Long-term meditators in an open monitoring (OM) state show reduced automatic mental processing of objects that imply actions, compared to their baseline state. Novice meditators did not show this reduction. The study used EEG to measure µ-rhythm desynchronization, which correlated with how long objects were perceived. The findings suggest OM meditation can help decouple automatic cognitive processing of action-related mental content.
A Random Forest classifier trained on two-second samples of EEG data can discriminate between Focused Attention Meditation (FAM) and a problem-solving task with high accuracy when personalized to each individual. Individual classifiers achieved an average accuracy of 93% across 14 subjects, whereas general classifiers trained on inter-individual data performed worse (74% and 54% depending on whether the tested subject's data was included in training). The most discriminating EEG features were Beta mean band amplitude and Theta-Gamma phase-amplitude coupling, especially in occipital and left centro-temporal brain regions. The findings favor personalized classifiers for real-time detection of meditative states.