Sensitivity to horizontal and vertical sine-wave corrugations defined by binocular disparity: factor analysis of individual differences reveals discrete processes with broad orientation and spatial frequency tuning

Read, J.; Serrano‐Pedraza, Ignacio; Widdall, Michael; Peterzell, David H.

doi:10.1167/16.12.833

Cited by 4 publications

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“…While most studies have used masking paradigms to characterize spatial frequency channels for stereopsis (Julesz and Miller, 1975 ; Yang and Blake, 1991 ; Shioiri et al, 1994 ; Tyler et al, 1994 ; Glennerster and Parker, 1997 ; Prince et al, 1998 ; Serrano-Pedraza et al, 2013 ), another possibility comes from factor analysis of population data (Read et al, 2016 ). The individual differences are then treated as systematic and meaningful, reflecting the true variability of underlying mechanisms rather than random noise (Peterzell, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Characterization of Spatial Frequency Channels Underlying Disparity Sensitivity by Factor Analysis of Population Data

Reynaud

Hess

2017

Front. Comput. Neurosci.

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It has been suggested that at least two mechanisms mediate disparity processing, one for coarse and one for fine disparities. Here we analyze individual differences in our previously measured normative dataset on the disparity sensitivity as a function of spatial frequency of 61 observers to assess the tuning of the spatial frequency channels underlying disparity sensitivity for oblique corrugations (Reynaud et al., 2015). Inter-correlations and factor analysis of the population data revealed two spatial frequency channels for disparity sensitivity: one tuned to high spatial frequencies and one tuned to low spatial frequencies. Our results confirm that disparity is encoded by spatial frequency channels of different sensitivities tuned to different ranges of corrugation frequencies.

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Section: Introductionmentioning

confidence: 99%

Characterization of Spatial Frequency Channels Underlying Disparity Sensitivity by Factor Analysis of Population Data

Reynaud

Hess

2017

Front. Comput. Neurosci.

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Neural Mechanisms That Hide Individual Behavioral Differences: Evidence from Psychophysics and Neuroscience

Billock

2019

Comput Brain Behav

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Thresholds for sine-wave corrugations defined by binocular disparity in random dot stereograms: Factor analysis of individual differences reveals two stereoscopic mechanisms tuned for spatial frequency

et al. 2017

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Threshold functions for sinusoidal depth corrugations typically reach their minimum (highest sensitivity) at spatial frequencies of 0.2-0.4 cycles/degree (cpd), with lower thresholds for horizontal than vertical corrugations at low spatial frequencies. To elucidate spatial frequency and orientation tuning of stereoscopic mechanisms, we measured the disparity sensitivity functions, and used factor analytic techniques to estimate the existence of independent underlying stereo channels. The data set (N = 30 individuals) was for horizontal and vertical corrugations of spatial frequencies ranging from 0.1 to 1.6 cpd. A principal component analysis of disparity sensitivities (log-arcsec) revealed that two significant factors accounted for 70% of the variability. Following Varimax rotation to approximate "simple structure", one factor clearly loaded onto low spatial frequencies (≤0.4 cpd), and a second was tuned to higher spatial frequencies (≥0.8 cpd). Each factor had nearly identical tuning (loadings) for horizontal and vertical patterns. The finding of separate factors for low and high spatial frequencies is consistent with previous studies. The failure to find separate factors for horizontal and vertical corrugations is somewhat surprising because the neuronal mechanisms are believed to be different. Following an oblique rotation (Direct Oblimin), the two factors correlated significantly, suggesting some interdependence rather than full independence between the two factors.

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Sensitivity to horizontal and vertical sine-wave corrugations defined by binocular disparity: factor analysis of individual differences reveals discrete processes with broad orientation and spatial frequency tuning

Cited by 4 publications

References 0 publications

Characterization of Spatial Frequency Channels Underlying Disparity Sensitivity by Factor Analysis of Population Data

Characterization of Spatial Frequency Channels Underlying Disparity Sensitivity by Factor Analysis of Population Data

Neural Mechanisms That Hide Individual Behavioral Differences: Evidence from Psychophysics and Neuroscience

Thresholds for sine-wave corrugations defined by binocular disparity in random dot stereograms: Factor analysis of individual differences reveals two stereoscopic mechanisms tuned for spatial frequency

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