Contextual interactions in grating plaid configurations are explained by natural image statistics and neural modeling

Processing natural scenes requires the visual system to integrate local features into global object descriptions. To achieve coherent representations, the human brain uses statistical dependencies to guide weighting of local feature conjunctions. Pairwise interactions among feature detectors in earl...

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Main Authors: Udo Alexander Ernst, Alina Schiffer, Malte Persike, Günter Meinhardt
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-10-01
Series:Frontiers in Systems Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnsys.2016.00078/full
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spelling doaj-1aa375f5514a4d28b6d8e33b67f85c192020-11-24T23:27:11ZengFrontiers Media S.A.Frontiers in Systems Neuroscience1662-51372016-10-011010.3389/fnsys.2016.00078188332Contextual interactions in grating plaid configurations are explained by natural image statistics and neural modelingUdo Alexander Ernst0Alina Schiffer1Malte Persike2Günter Meinhardt3University of BremenUniversity of BremenJohannes Gutenberg University MainzJohannes Gutenberg University MainzProcessing natural scenes requires the visual system to integrate local features into global object descriptions. To achieve coherent representations, the human brain uses statistical dependencies to guide weighting of local feature conjunctions. Pairwise interactions among feature detectors in early visual areas may form the early substrate of these local feature bindings. To investigate local interaction structures in visual cortex, we combined psychophysical experiments with computational modeling and natural scene analysis. We first measured contrast thresholds for 2x2 grating patch arrangements (plaids), which differed in spatial frequency composition (low, high or mixed), number of grating patch co-alignments (0, 1 or 2), and inter-patch distances (1° and 2° of visual angle). Contrast thresholds for the different configurations were compared to the prediction of probability summation (PS) among detector families tuned to the four retinal positions. For 1° distance the thresholds for all configurations were larger than predicted by PS, indicating inhibitory interactions. For 2° distance, thresholds were significantly lower compared to PS when the plaids were homogeneous in spatial frequency and orientation, but not when spatial frequencies were mixed or there was at least one misalignment. Next, we constructed a neural population model with horizontal laminar structure, which reproduced the detection thresholds after adaptation of connection weights. Consistent with prior work, contextual interactions were medium-range inhibition and long-range, orientation-specific excitation. However, inclusion of orientation-specific, inhibitory interactions between populations with different spatial frequency preferences were crucial for explaining detection thresholds. Finally, for all plaid configurations we computed their likelihood of occurrence in natural images. The likelihoods turned out to be inversely related to the detection thresholds obtained at larger inter-patch distances. However, likelihoods were almost independent of inter-patch distance, implying that natural image statistics could not explain the crowding-like results at short distances. This failure of natural image statistics to resolve the patch distance modulation of plaid visibility remains a challenge to the approach.http://journal.frontiersin.org/Journal/10.3389/fnsys.2016.00078/fullVisual CortexVisual PerceptionFeature integrationnatural image statisticsnetwork modelContextual interactions
collection DOAJ
language English
format Article
sources DOAJ
author Udo Alexander Ernst
Alina Schiffer
Malte Persike
Günter Meinhardt
spellingShingle Udo Alexander Ernst
Alina Schiffer
Malte Persike
Günter Meinhardt
Contextual interactions in grating plaid configurations are explained by natural image statistics and neural modeling
Frontiers in Systems Neuroscience
Visual Cortex
Visual Perception
Feature integration
natural image statistics
network model
Contextual interactions
author_facet Udo Alexander Ernst
Alina Schiffer
Malte Persike
Günter Meinhardt
author_sort Udo Alexander Ernst
title Contextual interactions in grating plaid configurations are explained by natural image statistics and neural modeling
title_short Contextual interactions in grating plaid configurations are explained by natural image statistics and neural modeling
title_full Contextual interactions in grating plaid configurations are explained by natural image statistics and neural modeling
title_fullStr Contextual interactions in grating plaid configurations are explained by natural image statistics and neural modeling
title_full_unstemmed Contextual interactions in grating plaid configurations are explained by natural image statistics and neural modeling
title_sort contextual interactions in grating plaid configurations are explained by natural image statistics and neural modeling
publisher Frontiers Media S.A.
series Frontiers in Systems Neuroscience
issn 1662-5137
publishDate 2016-10-01
description Processing natural scenes requires the visual system to integrate local features into global object descriptions. To achieve coherent representations, the human brain uses statistical dependencies to guide weighting of local feature conjunctions. Pairwise interactions among feature detectors in early visual areas may form the early substrate of these local feature bindings. To investigate local interaction structures in visual cortex, we combined psychophysical experiments with computational modeling and natural scene analysis. We first measured contrast thresholds for 2x2 grating patch arrangements (plaids), which differed in spatial frequency composition (low, high or mixed), number of grating patch co-alignments (0, 1 or 2), and inter-patch distances (1° and 2° of visual angle). Contrast thresholds for the different configurations were compared to the prediction of probability summation (PS) among detector families tuned to the four retinal positions. For 1° distance the thresholds for all configurations were larger than predicted by PS, indicating inhibitory interactions. For 2° distance, thresholds were significantly lower compared to PS when the plaids were homogeneous in spatial frequency and orientation, but not when spatial frequencies were mixed or there was at least one misalignment. Next, we constructed a neural population model with horizontal laminar structure, which reproduced the detection thresholds after adaptation of connection weights. Consistent with prior work, contextual interactions were medium-range inhibition and long-range, orientation-specific excitation. However, inclusion of orientation-specific, inhibitory interactions between populations with different spatial frequency preferences were crucial for explaining detection thresholds. Finally, for all plaid configurations we computed their likelihood of occurrence in natural images. The likelihoods turned out to be inversely related to the detection thresholds obtained at larger inter-patch distances. However, likelihoods were almost independent of inter-patch distance, implying that natural image statistics could not explain the crowding-like results at short distances. This failure of natural image statistics to resolve the patch distance modulation of plaid visibility remains a challenge to the approach.
topic Visual Cortex
Visual Perception
Feature integration
natural image statistics
network model
Contextual interactions
url http://journal.frontiersin.org/Journal/10.3389/fnsys.2016.00078/full
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