To account for CAF-induced changes in Ibrutinib chemical structure temporal song structure,

the post-CAF spectrogram was warped to the baseline spectrogram, using the same DTW warping routine as described above. Warping estimates for each interval were calculated as the ratio of post-CAF to pre-CAF interval duration. The warping paths thus derived were applied to the average post-CAF neural trace, yielding the green traces in Figure 7A. The same DTW routine was also applied to the neural traces to compare the warping in the underlying neural signal to warping in the song (Figure 7C). To make the warping estimates for the neural data more reliable, we flagged salient points in the neural trace (i.e., well-defined peaks and troughs) and calculated the time shifts in these points over the course of the CAF drive. Since

these points did not always line up with the interval boundaries in the song, we took the weighted average of the time shifts in the points within 10 ms of the interval boundary, this website each point being weighted inversely to its distance from the boundary. The estimate for the neural warping in a given interval was then derived from the difference in the estimated time shifts corresponding to the start and end points of the interval. To quantify the degree and temporal specificity of the changes in neural power induced by CAF, we calculated running Pearson’s correlations (50 ms boxcar window, 1 ms advance) between no the neural power in baseline and post-CAF conditions. For each analyzed CAF drive, we compared the mean correlation of nontargeted song intervals (motif onset to 50–100 ms prior to CAF target) with those in the targeted interval (pCAF) or targeted interval plus 100 ms (tCAF). All statistics presented in the main text refer to mean ± SD, while error bars in the figures all represent SEM. All statistical tests assessing significance across manipulations in the same birds were done using paired-samples t tests or one-sample t tests against mean zero unless otherwise noted.

We thank Ed Soucy for assistance with the CAF software and Stephen Turney and the Harvard University Neurobiology Department and the Neurobiology Imaging Facility for imaging consultation and equipment use. We acknowledge Jesse Goldberg, Aaron Andalman, Rajesh Poddar, Naoshige Uchida, Markus Meister, Evan Feinberg, Maurice Smith, and Kenneth Blum for helpful discussions and feedback on the manuscript. This work was supported by a grant from NINDS (R01 NS066408), a McKnight Scholar Award and Klingenstein Fellowship to B.P.Ö., and a Swartz Foundation postdoctoral fellowship to C.P. “
“Imagination, defined as the ability to interpret reality in ways that diverge from past experience, is fundamental to normal, adaptive behavior. This can be seen at a very simple level in our capacity to predict novel outcomes in new situations, unbound from our past experience with any particular static element or feature.