Data for Figures 2-4

Data for Figures 2-

Similar Mechanisms Underlie the Detection of Horizontal and Vertical Disparity Corrugations

<div><p>Our aim was to compare sensitivity for horizontal and vertical disparity corrugations and to resolve whether these stimuli are processed by similar or radically different underlying mechanisms. We measure global disparity sensitivity as a function of carrier spatial frequency for equi-detectable carriers and found a similar optimal carrier relationship for vertical and horizontal stimuli. Sensitivity as a function of corrugation spatial frequency for stimuli of comparable spatial summation and composed of optimal, equi-detectable narrowband carriers did not significantly differ for vertical and horizontal stimuli. A small anisotropy was revealed when fixed, high contrast broadband carriers were used. In a separate discrimination-at-threshold experiment, multiple mechanisms of similar tuning were revealed to underlie the detection of both vertical and horizontal disparity corrugations. We conclude that the processing of the horizontal and vertical disparity corrugations occurs along similar lines.</p></div

Stereo-pairs of the stimulus.

<p>Stimuli used for foveal global stereo sensitivity of vertical (A) and horizontal (B) corrugations. The foveal stimulus had a sigma of 9°. The luminance-defined carrier is band-pass noise whereas the stereo corrugation is a 1-D vertical (A) or horizontal(B) sinusoid for the foveal stimulus.</p

Disparity corrugation sensitivity for different carriers.

<p>Averaged optimum disparity corrugation sensitivity (min⁻¹) is plotted against corrugation disparity spatial frequency (c/d) for a foveal stimulus whose number of spatial cycles did not vary with corrugation disparity spatial frequency. Disparity sensitivity functions (DSFs) are measured with the carrier consisting of either narrowband (1 octave) filtered noise set to 7 times its contrast detection threshold (7X CDT), broadband (6 octaves) filtered noise set to 7X CDT, or broadband (6 octaves) filtered noise set to 80% contrast for vertically oriented sine wave corrugations in panel A and horizontally oriented sine wave corrugations in panel B. In panels A and B, sensitivity to the narrowband noise carrier (1 octave) is represented by black diamonds with negative standard deviations and sensitivity to the broadband noise carrier (6 octaves) is represented by white circles (7X CDT) and white squares (80% contrast) with positive standard deviations. Panel C plots the disparity sensitivity function (DSF) for both vertical and horizontal corrugations whose carrier consisted of broadband (6 octaves) filtered noise set to 7X CDT. Panel D plots the DSF for both vertical and horizontal corrugations whose carrier consisted of broadband (6 octaves) filtered noise set to 80% contrast. For both panels C and D, the black circles represent sensitivity for vertically oriented sine-wave corrugations with negative standard deviations. The white circles represent sensitivity for horizontally oriented sine-wave corrugations with positive standard deviations.</p

Discrimination of disparity corrugation spatial frequency at detection threshold.

<p>Foveal results from discrimination at detection threshold for 3 different pairs of horizontally oriented corrugation disparity spatial frequencies: 0.25 vs. 0.5 c/d (A), 0.25 vs. 1 c/d (B), and 1 vs. 4 c/d (C). The detection results from the 2×2 AFC paradigm are shown by small filled square stimuli and the discrimination results by small filled triangle symbols. The estimated threshold is shown by larger unfilled symbols. The ‘*’ indicates that perfect discrimination is possible at detection threshold as the thresholds for detection and discrimination are statistically indistinguishable (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084846#pone.0084846.s002" target="_blank">Text S2</a>).</p

Optimum carriers for horizontal and vertical corrugations.

<p>Optimum carrier luminance spatial frequency (c/d) is plotted against corrugation disparity spatial frequency (c/d) as a function of the average across subjects including the standard deviation. Panel A represents optimum carriers across a range of vertically oriented sine-wave corrugations while panel B represents optimum carriers across a range of horizontally oriented sine-wave corrugations. The solid bilinear line in both panels indicates the line of best fit for the data.</p

Median parameter estimates obtained by fitting to the bootstrapped pedestal masking data, with 95% confidence intervals.

<p>These values differ slightly from those in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150942#pone.0150942.t002" target="_blank">Table 2</a> as those were obtained by fitting to the empirical data.</p

Parameters (in dB) obtained by fitting the LAM model to simulated nonlinear model (NLM) data, that were generated based on each observer’s dipper function.

<p>Standard errors provided are calculated from the bootstrap distributions. Predictions for these parameters are shown by the solid curves in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150942#pone.0150942.g006" target="_blank">Fig 6</a>. The mean across observers is reported with the standard error.</p

Efficiency of an observer who combines signals over multiple channels by picking the maximum, expressed relative to that of a linear ideal observer.

<p>We obtained by simulating the detection of various levels of signal (-42 to 36 dB in 3 dB steps) by independently noisy channels with different standard deviations (6 to 18 dB in 3 dB steps). We simulated 5,000 trials per combination of signal and noise level, both for a system where the outputs were summed (ideal) before comparison between the two intervals and for a system where the max() was taken. The data from this simulation were fit by a psychometric function (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150942#sec006" target="_blank">Methods</a>), and then the average efficiency of the max() observer was calculated relative to the ideal.</p

Median psychometric slopes obtained from bootstrapping plotted as a function of pedestal mask contrast for each observer.

<p>The error bars show 95% confidence intervals. As in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150942#pone.0150942.g003" target="_blank">Fig 3</a>, the curves show the predictions from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150942#pone.0150942.e021" target="_blank">Eq (11)</a>.</p