Figure 9. Results of estimating 2D stimulus disparity from the 1D disparity encoding population.

Each panel shows the distribution of the estimated disparity component (left column, red: horizontal disparity; right column, blue: vertical disparity). The rows show three different test disparities (Δx_test,Δy_test), as indicated by the black vertical lines in each column. In each case, 1000 images with the specified test disparity were generated, and their 2D disparity was estimated as being the value of (Δx_dec,Δy_dec) which gave the best match between the population activity R_test(θ,f,Δφ, Δx_enc) evoked by the test image, and the stored W(θ,f,Δφ,Δx_enc;Δx_dec,Δy_dec), as in Figure 8. The root-mean-squared error between the estimated disparity and the correct value is indicated at the top of each panel. Matlab code: The disparity estimates were obtained with Protocol S7, and the figure was generated with Protocol S8.