The number of neurons that produced significantly different tastant responses in the two conditions was assessed by using a two-way ANOVA ([expected/unexpected trials] × tastants) on either single bins or on responses averaged across 2.5 s. Correlation between ΔPSTHs before and after gustatory stimulation was established performing a linear regression analysis. ΔPSTHs for the last 125 ms before stimulus

and for the first 125 after stimulus were used. This analysis was performed on all the neurons in which UT and ExpT were compared. Correlation was established via linear regression analysis of single-cell firing rates evoked by either UT or tones over a period of 125 ms from the stimulus. In few sessions (i.e., when pressing occurred before 125 ms), cue responses could be measured only over an interval shorter than 125 ms. In this case, responses UMI-77 cost to cues were measured from the onset of the tone to the time of the earliest lever press. Responses to UT were computed over a same-length interval. Firing rates were normalized to background firing. All the

cue-responsive neurons with no somatosensory rhythmicity were used for the correlation analysis. K-means clustering of cue and UT responses in this population suggested the presence of two subgroups with different firing rates. To examine how a single bin of population activity (i.e., the first 125 ms after either the cue or self-administrations) correlated with the check details whole time course of responses in another condition, a running correlation was used. Activity at each time point was described by a population vector of firing rates for all the cells that were cue responsive and that fired to tastants with less than 30 Hz above background. Population activity in the reference bin was correlated with that in each bin composing the time course of the target response from 1 s before to 2.5 s after

presentation of UT. The correlation was performed across single trials and averaged. The significance of peaks and differences was established with a one-way ANOVA and a Tukey-Kramer post hoc test. To visualize the time course of population activity as a trajectory in space, a PCA was used. PCA was performed for responses to cues, UT, and ExpT. PCA was applied on 2D matrices all composed by the trial-averaged activity for the population of neurons versus each 125 ms time bin ([neurons × time]). Tastant responses went from −2 to 2.5 s after stimulus presentation, whereas cue responses were limited to an interval going from −2 s to 125 ms after the tone. The difference between the Euclidean distance for homologous bins in different conditions (i.e., bin1 ExpT and bin1 UT; bin2 ExpT and bin2 UT, etc.) and that for successive bins in different conditions (i.e., bin1 ExpT and bin2 UT; bin2 ExpT and bin3 UT, etc.) was used to verify time course of the similarity between bins. Negative values indicated that the distance for successive bins was shorter than that for homologs bins, i.e.