Representation of the RT-based contrast gain k^-1 for near and far disparities.

<p>Solid line shows the near and the dashed line the far disparities. Asterisks mark disparity values where the contrast gains for near and far stimuli were significantly different (*p<0.05, paired t-test of log transformed data). The data points represent means of 15 participants, error bars show ±SEM.</p

Simple reaction times to cyclopean stimuli reveal that the binocular system is tuned to react faster to near than to far objects

<div><p>Binocular depth perception is an important mechanism to segregate the visual scene for mapping relevant objects in our environment. Convergent evidence from psychophysical and neurophysiological studies have revealed asymmetries between the processing of near (crossed) and far (uncrossed) binocular disparities. The aim of the present study was to test if near or far objects are processed faster and with higher contrast sensitivity in the visual system. We therefore measured the relationship between binocular disparity and simple reaction time (RT) as well as contrast gain based on the contrast-RT function in young healthy adults. RTs were measured to suddenly appearing cyclopean target stimuli, which were checkerboard patterns encoded by depth in dynamic random dot stereograms (DRDS). The DRDS technique allowed us to selectively study the stereoscopic processing system by eliminating all monocular cues. The results showed that disparity and contrast had significant effects on RTs. RTs as a function of disparity followed a U-shaped tuning curve indicating an optimum at around 15 arc min, where RTs were minimal. Surprisingly, the disparity tuning of RT was much less pronounced for far disparities. At the optimal disparity, we measured advantages of about 80 ms and 30 ms for near disparities at low (10%) and high (90%) contrasts, respectively. High contrast always reduced RTs as well as the disparity dependent differences. Furthermore, RT-based contrast gains were higher for near disparities in the range of disparities where RTs were the shortest. These results show that the sensitivity of the human visual system is biased for near versus far disparities and near stimuli can result in faster motor responses, probably because they bear higher biological relevance.</p></div

Distribution of the number of trials with valid RTs for near disparities.

<p>Distribution of the number of trials with valid RTs for near disparities.</p

Measurement of reaction times.

<p>The random dot stereograms at the top of the figure can be viewed using simple red-green goggles. The cyclopean checkerboard appears in near disparity if the red and green filters are in front of the left and right eyes, respectively. Disparity turns into far if the filters are reversed. Note that this is just an illustration of concept for the reader, in the real experiment, left and right channels were separated by circularly polarizing filters and the pattern of random dots was updated at 60 Hz frequency. The images show one frame each of the background (left) and the target (right) condition. Reaction time was measured with millisecond accuracy from the first frame of the target (red tick marks) until the response button was pressed.</p

Mean reaction times for near disparity values at two (10% and 90%) contrast levels.

<p>Each data point represents the mean of 15 participants (at least 133 RTs); error bars show ±SEM. RTs formed statistically homogeneous groups for each contrast level. While the RTs (filled circles) were not significantly different from the shortest mean RT (370 ms for 10% and 317 ms for 90%), RTs signed open circles were not significantly different from the longest mean RTs (495 ms for 10% and 373 ms for 90% contrast), except 7.3 arc min at 10% contrast. Solid black curves show best fit 2^nd order polynomial functions (R² = 0.867, min. value = 16.3 arc min, equation = 186 * <i>x</i>² − 450 * <i>x</i> + 654 or 10% and R² = 0.833, min. value = 20.2 arc min, equation = 79 * <i>x</i>² − 206 * <i>x</i> + 464 for 90% contrast).</p

Mean reaction times for far disparity values at two contrast levels (10% and 90%).

<p>Each data point represents the mean of 15 participants (at least 141 RTs); error bars show ±SEM. Asterisk marks significant difference (p<0.05) found in pairwise comparisons between the lowest disparity and disparity with the shortest mean RT at both contrast. The mean RTs for near disparities (from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0188895#pone.0188895.g002" target="_blank">Fig 2</a>) are superimposed for comparison by gray lines. Second order polynomial fits are represented by solid black curves (R² = 0.592, min. value = 19.8 arc min, equation = for 10% and R² = 0.422, min. value = 19 arc min, equation = for 90% contrast).</p

The difference between ΔRTs to near and far disparity.

<p><b>(A)</b> Differences of mean RT values between 10% and 90% contrast (ΔRT) for near disparities. The data points represent means of 15 participants, error bars show ±SEM. The best fit 2^nd order polynomial function (solid black curve) is shown (R² = 0.821). <b>(B)</b> The same as <b>A</b> for far disparities, (R² = 0.62).</p

Distribution of the number of trials with valid RTs for far disparities.

<p>Distribution of the number of trials with valid RTs for far disparities.</p