Figure-ground responsive fields of monkey V4 neurons estimated from natural image patches.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2022
2022
Historique:
received:
14
05
2021
accepted:
04
05
2022
entrez:
16
6
2022
pubmed:
17
6
2022
medline:
22
6
2022
Statut:
epublish
Résumé
Neurons in visual area V4 modulate their responses depending on the figure-ground (FG) organization in natural images containing a variety of shapes and textures. To clarify whether the responses depend on the extents of the figure and ground regions in and around the classical receptive fields (CRFs) of the neurons, we estimated the spatial extent of local figure and ground regions that evoked FG-dependent responses (RF-FGs) in natural images and their variants. Specifically, we applied the framework of spike triggered averaging (STA) to the combinations of neural responses and human-marked segmentation images (FG labels) that represent the extents of the figure and ground regions in the corresponding natural image stimuli. FG labels were weighted by the spike counts in response to the corresponding stimuli and averaged over. The bias due to the nonuniformity of FG labels was compensated by subtracting the ensemble average of FG labels from the weighted average. Approximately 50% of the neurons showed effective RF-FGs, and a large number exhibited structures that were similar to those observed in virtual neurons with ideal FG-dependent responses. The structures of the RF-FGs exhibited a subregion responsive to a preferred side (figure or ground) around the CRF center and a subregion responsive to a non-preferred side in the surroundings. The extents of the subregions responsive to figure were smaller than those responsive to ground in agreement with the Gestalt rule. We also estimated RF-FG by an adaptive filtering (AF) method, which does not require spherical symmetry (whiteness) in stimuli. RF-FGs estimated by AF and STA exhibited similar structures, supporting the veridicality of the proposed STA. To estimate the contribution of nonlinear processing in addition to linear processing, we estimated nonlinear RF-FGs based on the framework of spike triggered covariance (STC). The analyses of the models based on STA and STC did not show inconsiderable contribution of nonlinearity, suggesting spatial variance of FG regions. The results lead to an understanding of the neural responses that underlie the segregation of figures and the construction of surfaces in intermediate-level visual areas.
Identifiants
pubmed: 35709141
doi: 10.1371/journal.pone.0268650
pii: PONE-D-21-15930
pmc: PMC9202882
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0268650Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
Références
PLoS One. 2008 Aug 26;3(8):e3060
pubmed: 18725977
PLoS One. 2020 Jun 26;15(6):e0235128
pubmed: 32589671
Neuron. 2005 Mar 3;45(5):781-91
pubmed: 15748852
Vision Res. 2014 Oct;103:116-26
pubmed: 25175115
J Vis. 2006 Apr 28;6(4):414-28
pubmed: 16889478
Neuron. 2012 Apr 12;74(1):12-29
pubmed: 22500626
Vision Res. 1990;30(2):249-54
pubmed: 2309459
Front Psychol. 2018 Sep 06;9:1681
pubmed: 30237781
J Neurosci. 2010 May 26;30(21):7269-80
pubmed: 20505093
Network. 2001 May;12(2):199-213
pubmed: 11405422
J Neurosci. 2000 Mar 15;20(6):2315-31
pubmed: 10704507
J Neurophysiol. 2001 Oct;86(4):2011-28
pubmed: 11600658
Elife. 2018 Dec 20;7:
pubmed: 30570484
J Vis. 2006 Jul 17;6(4):484-507
pubmed: 16889482
Annu Rev Neurosci. 2013 Jul 8;36:103-20
pubmed: 23841838
Curr Biol. 2011 Feb 22;21(4):288-93
pubmed: 21315595
J Neurophysiol. 2001 Nov;86(5):2505-19
pubmed: 11698538
J Neurosci. 2012 Feb 1;32(5):1560-76
pubmed: 22302799
Brain Res. 1973 Apr 27;53(2):422-7
pubmed: 4196224
Proc Natl Acad Sci U S A. 1993 Nov 1;90(21):9785-90
pubmed: 8234315
Neuron. 2012 Jul 12;75(1):143-56
pubmed: 22794268
J Neurophysiol. 1993 Apr;69(4):1091-117
pubmed: 8492151
J Vis. 2002;2(1):12-24
pubmed: 12678594
PLoS One. 2010 May 19;5(5):e10705
pubmed: 20502718
J Neurophysiol. 1987 Dec;58(6):1187-211
pubmed: 3437330
Nat Neurosci. 2002 Jul;5(7):665-70
pubmed: 12068303
Sci Rep. 2019 Mar 7;9(1):3791
pubmed: 30846783
Neuron. 2014 May 7;82(3):682-94
pubmed: 24811385
Exp Brain Res. 2008 Jul;189(1):109-20
pubmed: 18506435
Neural Netw. 2012 Sep;33:257-74
pubmed: 22732320
Cereb Cortex. 2016 Oct;26(10):3964-76
pubmed: 27522074
Elife. 2020 Nov 19;9:
pubmed: 33211007
J Neurophysiol. 1999 Nov;82(5):2490-502
pubmed: 10561421
Neuron. 1999 Sep;24(1):19-29, 111-25
pubmed: 10677024
J Neurosci. 2004 Aug 4;24(31):6991-7006
pubmed: 15295035
Neuron. 2007 Nov 8;56(3):560-73
pubmed: 17988638
J Neurosci. 2011 Mar 16;31(11):4012-24
pubmed: 21411644
Front Psychol. 2015 Nov 03;6:1685
pubmed: 26579057
Vision Res. 2000;40(7):855-71
pubmed: 10683461
J Neurosci. 2014 Jun 18;34(25):8570-84
pubmed: 24948811
Vision Res. 2000;40(15):1955-67
pubmed: 10828464
Sci Rep. 2021 Apr 13;11(1):8024
pubmed: 33850220
Annu Rev Vis Sci. 2020 Sep 15;6:363-385
pubmed: 32580663
J Neurophysiol. 2019 Mar 1;121(3):1059-1077
pubmed: 30699004
Neural Comput. 2014 Oct;26(10):2135-62
pubmed: 25058707
J Vis. 2007 Jun 08;7(8):2
pubmed: 17685809
Neuron. 2005 Jun 16;46(6):945-56
pubmed: 15953422