Literature DB >> 23791199

The fine structure of shape tuning in area V4.

Anirvan S Nandy1, Tatyana O Sharpee, John H Reynolds, Jude F Mitchell.   

Abstract

Previous studies have shown that neurons in area V4 are involved in the processing of shapes of intermediate complexity and are sensitive to curvature. These studies also suggest that curvature-tuned neurons are position invariant. We sought to examine the mechanisms that endow V4 neurons with these properties. Consistent with previous studies, we found that response rank order to the most- and least-preferred stimuli was preserved throughout the receptive field. However, a fine-grained analysis of shape tuning revealed a surprising result: V4 neurons tuned to highly curved shapes exhibit very limited translation invariance. At a fine spatial scale, these neurons exhibit local variation in orientation. In contrast, neurons that prefer straight contours exhibit spatially invariant orientation-tuning and homogenous fine-scale orientation maps. Both of these patterns are consistent with a simple orientation-pooling model, with tuning for straight or curved shapes resulting, respectively, from pooling of homogenous or heterogeneous orientation signals inherited from early visual areas.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23791199      PMCID: PMC3694358          DOI: 10.1016/j.neuron.2013.04.016

Source DB:  PubMed          Journal:  Neuron        ISSN: 0896-6273            Impact factor:   17.173


  41 in total

1.  Responses to contour features in macaque area V4.

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

2.  Synergy in a neural code.

Authors:  N Brenner; S P Strong; R Koberle; W Bialek; R R de Ruyter van Steveninck
Journal:  Neural Comput       Date:  2000-07       Impact factor: 2.026

3.  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

4.  Local sensitivity to stimulus orientation and spatial frequency within the receptive fields of neurons in visual area 2 of macaque monkeys.

Authors:  X Tao; B Zhang; E L Smith; S Nishimoto; I Ohzawa; Y M Chino
Journal:  J Neurophysiol       Date:  2011-11-23       Impact factor: 2.714

5.  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

6.  Equiluminance cells in visual cortical area v4.

Authors:  Brittany N Bushnell; Philip J Harding; Yoshito Kosai; Wyeth Bair; Anitha Pasupathy
Journal:  J Neurosci       Date:  2011-08-31       Impact factor: 6.167

7.  A sparse object coding scheme in area V4.

Authors:  Eric T Carlson; Russell J Rasquinha; Kechen Zhang; Charles E Connor
Journal:  Curr Biol       Date:  2011-02-22       Impact factor: 10.834

8.  Selectivity and tolerance ("invariance") both increase as visual information propagates from cortical area V4 to IT.

Authors:  Nicole C Rust; James J Dicarlo
Journal:  J Neurosci       Date:  2010-09-29       Impact factor: 6.167

9.  Retinal origin of orientation maps in visual cortex.

Authors:  Se-Bum Paik; Dario L Ringach
Journal:  Nat Neurosci       Date:  2011-05-29       Impact factor: 24.884

10.  Functional organization for color and orientation in macaque V4.

Authors:  Hisashi Tanigawa; Haidong D Lu; Anna W Roe
Journal:  Nat Neurosci       Date:  2010-11-14       Impact factor: 24.884

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  37 in total

1.  Multimap formation in visual cortex.

Authors:  Rishabh Jain; Rachel Millin; Bartlett W Mel
Journal:  J Vis       Date:  2015       Impact factor: 2.240

2.  Receptive field focus of visual area V4 neurons determines responses to illusory surfaces.

Authors:  Michele A Cox; Michael C Schmid; Andrew J Peters; Richard C Saunders; David A Leopold; Alexander Maier
Journal:  Proc Natl Acad Sci U S A       Date:  2013-10-01       Impact factor: 11.205

3.  'Artiphysiology' reveals V4-like shape tuning in a deep network trained for image classification.

Authors:  Dean A Pospisil; Anitha Pasupathy; Wyeth Bair
Journal:  Elife       Date:  2018-12-20       Impact factor: 8.140

4.  Sparsey™: event recognition via deep hierarchical sparse distributed codes.

Authors:  Gerard J Rinkus
Journal:  Front Comput Neurosci       Date:  2014-12-15       Impact factor: 2.380

5.  Representing "stuff" in visual cortex.

Authors:  Corey M Ziemba; Jeremy Freeman
Journal:  Proc Natl Acad Sci U S A       Date:  2015-01-13       Impact factor: 11.205

6.  Image statistics underlying natural texture selectivity of neurons in macaque V4.

Authors:  Gouki Okazawa; Satohiro Tajima; Hidehiko Komatsu
Journal:  Proc Natl Acad Sci U S A       Date:  2014-12-22       Impact factor: 11.205

7.  Sample skewness as a statistical measurement of neuronal tuning sharpness.

Authors:  Jason M Samonds; Brian R Potetz; Tai Sing Lee
Journal:  Neural Comput       Date:  2014-02-20       Impact factor: 2.026

8.  Curvature domains in V4 of macaque monkey.

Authors:  Jia Ming Hu; Xue Mei Song; Qiannan Wang; Anna Wang Roe
Journal:  Elife       Date:  2020-11-19       Impact factor: 8.140

9.  Curvature-processing domains in primate V4.

Authors:  Rendong Tang; Qianling Song; Ying Li; Rui Zhang; Xingya Cai; Haidong D Lu
Journal:  Elife       Date:  2020-11-19       Impact factor: 8.140

10.  Contour Curvature As an Invariant Code for Objects in Visual Area V4.

Authors:  Yasmine El-Shamayleh; Anitha Pasupathy
Journal:  J Neurosci       Date:  2016-05-18       Impact factor: 6.167

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