Figure 4. Compressed modular sequence reactivation. See also Fig. S7 and Table S3-4.

A. Mean (±SEM) match percentage [(n matches/n time bins)*100] across the compression factors for multi-unit activity (MUA) templates during slow-wave sleep. Template matching increases between pre- (blue) and post-task-sleep (red) for compressed data, but not for ‘no-compression’ (nc). Match percentage varied significantly across compression factors (F_(4,44)=11.18, p<0.0001) and reactivation peaked at 4x compression. B. Example of MUA showing the match percentage (2min bins) for ‘no-compression’ (left) and 4x compression (right), over the pre-task-sleep, task and post-task-sleep. For ‘no-compression’, there is a high match percentage during the task, but not post-task-sleep. For the 4x compression (right), match percentage is higher in post-task-sleep, relative to both pre-task-sleep and task. C. Mean of the pre-task-sleep, task and post-task-sleep as was calculated for each session and averaged across time bins that are shown in B. Then a mean for all sessions was calculated for each rat. Finally, the mean (±SEM) of the rat mean data shows that across rats reactivation is stronger in post-task rest when a 4x compression factor is applied, but not for nc. To avoid the possible contribution of awake reactivation to template matching during task, only the contiguous movement periods (>5cm/s) longer than 2s were used for template matching. D. Normalized match percentage (match percentage/peak match percentage for that session) across ‘no-compression’ (left) and 4x (right) compression factors for MUA templates for each session for each of 3 rats. Reactivation consistently increases between pre- and post-task-sleep for compressed data, but not for ‘no compression’. Datapoints are normalized to pre-task-sleep values. A-D. Only the slow-wave sleep (SWS) periods are used from sleep and n is the number of data sets (n=12). * p<0.05.