Meditation produces distinct whole-brain dynamics compared to rest. Using fMRI data from expert meditators and controls, the authors defined probabilistic metastable substates (PMS) for each condition, capturing different probabilities of dynamic brain patterns. They then fit a whole-brain model to these substates and performed in silico perturbations to simulate transitions between resting-state and meditation. The results show that localized artificial perturbations can induce such transitions, and the sensitivity of different brain areas to perturbation varies. This mechanistic framework clarifies how meditation alters brain dynamics and suggests potential applications for health and therapy.
Meditation produces distinct whole-brain dynamics compared to rest, particularly in the triple-network model (executive control, salience, and default-mode networks). Using a causal mechanistic framework, researchers defined probabilistic metastable substates from dynamic brain patterns and adjusted a whole-brain model of the resting state to simulate transitions to meditation. They successfully induced the meditative state through localized artificial perturbations, primarily shifting areas in the somatomotor and dorsal attention networks. The work suggests meditation can be studied as a practice for health and as a potential therapy for brain disorders.