This study uses a rigorous interdisciplinary approach to analyze EEG data collected during two 3-month long intensive meditation retreats in four steps. First, novel tools were developed for preprocessing the EEG data. Second, in order to identify the cortical correlates of meditation, longitudinal changes in the cortical activity were measured using spectral analysis. Three main changes were observed after retreat: (1) reduced individual alpha frequency after training, similar reduction has been consistently found in experienced meditators; (2) reduced alpha-band power in the midline frontal region, which correlated with improved vigilance performance; and (3) reduced beta-band power in the parietal-occipital regions, which correlated with daily time spent in meditation and enhanced self-reported psychological well-being. Third, a computational model was developed to provide a concrete and testable theory about the underlying mechanisms. Four experiments were run, which showed, (1) reduced intrathalamic gain after training, suggesting enhanced alertness; (2) increased corticothalamic delay, which strongly correlated with the reduction in individual alpha frequency; (3) reduction in intrathalamic gain provided increased stability to the brain; and (4) anterior-posterior division in the modeled reticular nucleus of the thalamus (TRN) layer and increased connectivity in the posterior region of TRN after training. Fourth, correlation analysis was performed to ground the changes in cortical activity and model parameters into changes in behavior and self-reported psychological functions. Through these four steps, a concrete theory of the mechanisms underlying focused-attention meditation was constructed.

Manish Saggar

University of Texas–Austin