03, p = 0.6 for velocity and r2 = 0.02, p > 0.72 for acceleration). Correlations of firing rates between different arms indicate that the population of mPFC single units is capable of representing anxiety-related
task components. However, such correlations do not quantify the extent to which the firing pattern of any given single unit is paradigm-related. To address this issue, we first binned each spike train into three-second segments, and calculated the influence Cobimetinib of arm type (open versus closed) on firing rate by ANOVA. 29/69 (42%) of the recorded neurons fired significantly differently (p < 0.05) to the closed and open arms by ANOVA . Next, to confirm that the observed frequency of task-related firing patterns in the population of single units was not due to chance, an EPM score was calculated for each unit. The EPM score is a normalized ratio of GSI-IX cell line the average difference in firing rates across arms of the same type, compared to the average differences in firing rates across arms of different types (see Experimental Procedures). The resultant measure, which varies from −0.33 to 1, indicates the degree to which that unit’s firing pattern represents the “open vs. closed” structure of the EPM. Units with positive EPM scores closer to 1 represent
this structure well; units with EPM scores near or below zero do not. Accordingly, the correlation of firing rates across arms of the same type was higher in units with positive EPM scores than in units with negative EPM scores (Figures 4A and 4B). Furthermore, single units with a significant effect of arm type on firing in the ANOVA had higher
EPM scores than other units (mean score = 0.3 ± 0.06 and 0.064 ± 0.04 for units with and without significant main effects of arm type), demonstrating the old utility of the EPM score as a quantification of the strength of paradigm-related activity. We next examined whether the distribution of EPM scores obtained in our sample (Figure 4C) could have been obtained by chance, using a bootstrap method. Briefly, 500 simulated spike trains were generated for each unit. The location of each spike was assigned randomly from the actual path of the animal in the maze when that spike was recorded, and EPM scores were computed from these simulated spike trains. The distribution of simulated EPM scores (Figure 4C, red line) was significantly different from the experimental distribution (p < 0.0001, Wilcoxon’s rank-sum test), due to the presence of a greater fraction of units with positive (i.e., paradigm-related) EPM scores in the experimental distribution. These results confirm that the paradigm-related firing patterns seen in our sample in the standard EPM were unlikely to have arisen by chance. In cognitive tasks, mPFC unit activity predicts future choice behavior (Fujisawa et al., 2008, Peters et al., 2005 and Rich and Shapiro, 2009).