Does meditation lead to a stable mind? Synchronous stability and time-varying graphs in meditators

Abstract

Abstract The dynamical approach represents a new branch in the understanding of functional brain networks. Using simple indices to represent time connectivity and topological stability, we evaluated the hypothesis of increased brain stability during the meditative state in comparison to the relaxation state. We used a new way to consider the time evolution of synchronization patterns in electroencephalography (EEG) data. The time-varying graph approach and the motif synchronization method were combined to build a set of graphs representing time evolution for the synchronization of 29 EEG electrodes. We analysed these graphs during meditation and relaxation states in 17 experienced meditators. As result, we found significant increasing of time connectivity (t(15) $= -2.50$, p $= 0.023$) and topological stability (t(15) $= 1.23$, p $= 0.020$) in the meditation state when compared to the relaxation state. These findings suggest that dynamical properties of the synchronization network may revel aspects of brain activity in altered states of consciousness not possible to measure using a static approach. We concluded that the topological patterns evolution in the functional networks of experienced meditators are more stable in the meditative state than in the relaxation state.