forming depth percepts
MODEL DESCRIPTION
MODEL SIMULATIONS
THE VENETIAN BLIND EFFECT
MODEL EQUATIONS
Far disparity disparity disparity disparity disparity
V2 THIN STRIPE MONOCULAR SURFACE FILLING-IN
DISCUSSION
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