Figure 7. PV decoding becomes more efficient with experience.
(A) Top, sample performance of the PV decoder on training day 1 when trained with 40 (magenta, left) and 160 (green, right) neurons. Identification score (I) and decoding error (E) are indicated above the plots. As expected, the decoder performs better when more neurons are included. Bottom, same as above but on day 7 of training, demonstrating marked improvement over day 1. Note that the 40 neuron decoder on day 7 equals or exceeds the performance of the 160-neuron decoder on day 1.
(B) The Identification Score of the decoder increased as a function of experience. This was true for decoders trained on a small (left, 40) or large (middle, 160) number of neurons. (Right) Decoders trained on later sessions with few neurons could achieve similar accuracy as decoders trained on early sessions with many neurons, indicating an increased efficiency of encoding the space (two-way ANOVA, effect of number of neurons, p = 1.7 × 10−4; effect of day, p = 1.3 × 10−14; interaction, p = 0.98).
(C) As in B but for decoding error. Decoding Error only slightly improved with experience; the number of neurons was a stronger influence on Decoding Error (Two-way ANOVA, effect of number of neurons, p = 2.9 × 10−31; effect of Day, p = 1.7 × 10−9; interaction, p = 0.36, see STAR Methods).
Data presented as mean ± standard error of the mean (gray lines), n = 6 mice.