Cortical sensitivity to visual features in natural scenes.

A central hypothesis concerning sensory processing is that the neuronal circuits are specifically adapted to represent natural stimuli efficiently. Here we show a novel effect in cortical coding of natural images. Using spike-triggered average or spike-triggered covariance analyses, we first identif...

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Main Authors: Gidon Felsen, Jon Touryan, Feng Han, Yang Dan
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2005-10-01
Series:PLoS Biology
Online Access:https://doi.org/10.1371/journal.pbio.0030342
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spelling doaj-b76580875c594c5bb4b65f18660e192c2021-07-02T17:09:40ZengPublic Library of Science (PLoS)PLoS Biology1544-91731545-78852005-10-01310e34210.1371/journal.pbio.0030342Cortical sensitivity to visual features in natural scenes.Gidon FelsenJon TouryanFeng HanYang DanA central hypothesis concerning sensory processing is that the neuronal circuits are specifically adapted to represent natural stimuli efficiently. Here we show a novel effect in cortical coding of natural images. Using spike-triggered average or spike-triggered covariance analyses, we first identified the visual features selectively represented by each cortical neuron from its responses to natural images. We then measured the neuronal sensitivity to these features when they were present in either natural images or random stimuli. We found that in the responses of complex cells, but not of simple cells, the sensitivity was markedly higher for natural images than for random stimuli. Such elevated sensitivity leads to increased detectability of the visual features and thus an improved cortical representation of natural scenes. Interestingly, this effect is due not to the spatial power spectra of natural images, but to their phase regularities. These results point to a distinct visual-coding strategy that is mediated by contextual modulation of cortical responses tuned to the spatial-phase structure of natural scenes.https://doi.org/10.1371/journal.pbio.0030342
collection DOAJ
language English
format Article
sources DOAJ
author Gidon Felsen
Jon Touryan
Feng Han
Yang Dan
spellingShingle Gidon Felsen
Jon Touryan
Feng Han
Yang Dan
Cortical sensitivity to visual features in natural scenes.
PLoS Biology
author_facet Gidon Felsen
Jon Touryan
Feng Han
Yang Dan
author_sort Gidon Felsen
title Cortical sensitivity to visual features in natural scenes.
title_short Cortical sensitivity to visual features in natural scenes.
title_full Cortical sensitivity to visual features in natural scenes.
title_fullStr Cortical sensitivity to visual features in natural scenes.
title_full_unstemmed Cortical sensitivity to visual features in natural scenes.
title_sort cortical sensitivity to visual features in natural scenes.
publisher Public Library of Science (PLoS)
series PLoS Biology
issn 1544-9173
1545-7885
publishDate 2005-10-01
description A central hypothesis concerning sensory processing is that the neuronal circuits are specifically adapted to represent natural stimuli efficiently. Here we show a novel effect in cortical coding of natural images. Using spike-triggered average or spike-triggered covariance analyses, we first identified the visual features selectively represented by each cortical neuron from its responses to natural images. We then measured the neuronal sensitivity to these features when they were present in either natural images or random stimuli. We found that in the responses of complex cells, but not of simple cells, the sensitivity was markedly higher for natural images than for random stimuli. Such elevated sensitivity leads to increased detectability of the visual features and thus an improved cortical representation of natural scenes. Interestingly, this effect is due not to the spatial power spectra of natural images, but to their phase regularities. These results point to a distinct visual-coding strategy that is mediated by contextual modulation of cortical responses tuned to the spatial-phase structure of natural scenes.
url https://doi.org/10.1371/journal.pbio.0030342
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