Literature DB >> 12426571

Population coding of shape in area V4.

Anitha Pasupathy1, Charles E Connor.   

Abstract

Shape is represented in the visual system by patterns of activity across populations of neurons. We studied the population code for shape in area V4 of macaque monkeys, which is part of the ventral (object-related) pathway in primate visual cortex. We have previously found that many macaque V4 neurons are tuned for the curvature and object-centered position of boundary fragments (such as 'concavity on the right'). Here we tested the hypothesis that populations of such cells represent complete shapes as aggregates of boundary fragments. To estimate the population representation of a given shape, we scaled each cell's tuning peak by its response to that shape, summed across cells and smoothed. The resulting population response surface contained 3-8 peaks that represented major boundary features and could be used to reconstruct (approximately) the original shape. This exemplifies how a multi-peaked neural population response can represent a complex stimulus in terms of its constituent elements.

Mesh:

Year:  2002        PMID: 12426571     DOI: 10.1038/nn972

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


  135 in total

1.  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

2.  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

3.  Estimation of 3D shape from image orientations.

Authors:  Roland W Fleming; Daniel Holtmann-Rice; Heinrich H Bülthoff
Journal:  Proc Natl Acad Sci U S A       Date:  2011-12-06       Impact factor: 11.205

4.  Characterizing responses of translation-invariant neurons to natural stimuli: maximally informative invariant dimensions.

Authors:  Michael Eickenberg; Ryan J Rowekamp; Minjoon Kouh; Tatyana O Sharpee
Journal:  Neural Comput       Date:  2012-06-26       Impact factor: 2.026

Review 5.  Uncovering the visual "alphabet": advances in our understanding of object perception.

Authors:  Leslie G Ungerleider; Andrew H Bell
Journal:  Vision Res       Date:  2010-10-28       Impact factor: 1.886

6.  Internal curvature signal and noise in low- and high-level vision.

Authors:  Timothy D Sweeny; Marcia Grabowecky; Yee Joon Kim; Satoru Suzuki
Journal:  J Neurophysiol       Date:  2011-01-05       Impact factor: 2.714

7.  Medial axis shape coding in macaque inferotemporal cortex.

Authors:  Chia-Chun Hung; Eric T Carlson; Charles E Connor
Journal:  Neuron       Date:  2012-06-21       Impact factor: 17.173

8.  Visual saliency and texture segregation without feature gradient.

Authors:  Ohad Ben-Shahar
Journal:  Proc Natl Acad Sci U S A       Date:  2006-10-09       Impact factor: 11.205

9.  Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences.

Authors:  Carlos R Ponce; Will Xiao; Peter F Schade; Till S Hartmann; Gabriel Kreiman; Margaret S Livingstone
Journal:  Cell       Date:  2019-05-02       Impact factor: 41.582

10.  Selective mechanisms for simple contours revealed by compound adaptation.

Authors:  Sarah Hancock; Jonathan W Peirce
Journal:  J Vis       Date:  2008-06-03       Impact factor: 2.240

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