The grid location was marked as significant if the spatial Z score exceeded the significance level of 0.05 (corrected for 25 multiple comparisons; see Figure S1A). Spatially significant grid locations for example neurons are marked with “x” or

numerals in Figures 2 and 3. For each spatially significant grid location, we next determined whether the neuron was significantly selective to the composite stimuli at that location. We calculated a Z score for each stimulus: Zshape(x,y,s)=rˆ(x,y,s)−rˆ(x,y,∗)η(x,y,s)×Nj−1. We define a shape selectivity index, SSI(x,y)SSI(x,y), for that spatial location as the maximum of the shape Z   scores: SSI(x,y)=max(Zshape(x,y,s))SSI(x,y)=max(Zshape(x,y,s)). A grid BAY 73-4506 manufacturer location was considered significantly shape selective if the index exceeded the significance level of 0.05 (corrected for 72 × M multiple comparisons, where M was the number ZD1839 clinical trial of significant spatial locations; see Figure S1A). A neuron was considered significantly shape selective if it had at least one spatially significant grid location that was also significantly shape selective. A total of 13 neurons failed this significance test. These neurons had significant spatial RFs, but were not significantly shape selective (Figure 1B). An example of a nonselective neuron is shown in

Figure 2 (example neuron IV). We did not analyze these neurons any further. All subsequent analyses were performed on the remaining 80 neurons. We used the mean responses rˆ(x,y,s)

to generate first three basic response maps: (1) location-specific response maps for the composite stimuli at each location in the 5 × 5 presentation grid (Figures 2B and 3B); (2) average response map, rˆ(∗,∗,s), for the composite stimuli by averaging across spatially significant grid locations; and (3) fine-scale orientation-tuning maps using the same procedure as in (1) for the bar stimuli on the 15 × 15 grid (Figure 3C). For the population analysis, we determined several metrics from the response maps for each neuron: Average shape preference was calculated by first determining the set of composite shapes, sisi, whose firing rate in the average response map, rˆ(∗,∗,si), exceeded 90% of the maximum firing rate. The shape category, cici (0: straight, 1: low curvature, 2: medium curvature, etc.), corresponding to these shapes was weighted and averaged by their firing rates to determine the average shape preference: ∑irˆ(∗,∗,si)ci∑irˆ(∗,∗,si). Local shape preference is same as above but derived from the location-specific response maps. Local preferred shape orientation is the orientation (0°, 22.5°, 45° … 337.5°) of the local preferred shape defined above. We computed the conditional joint distribution of local shape preference and the angular deviation of preferred shape orientation, ΔθprefΔθpref (Figure 4). The computation was conditioned on the shape preference and shape orientation at the maximally responsive location for each neuron.