Figure 5.

Cumulative Kullback–Leibler divergence (D_cKL⁽ⁿ⁾) between neural responses, as defined in Equation 2, as a function of the log ratio of two stimulus SDs, σ_B and σ_A. This divergence is related to the probability of misclassification in which a distance of one bit corresponds to a twofold reduction in error and is a measure of the capacity to discriminate between two ISI distributions resulting from two stimulus variances, as in Figure 4, a and b. D_cKL⁽ⁿ⁾ is for n = 1, 3, or 5 ISIs from fly data for a given SD ratio (a) and from the HH model neuron (b). For example, the circle represents the average discrimination for all 10-fold ratios of stimulus SD decrease, e.g., 10 to 1, 30 to 3, and 60 to 6. Error bars represent the SD.