Description: MEG beamforming source reconstruction of the onset of sequenceness events during episodic memory retrieval. Linearly constrained minimum variance beamforming was used to reconstruct the epoched MEG data to a grid in MNI space, sampled with a grid step of 5 mm. The sensor covariance matrix for beamforming was estimated using data in broadband power across all frequencies. The baseline activity was the mean power activity averaged over -100 ms to -50 ms relative to replay onset. All non-artifactual trials were baseline corrected at source level. We looked at the main effect of the initialization of replay. This analysis was conducted separately to investigate backward replay events in the after condition and forward replay events in the before condition. The statistical significance of clusters identified in the beamforming analysis was calculated using SPM12. An initial cluster-forming threshold of p < 0.001 was applied and regions exceeding p < 0.05 whole-brain family-wise-error corrected (FWE) at the cluster level are reported. Replay onsets were defined as moments when a strong reactivation of a stimulus was followed by a strong reactivation of the next (or preceding) stimulus in the sequence from an episode (Liu et al. 2019). We thresholded putative events at the 95th percentile to only include high-magnitude putative replay onset events. We also imposed a constraint that a replay onset event had 100 ms of preceding replay-free time.
If you use the data from this collection please include the following persistent identifier in the text of your manuscript:
This will help to track the use of this data in the literature.