Additional file 4 of TRPM4 regulates hilar mossy cell loss in temporal lobe epilepsy

Additional file 4. Individual data points

Additional file 2 of TRPM4 regulates hilar mossy cell loss in temporal lobe epilepsy

Additional file 2. Patched neurons in the hilus are SATB1 positive. Representative confocal images of biocytinfilled WTand Trpm4−/−MCs counterstained with SATB1. Note that the biocytin filled cells are also SATB1 positive. Scale bar 5 μm. Image of WT neuronwas modified from previous publication [6]

Additional file 5 of TRPM4 regulates hilar mossy cell loss in temporal lobe epilepsy

Additional file 5. Summary of statistics

Additional file 3 of TRPM4 regulates hilar mossy cell loss in temporal lobe epilepsy

Additional file 3. Power spectrum of epileptic WT and Trpm4−/− mice is not different.Power spectral density plot of epileptic WTand Trpm4−/−mice during exploration.Statistics showing theta, alpha, betaand gammapower in epileptic WTand Trpm4−/−mice. n = 6 for WT and 6 for Trpm4−/− mice

Additional file 1 of TRPM4 regulates hilar mossy cell loss in temporal lobe epilepsy

Additional file 1. SATB1 and Glur2/3 are colocalized in the hilus. Representative 10xand 60xconfocal images of double immunofluorescence staining for SATB1and GLuR2/3.Left, percentage of SATB1 positive neurons that express GLuR2/3. Right, percentage of GLuR2/3 positive neurons that express SATB1. n = 211 neurons from 2 mice. Scale bar 100 μmand 5 μm

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

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

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

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

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