Fig. 2.

Reactivation following initial learning predicts subsequent encoding of related content. (Upper) Depiction of rest-phase pattern classification analysis. A pattern classifier was trained to discriminate FFA (purple) activation patterns associated with faces, objects, scrambled objects, and fixation baseline (not depicted). The trained classifier was then applied to each time point of the rest data (grayscale matrices). (Lower) Relationship between FFA reactivation and BC (Left) and AC (Right) performance, plotted as residuals after regressing each on XY performance. See also Figs. S2 and S3.