Fig. 3.

Four neurometrics were used to measure neural discriminability. A: within each metric, each dot represents the discriminability of a single neuron. Neurons were ordered independently for each neurometric, from lowest to highest performance. Error bars show the SD across 100 repetitions of each neurometric. The right panel shows the mean discrimination performance using each neurometric. Error bars are ±1SD. B: discriminability measured with the K-means and van Rossum metrics showed a strong correspondence (r = 0.95). C: discrimination using the K-means and Victor–Purpura metrics were also highly correlated at the single neuron level (r = 0.96). In B and C, solid lines are unity. D: discriminability measured with the K-means metric was correlated with response strengths (driven firing rate minus baseline firing rate) between 0 and 13 spikes/s (r = 0.69, P < 0.0001). E: K-means discriminability increased with spike train duration. Each gray line shows the discriminability of a single neuron; the black line shows the average for the population. F: discriminability decreased as the number of songs to discriminate increased. The solid black line shows the average discriminability for the population and the dashed line shows chance performance at each set size. G: as the number of songs to discriminate increased, the spike train duration necessary to maintain discriminability increased sublinearly. Performance is represented as color, ranging from 0 to 100% correct. The abscissa shows the number of songs to discriminate and the ordinate shows the spike train duration used in the K-means neurometric. The solid line represents the isodiscriminabiltiy contour of 56% correct, which was the average discriminability. The dashed line shows the linear prediction of spike train duration necessary to maintain this level of discriminabitliy, based on set sizes of 2–4 songs. The dotted-dashed line shows the linear prediction based on set sizes of 5–7 songs.