We computed figure-ground

measure for population response (FG-m, Equation 1; see Figure 3Ai). FG-m was defined by subtracting the population response (average over pixels) in the background from the circle for the contour and noncontour conditions and then taking the difference between the two conditions. This index indicated how well the “figure” (circle area) is differentiated from the “ground” (background area). FG-m was calculated for each recording session separately. equation(Equation 1) FG-m=(Pc−Pb)cont−(Pc−Pb)non−cont,FG-m=(Pc−Pb)cont−(Pc−Pb)non−cont,where Pc and Pb are the population responses in the circle and background areas, respectively, cont and non-cont are the contour and noncontour conditions, respectively. The subtraction of the noncontour from the contour condition also enabled us to eliminate any response differences PD0325901 price in space due to uneven staining. We also computed the differential selleck compound (contour minus noncontour) circle or background response ( Equations 2 and 3). Figure 3Bi depicts the circle differential response (Pcdiff) and background differential response (Pbdiff) as function of time. equation(Equation 2) Pcdiff=Pccont−Pcnon−contPcdiff=Pccont−Pcnon−cont equation(Equation 3) Pbdiff=Pbcont−Pbnon−contPbdiff=Pbcont−Pbnon−cont To study

the behavioral performance in the contour saliency experiments, we computed the probability of contour detection. This was normalized to the contour and noncontour conditions by setting the probability of contour detection to 1 in the contour condition, 0 in the noncontour condition and varying accordingly the probability for the jittering orientation conditions (Figure 5B). The purpose of this

normalization was to overcome the slight variation in behavioral performance due to the animal’s motivation. We verified that the nonnormalized and normalized psychometric curves showed similar results (Figure S4A). To study the effects of contour saliency on the population response, the neurometric curve was computed by calculating the FG-m as a function of orientation jitter (FG-mjitt; Equation 4). equation(Equation 4) FG−mjitt=(Pc−Pb)jitt−(Pc−Pb)non−cont,FG−mjitt=(Pc−Pb)jitt−(Pc−Pb)non−cont,where Pc and Pb are the population responses in the circle and background Terminal deoxynucleotidyl transferase areas, respectively, and jitt and non-cont are the different jitter conditions and noncontour condition, respectively (the contour condition is defined by jitter = 0). The neurometric curve values were normalized to maximal and minimal values in each recording session (to overcome the variable staining quality across recording sessions; Figure 5C). We verified that the nonnormalized and normalized curves showed similar results (Figure S4B). The population response for each pixel (VSDI amplitude, normalized as in the previous section) was computed as function of the orientation jitter condition. This yielded the neurometric curve for each pixel, which was then computed for each time frame.