Literature DB >> 17594799

Laminar cortical dynamics of visual form and motion interactions during coherent object motion perception.

J Berzhanskaya1, S Grossberg, E Mingolla.   

Abstract

How do visual form and motion processes cooperate to compute object motion when each process separately is insufficient? Consider, for example, a deer moving behind a bush. Here the partially occluded fragments of motion signals available to an observer must be coherently grouped into the motion of a single object. A 3D FORMOTION model comprises five important functional interactions involving the brain's form and motion systems that address such situations. Because the model's stages are analogous to areas of the primate visual system, we refer to the stages by corresponding anatomical names. In one of these functional interactions, 3D boundary representations, in which figures are separated from their backgrounds, are formed in cortical area V2. These depth-selective V2 boundaries select motion signals at the appropriate depths in MT via V2-to-MT signals. In another, motion signals in MT disambiguate locally incomplete or ambiguous boundary signals in V2 via MT-to-V1-to-V2 feedback. The third functional property concerns resolution of the aperture problem along straight moving contours by propagating the influence of unambiguous motion signals generated at contour terminators or corners. Here, sparse 'feature tracking signals' from, for example, line ends are amplified to overwhelm numerically superior ambiguous motion signals along line segment interiors. In the fourth, a spatially anisotropic motion grouping process takes place across perceptual space via MT-MST feedback to integrate veridical feature-tracking and ambiguous motion signals to determine a global object motion percept. The fifth property uses the MT-MST feedback loop to convey an attentional priming signal from higher brain areas back to V1 and V2. The model's use of mechanisms such as divisive normalization, endstopping, cross-orientation inhibition, and long-range cooperation is described. Simulated data include: the degree of motion coherence of rotating shapes observed through apertures, the coherent vs. element motion percepts separated in depth during the chopsticks illusion, and the rigid vs. nonrigid appearance of rotating ellipses.

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Year:  2007        PMID: 17594799     DOI: 10.1163/156856807780919000

Source DB:  PubMed          Journal:  Spat Vis        ISSN: 0169-1015


  22 in total

1.  Integrating motion and depth via parallel pathways.

Authors:  Carlos R Ponce; Stephen G Lomber; Richard T Born
Journal:  Nat Neurosci       Date:  2008-01-13       Impact factor: 24.884

2.  Rotating columns: relating structure-from-motion, accretion/deletion, and figure/ground.

Authors:  Vicky Froyen; Jacob Feldman; Manish Singh
Journal:  J Vis       Date:  2013-08-14       Impact factor: 2.240

3.  Binocular fusion and invariant category learning due to predictive remapping during scanning of a depthful scene with eye movements.

Authors:  Stephen Grossberg; Karthik Srinivasan; Arash Yazdanbakhsh
Journal:  Front Psychol       Date:  2015-01-14

4.  Low-level sensory plasticity during task-irrelevant perceptual learning: evidence from conventional and double training procedures.

Authors:  Praveen K Pilly; Stephen Grossberg; Aaron R Seitz
Journal:  Vision Res       Date:  2009-10-01       Impact factor: 1.886

5.  Neural dynamics of object-based multifocal visual spatial attention and priming: object cueing, useful-field-of-view, and crowding.

Authors:  Nicholas C Foley; Stephen Grossberg; Ennio Mingolla
Journal:  Cogn Psychol       Date:  2012-03-14       Impact factor: 3.468

6.  Construction and evaluation of an integrated dynamical model of visual motion perception.

Authors:  Émilien Tlapale; Barbara Anne Dosher; Zhong-Lin Lu
Journal:  Neural Netw       Date:  2015-03-28

7.  Bifurcation analysis applied to a model of motion integration with a multistable stimulus.

Authors:  James Rankin; Emilien Tlapale; Romain Veltz; Olivier Faugeras; Pierre Kornprobst
Journal:  J Comput Neurosci       Date:  2012-07-03       Impact factor: 1.621

8.  Representation of motion onset and offset in an augmented Barlow-Levick model of motion detection.

Authors:  Timothy Barnes; Ennio Mingolla
Journal:  J Comput Neurosci       Date:  2012-04-13       Impact factor: 1.621

9.  Desirability, availability, credit assignment, category learning, and attention: Cognitive-emotional and working memory dynamics of orbitofrontal, ventrolateral, and dorsolateral prefrontal cortices.

Authors:  Stephen Grossberg
Journal:  Brain Neurosci Adv       Date:  2018-05-08

10.  A Canonical Laminar Neocortical Circuit Whose Bottom-Up, Horizontal, and Top-Down Pathways Control Attention, Learning, and Prediction.

Authors:  Stephen Grossberg
Journal:  Front Syst Neurosci       Date:  2021-04-23
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