Topic: magnetoencephalography (MEG)

Normal brain function results from directed causal interactions between brain regions. However, the large-scale spatial and temporal structure of these interactions remains unclear. Lagged correlations between the activity of different brain regions may reflect their directed causal interactions. Thus, we combined magnetoencephalography (MEG) and machine learning approaches to characterize and disentangle the structure of lagged correlations in the human brain. We computed lagged correlations between all pairs of cortical regions and frequencies of neural activity. We employed curvature-regul