Figure 12. A simulation of correlated neural data is able to predict rat behavior with less smoothing than the unaltered population.

To evaluate the effect of different recording sessions on the performance of the classifier, we altered our dataset to mimic the correlated firing across recording sites acquired simultaneously (see Methods). The re-correlated data was able to predict rat behavior on the sequence task with less spatial smoothing than was required in the un-altered population (Gaussian filter with a half-width of 2% of the total number of sites; R²=0.67, p=0.04). The performance of the re-correlated data is not significantly different than the performance of the un-altered population (unpaired-t-test, p=0.11).