Similar Mechanisms Underlie the Detection of Horizontal and Vertical Disparity Corrugations

Witz, Nirel; Zhou, Jiawei; Hess, Robert F.

doi:10.1371/journal.pone.0084846

Cited by 7 publications

(8 citation statements)

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“…It is generally accepted that our visual system processes disparity PLOS COMPUTATIONAL BIOLOGY along at least two [7][8][9][10][11] or more [12] channels that are selective for depth changes at different disparity spatial scales. These disparity spatial scales in turn may rely on distinct sets of luminance spatial channels [13][14][15][16] (as well as second-order channels [49][50][51]). A key insight provided by our work is that depth-selective channels emerge directly from the log-polar, retinocortical transform, since log-polar spatial sampling acts as a "sliding" multi-scale analysis, i.e.…”

Section: Plos Computational Biologymentioning

confidence: 99%

“…It has been proposed that the visual system may process disparity at different disparity spatial scales along separate channels [5], analogous to the channels selective for luminance differences at different luminance spatial frequencies [6]. Using a variety of paradigms to investigate both absolute and relative disparity processing, several authors have provided evidence for at least two [7][8][9][10][11] or more [12] disparity spatial channels for disparity processing, which in turn may rely on distinct sets of luminance spatial channels [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

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Near-optimal combination of disparity across a log-polar scaled visual field

et al. 2020

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The human visual system is foveated: we can see fine spatial details in central vision, whereas resolution is poor in our peripheral visual field, and this loss of resolution follows an approximately logarithmic decrease. Additionally, our brain organizes visual input in polar coordinates. Therefore, the image projection occurring between retina and primary visual cortex can be mathematically described by the log-polar transform. Here, we test and model how this space-variant visual processing affects how we process binocular disparity, a key component of human depth perception. We observe that the fovea preferentially processes disparities at fine spatial scales, whereas the visual periphery is tuned for coarse spatial scales, in line with the naturally occurring distributions of depths and disparities in the real-world. We further show that the visual system integrates disparity information across the visual field, in a near-optimal fashion. We develop a foveated, log-polar model that mimics the processing of depth information in primary visual cortex and that can process disparity directly in the cortical domain representation. This model takes real images as input and recreates the observed topography of human disparity sensitivity. Our findings support the notion that our foveated, binocular visual system has been moulded by the statistics of our visual environment.

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Section: Plos Computational Biologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Near-optimal combination of disparity across a log-polar scaled visual field

et al. 2020

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“…Witz and Hess, 12 using spatially band-pass noise rather than random dots, also concluded that vertical and horizontal stereo corrugations are detected by multiple disparity channels. 13 Thus, the single versus multiple disparity channel hypothesis for explaining the stereoscopic anisotropy cannot be sustained.…”

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confidence: 99%

The Stereoscopic Anisotropy Develops During Childhood

Serrano‐Pedraza

Herbert

Villa-Laso

et al. 2016

Invest. Ophthalmol. Vis. Sci.

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PurposeHuman vision has a puzzling stereoscopic anisotropy: horizontal depth corrugations are easier to detect than vertical depth corrugations. To date, little is known about the function or the underlying mechanism responsible for this anisotropy. Here, we aim to find out whether this anisotropy is independent of age. To answer this, we compare detection thresholds for horizontal and vertical depth corrugations as a function of age.MethodsThe depth corrugations were defined solely by the horizontal disparity of random dot patterns. The disparities depicted a horizontal or vertical sinusoidal depth corrugation of spatial frequency 0.1 cyc/deg. Detection thresholds were obtained using Bayesian adaptive staircases from a total of 159 subjects aged from 3 to 73 years. For each participant we computed the anisotropy index, defined as the log10-ratio of the detection threshold for vertical corrugations divided by that for horizontal.ResultsAnisotropy index was highly variable between individuals but was positive in 87% of the participants. There was a significant correlation between anisotropy index and log-age (r = 0.21, P = 0.008) mainly driven by a significant difference between children and adults. In 67 children aged 3 to 13 years, the mean anisotropy index was 0.34 ± 0.38 (mean ± SD, meaning that vertical thresholds were on average 2.2 times the horizontal ones), compared with 0.59 ± 0.55 in 84 adults aged 18 to 73 years (vertical 3.9 times horizontal). This was mainly driven by a decline in the sensitivity to vertical corrugations. Children had poorer stereoacuity than adults, but had similar sensitivity to adults for horizontal corrugations and were actually more sensitive than adults to vertical corrugations.ConclusionsThe fact that adults show stronger stereo anisotropy than children raises the possibility that visual experience plays a critical role in developing and strengthening the stereo anisotropy.

