Population coding of figure and ground in natural image patches by V4 neurons.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2020
Historique:
received: 08 03 2020
accepted: 08 06 2020
entrez: 27 6 2020
pubmed: 27 6 2020
medline: 10 9 2020
Statut: epublish

Résumé

Segmentation of a natural scene into objects and background is a fundamental but challenging task for recognizing objects. Investigating intermediate-level visual cortical areas with a focus on local information is a crucial step towards understanding the formation of the cortical representations of figure and ground. We examined the activity of a population of macaque V4 neurons during the presentation of natural image patches and their respective variations. The natural image patches were optimized to exclude the influence of global context but included various characteristics of local stimulus. Around one fourth of the patch-responsive V4 neurons exhibited significant modulation of firing activity that was dependent on the positional relation between the figural region of the stimulus and the classical receptive field of the neuron. However, the individual neurons showed low consistency in figure-ground modulation across a variety of image patches (55-62%), indicating that individual neurons were capable of correctly signaling figure and ground only for a limited number of stimuli. We examined whether integration of the activity of multiple neurons enabled higher consistency across a variety of natural patches by training a support vector machine to classify figure and ground of the stimuli from the population firing activity. The integration of the activity of a few tens of neurons yielded discrimination accuracy much greater than that of single neurons (up to 85%), suggesting a crucial role of population coding for figure-ground discrimination in natural images.

Identifiants

pubmed: 32589671
doi: 10.1371/journal.pone.0235128
pii: PONE-D-20-06730
pmc: PMC7319327
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0235128

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Yukako Yamane (Y)

Graduate School of Frontiers Biosciences, Osaka University, Osaka, Japan.
Japan Society for Promotion of Science, Tokyo, Japan.

Atsushi Kodama (A)

Department of Computer Science, University of Tsukuba, Ibaraki, Japan.

Motofumi Shishikura (M)

Department of Computer Science, University of Tsukuba, Ibaraki, Japan.

Kouji Kimura (K)

Department of Computer Science, University of Tsukuba, Ibaraki, Japan.

Hiroshi Tamura (H)

Graduate School of Frontiers Biosciences, Osaka University, Osaka, Japan.
Center for Information and Neural Networks, Osaka, Japan.

Ko Sakai (K)

Department of Computer Science, University of Tsukuba, Ibaraki, Japan.

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