01, p = 0.14). These results are in agreement with a previous report by Ringach et al. (2002)

observing only minimal differences in tuning strength across cortical layers, but a high diversity of tuning width and spontaneous firing in all layers (see also Schiller et al., 1976). Analysis of the reliability of neuronal responses, or Fano factor, yielded similar C59 wnt cost results across layers, with only a slight tendency for neurons in the granular layer to exhibit decreased values (p > 0.1, Wilcoxon sign-ranked test). Altogether, these analyses argue that the shape of orientation tuning curves and response reliability cannot explain the laminar dependence of noise correlations. Figure 4A shows the laminar distribution of correlations—whereas correlation coefficients in supragranular and infragranular layers are skewed toward high values, those in the granular layer

have much lower values. Based on our CSD-defined laminar regions, we were able to record from pairs of cells in a given layer up to 400 μm away, and hence investigated the effect of distance between laminar contacts on correlated variability. By computing the number of cell pairs as a function of electrode contact distance across layers, we found that ∼78% of cell pairs were within 200 μm (Figure 4B). In addition, the mean correlation coefficient did not depend on contact distance irrespective of cortical layer (Figure 4C; p > 0.45; Wilcoxon rank sum test). We also calculated noise correlations for neuron pairs originating RO4929097 chemical structure from different layers and found

that correlations between neurons in the granular layer and those in other cortical layers (SG-G: 0.12 ± 0.03; IG-G: 0.10 ± 0.03) were significantly weaker. When we computed correlations between neurons in supragranular and infragranular layers we observed significantly those higher values (SG-IG: 0.21 ± 0.03; one-way ANOVA, F (2, 156) = 12.73, p = 10−5; post hoc multicomparison, Tukey’s least significant difference). This result is consistent with our hypothesis that there is a greater fraction of common input in the output layers possibly due to the influence of long-range horizontal connections (see Figure S2 for a summary of interlayer rSC). One possible confound is eye movements during fixation. Indeed, eye movements could modulate the firing rates of all the neurons recorded simultaneously to possibly increase correlated variability due to an increase in common input. Although the eye movement modulation of firing rates has not been demonstrated to depend on cortical layer, one cannot totally exclude the possibility that this modulation could be larger in supragranular and infragranular layers of V1 to contribute to an increase in noise correlations. However, if eye movements were a confounding variable in our study, they would equally affect correlations in all layers.