Characterizing the Dynamical Complexity underlying Meditation

Abstract

Over the past 2,500 years, contemplative traditions have explored the nature of the mind using meditation. More recently, neuroimaging research on meditation has revealed differences in brain function and structure in meditators. Nevertheless, the underlying neural mechanisms are still unclear. In order to understand how meditation shapes global activity through the brain, we investigated the spatiotemporal dynamics across the whole-brain functional network using the Intrinsic Ignition Framework. Recent neuroimaging studies have demonstrated that different states of consciousness differ in their underlying dynamical complexity, i.e., how the broadness of communication is elicited and distributed through the brain over time and space.In this work, controls and experienced meditators were scanned using functional magnetic resonance imaging (fMRI) during resting-state and meditation (focused attention on breathing). Our results evidenced that the dynamical complexity underlying meditation shows less complexity than during resting-state in the meditator group but not in the control group.Furthermore, we report that during resting-state, the brain activity of experienced meditators showed higher metastability (i.e., a wider dynamical regime over time) than the one observed in the control group. Overall, these results indicate that the meditation state operates in a different dynamical regime than the resting-state.

Uncovering a stability signature of brain dynamics associated with meditation experience using massive time-series feature extraction

“…Given the novelty of our results with regards to the univariate stationarity and distributional properties of the data, there are no directly comparable studies within the meditation literature to help guide our interpretation. However, previous research has reported that experienced meditators in the meditation state show increased stability in the topographical pattern of EEG activity and in the temporal patterns of both EEG and fMRI based connectivity (Escrichs et al, 2019;Toutain et al, 2020;Vivot et al, 2020). The increased fMRI connectivity stability finding has also been reported in novice meditators, and for comparisons between meditator and non-meditator resting-state connectivity (Escrichs et al, 2019).…”

“…However, previous research has reported that experienced meditators in the meditation state show increased stability in the topographical pattern of EEG activity and in the temporal patterns of both EEG and fMRI based connectivity (Escrichs et al, 2019;Toutain et al, 2020;Vivot et al, 2020). The increased fMRI connectivity stability finding has also been reported in novice meditators, and for comparisons between meditator and non-meditator resting-state connectivity (Escrichs et al, 2019). Previous research has also shown that meditators generate more consistent brain activity in response to stimuli while performing a cognitive task, enabling their brain activity to time-lock more effectively to the stimuli presented in the task (Bailey et al, 2023b;Lutz et al, 2009).…”

“…However, previous research has reported that experienced meditators in the meditation state show increased stability in the topographical pattern of EEG activity and in the temporal patterns of both EEG and fMRI based connectivity (Escrichs et al, 2019;Toutain et al, 2020;Vivot et al, 2020). The increased fMRI connectivity stability finding has also been reported in novice meditators, and for comparisons between meditator and non-meditator resting-state connectivity (Escrichs et al, 2019). Previous research has also…”