Literature DB >> 17041595

How MT cells analyze the motion of visual patterns.

Nicole C Rust1, Valerio Mante, Eero P Simoncelli, J Anthony Movshon.   

Abstract

Neurons in area MT (V5) are selective for the direction of visual motion. In addition, many are selective for the motion of complex patterns independent of the orientation of their components, a behavior not seen in earlier visual areas. We show that the responses of MT cells can be captured by a linear-nonlinear model that operates not on the visual stimulus, but on the afferent responses of a population of nonlinear V1 cells. We fit this cascade model to responses of individual MT neurons and show that it robustly predicts the separately measured responses to gratings and plaids. The model captures the full range of pattern motion selectivity found in MT. Cells that signal pattern motion are distinguished by having convergent excitatory input from V1 cells with a wide range of preferred directions, strong motion opponent suppression and a tuned normalization that may reflect suppressive input from the surround of V1 cells.

Mesh:

Year:  2006        PMID: 17041595     DOI: 10.1038/nn1786

Source DB:  PubMed          Journal:  Nat Neurosci        ISSN: 1097-6256            Impact factor:   24.884


  189 in total

1.  Hierarchy of direction-tuned motion adaptation in human visual cortex.

Authors:  Hyun Ah Lee; Sang-Hun Lee
Journal:  J Neurophysiol       Date:  2012-01-04       Impact factor: 2.714

2.  Hierarchical processing of complex motion along the primate dorsal visual pathway.

Authors:  Patrick J Mineault; Farhan A Khawaja; Daniel A Butts; Christopher C Pack
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-31       Impact factor: 11.205

3.  Curvature processing dynamics in macaque area V4.

Authors:  Jeffrey M Yau; Anitha Pasupathy; Scott L Brincat; Charles E Connor
Journal:  Cereb Cortex       Date:  2012-01-31       Impact factor: 5.357

4.  Visual motion integration by neurons in the middle temporal area of a New World monkey, the marmoset.

Authors:  Selina S Solomon; Chris Tailby; Saba Gharaei; Aaron J Camp; James A Bourne; Samuel G Solomon
Journal:  J Physiol       Date:  2011-09-26       Impact factor: 5.182

5.  Motion-based prediction is sufficient to solve the aperture problem.

Authors:  Laurent U Perrinet; Guillaume S Masson
Journal:  Neural Comput       Date:  2012-06-26       Impact factor: 2.026

6.  The role of V1 surround suppression in MT motion integration.

Authors:  James M G Tsui; J Nicholas Hunter; Richard T Born; Christopher C Pack
Journal:  J Neurophysiol       Date:  2010-03-24       Impact factor: 2.714

7.  Receptive field dynamics underlying MST neuronal optic flow selectivity.

Authors:  Chen Ping Yu; William K Page; Roger Gaborski; Charles J Duffy
Journal:  J Neurophysiol       Date:  2010-03-24       Impact factor: 2.714

8.  Attention alters feature space in motion processing.

Authors:  Marc Zirnsak; Fred H Hamker
Journal:  J Neurosci       Date:  2010-05-19       Impact factor: 6.167

9.  Responses to random dot motion reveal prevalence of pattern-motion selectivity in area MT.

Authors:  Hironori Kumano; Takanori Uka
Journal:  J Neurosci       Date:  2013-09-18       Impact factor: 6.167

Review 10.  Acting without seeing: eye movements reveal visual processing without awareness.

Authors:  Miriam Spering; Marisa Carrasco
Journal:  Trends Neurosci       Date:  2015-03-10       Impact factor: 13.837

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