Hot off the press: Identifying transient networks from spontaneous MEG activity

In a study published in eLife this week, Baker et al. apply a novel methodology to identify short-lived brain states from resting state MEG recordings. These states captured similar networks to those found from fMRI studies, but were typically stable for periods of only 100-200 ms. This study provides evidence that patterns of co-activation in the resting brain are underpinned by oscillatory dynamics that fluctuate at much faster time scales than previously thought. These results suggest that the resting brain is constantly changing between different patterns of activity, which enables it to respond quickly to any given situation.