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“…The pattern of human disparity sensitivity that we observe is well captured by our 136 biologically-motivated model of disparity processing that critically incorporates the 137 log-polar retino-cortical transformation. It is generally accepted that our visual system 138 processes disparity along at least two [2,[4][5][6][7][8][9][10] or more [11][12][13] channels that are 139 selective for depth changes at different spatial scales. A key insight provided by our 140 work is that depth-selective channels emerge directly from the log-polar, retino-cortical 141 transform, since log-polar spatial sampling acts as an "horizontal" multi-scale analysis, 142 i.e.…”

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confidence: 99%

“…• The algorithm presented in [42] did not contain neural noise, which is instead 521 present in the human visual system [28] and was thus incorporated into the 522 current model 523 • In [42] a multi-scale approach was adopted with 11 sub-octave scales in order to 524 recover a large range of disparities (common in computer vision) by using Gabor 525 filters with peak frequency of 0.26 cycles/pixel. In the current model, only 2 scales 526 were employed, since several authors have proposed two spatial frequency channels 527 for disparity processing in humans [4][5][6][7][8][9][10]…”

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confidence: 99%

Near-optimal combination of disparity across a log-polar scaled visual field

Maiello

Chessa

Bex

et al. 2019

Preprint

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AbstractThe human visual system is foveated: we can see fine spatial details in central vision, whereas resolution is poor in our peripheral visual field, and this loss of resolution follows an approximately logarithmic decrease. Additionally, our brain organizes visual input in polar coordinates. Therefore, the image projection occurring between retina and primary visual cortex can be mathematically described by the log-polar transform. Here, we test and model how this space-variant visual processing affects how we process binocular disparity, a key component of human depth perception. We observe that the fovea preferentially processes disparities at fine spatial scales, whereas the visual periphery is tuned for coarse spatial scales, in line with the naturally occurring distributions of depths and disparities in the real-world. We further show that the visual field integrates disparity information across the visual field, in a near-optimal fashion. We develop a foveated, log-polar model that mimics the processing of depth information in primary visual cortex and that can process disparity directly in the cortical domain representation. This model takes real images as input and recreates the observed topography of disparity sensitivity in man. Our findings support the notion that our foveated, binocular visual system has been moulded by the statistics of our visual environment.Author summaryWe investigate how humans perceive depth from binocular disparity at different spatial scales and across different regions of the visual field. We show that small changes in disparity-defined depth are detected best in central vision, whereas peripheral vision best captures the coarser structure of the environment. We also demonstrate that depth information extracted from different regions of the visual field is combined into a unified depth percept. We then construct an image-computable model of disparity processing that takes into account how our brain organizes the visual input at our retinae. The model operates directly in cortical image space, and neatly accounts for human depth perception across the visual field.

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Similar Mechanisms Underlie the Detection of Horizontal and Vertical Disparity Corrugations

Cited by 7 publications

References 17 publications

Near-optimal combination of disparity across a log-polar scaled visual field

Near-optimal combination of disparity across a log-polar scaled visual field

The Stereoscopic Anisotropy Develops During Childhood

Near-optimal combination of disparity across a log-polar scaled visual field

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