Literature DB >> 30948478

Neural Coding for Shape and Texture in Macaque Area V4.

Taekjun Kim1,2, Wyeth Bair1,2, Anitha Pasupathy3,2.   

Abstract

The distinct visual sensations of shape and texture have been studied separately in cortex; therefore, it remains unknown whether separate neuronal populations encode each of these properties or one population carries a joint encoding. We directly compared shape and texture selectivity of individual V4 neurons in awake macaques (1 male, 1 female) and found that V4 neurons lie along a continuum from strong tuning for boundary curvature of shapes to strong tuning for perceptual dimensions of texture. Among neurons tuned to both attributes, tuning for shape and texture were largely separable, with the latter delayed by ∼30 ms. We also found that shape stimuli typically evoked stronger, more selective responses than did texture patches, regardless of whether the latter were contained within or extended beyond the receptive field. These results suggest that there are separate specializations in mid-level cortical processing for visual attributes of shape and texture.SIGNIFICANCE STATEMENT Object recognition depends on our ability to see both the shape of the boundaries of objects and properties of their surfaces. However, neuroscientists have never before examined how shape and texture are linked together in mid-level visual cortex. In this study, we used systematically designed sets of simple shapes and texture patches to probe the responses of individual neurons in the primate visual cortex. Our results provide the first evidence that some cortical neurons specialize in processing shape whereas others specialize in processing textures. Most neurons lie between the ends of this continuum, and in these neurons we find that shape and texture encoding are largely independent.
Copyright © 2019 the authors.

Keywords:  monkey; object recognition; rhesus macaque; shape; texture; ventral visual pathway

Year:  2019        PMID: 30948478      PMCID: PMC6561689          DOI: 10.1523/JNEUROSCI.3073-18.2019

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  61 in total

1.  Hierarchical models of object recognition in cortex.

Authors:  M Riesenhuber; T Poggio
Journal:  Nat Neurosci       Date:  1999-11       Impact factor: 24.884

2.  Responses to contour features in macaque area V4.

Authors:  A Pasupathy; C E Connor
Journal:  J Neurophysiol       Date:  1999-11       Impact factor: 2.714

3.  The spatial transformation of color in the primary visual cortex of the macaque monkey.

Authors:  E N Johnson; M J Hawken; R Shapley
Journal:  Nat Neurosci       Date:  2001-04       Impact factor: 24.884

4.  Separate processing dynamics for texture elements, boundaries and surfaces in primary visual cortex of the macaque monkey.

Authors:  V A Lamme; V Rodriguez-Rodriguez; H Spekreijse
Journal:  Cereb Cortex       Date:  1999-06       Impact factor: 5.357

5.  Cortical area V4 is critical for certain texture discriminations, but this effect is not dependent on attention.

Authors:  W H Merigan
Journal:  Vis Neurosci       Date:  2000 Nov-Dec       Impact factor: 3.241

6.  Shape representation in area V4: position-specific tuning for boundary conformation.

Authors:  A Pasupathy; C E Connor
Journal:  J Neurophysiol       Date:  2001-11       Impact factor: 2.714

7.  Coding of border ownership in monkey visual cortex.

Authors:  H Zhou; H S Friedman; R von der Heydt
Journal:  J Neurosci       Date:  2000-09-01       Impact factor: 6.167

8.  Population coding of shape in area V4.

Authors:  Anitha Pasupathy; Charles E Connor
Journal:  Nat Neurosci       Date:  2002-12       Impact factor: 24.884

9.  Neural mechanisms of cortico-cortical interaction in texture boundary detection: a modeling approach.

Authors:  A Thielscher; H Neumann
Journal:  Neuroscience       Date:  2003       Impact factor: 3.590

10.  Cortical area V4 and its role in the perception of color.

Authors:  C A Heywood; A Gadotti; A Cowey
Journal:  J Neurosci       Date:  1992-10       Impact factor: 6.167

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  10 in total

Review 1.  Visual Functions of Primate Area V4.

Authors:  Anitha Pasupathy; Dina V Popovkina; Taekjun Kim
Journal:  Annu Rev Vis Sci       Date:  2020-06-24       Impact factor: 6.422

Review 2.  Neurophysiological considerations for visual implants.

Authors:  Sabrina J Meikle; Yan T Wong
Journal:  Brain Struct Funct       Date:  2021-11-13       Impact factor: 3.270

Review 3.  Anatomy and physiology of word-selective visual cortex: from visual features to lexical processing.

Authors:  Sendy Caffarra; Iliana I Karipidis; Maya Yablonski; Jason D Yeatman
Journal:  Brain Struct Funct       Date:  2021-10-12       Impact factor: 3.270

4.  Perceptual Texture Dimensions Modulate Neuronal Response Dynamics in Visual Cortical Area V4.

Authors:  Taekjun Kim; Wyeth Bair; Anitha Pasupathy
Journal:  J Neurosci       Date:  2021-12-03       Impact factor: 6.709

Review 5.  Object shape and surface properties are jointly encoded in mid-level ventral visual cortex.

Authors:  Anitha Pasupathy; Taekjun Kim; Dina V Popovkina
Journal:  Curr Opin Neurobiol       Date:  2019-10-04       Impact factor: 6.627

6.  A Stable Population Code for Attention in Prefrontal Cortex Leads a Dynamic Attention Code in Visual Cortex.

Authors:  Adam C Snyder; Byron M Yu; Matthew A Smith
Journal:  J Neurosci       Date:  2021-09-28       Impact factor: 6.167

7.  Interaction of surface pattern and contour shape in the tilt after effects evoked by symmetry.

Authors:  Ko Sakai; Yui Sakata; Ken Kurematsu
Journal:  Sci Rep       Date:  2021-04-13       Impact factor: 4.379

8.  Segmenting surface boundaries using luminance cues.

Authors:  Christopher DiMattina; Curtis L Baker
Journal:  Sci Rep       Date:  2021-05-12       Impact factor: 4.379

9.  Pooling strategies in V1 can account for the functional and structural diversity across species.

Authors:  Victor Boutin; Angelo Franciosini; Frédéric Chavane; Laurent U Perrinet
Journal:  PLoS Comput Biol       Date:  2022-07-21       Impact factor: 4.779

10.  From CAPTCHA to Commonsense: How Brain Can Teach Us About Artificial Intelligence.

Authors:  Dileep George; Miguel Lázaro-Gredilla; J Swaroop Guntupalli
Journal:  Front Comput Neurosci       Date:  2020-10-22       Impact factor: 2.380

  10 in total

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