Fix, S. (2017). Examining how regular meditation practice influences the neural oscillatory activity associated with refocusing attention after a mind wandering episode. Unc Charlotte Electronic Theses And Dissertations.
Introduction. Mind wandering (MW) has become a topic of interest in neuroscience research, particularly because of its tendency to interrupt goal directed behavior and negatively impact mental and physical health. Several brain networks have been implicated in the generation and suppression of MW, including the default mode network (DMN), fronto-parietal control network (FPCN), and dorsal attention network (DAN). Furthermore, meditation practices have been found to be associated with an increased ability to suppress MW and maintain focused attention. To examine the effects of meditation on the interactions between these three networks, comparisons were made in electroencephalographic (EEG) activity and self-report incidences of mind wandering. Methods. A between-groups design was used to investigate differences in event-related spectral perturbations (ERSP), an EEG measure of neural activity and inhibition, between a novice meditator and regular meditator group. Additionally, an independent component analysis was conducted to identify nodes of the DMN, FPCN, and DAN so that the ERSP changes associated with each network can be detected. Lastly, a functional connectivity analysis was conducted to examine the correlation in activity between networks. Results. Both groups displayed significant increases in alpha, beta, and gamma band activity and decreases in delta and theta activity following awareness of MW. Connectivity results suggest activation changes represented the FPCN and DMN coordinating to suppress MW and refocus attention. Though few activation differences were observed between groups, meditators produced lower connectivity between several pairs of network nodes than did novice meditator participants, suggestive of enhance neural efficiency. Conclusion. The present study provides preliminary support for the use of independent component analysis in separating the activity of disparate neural network nodes. Finally, a robust activation pattern was replicated from a previous study which, when combined with the current connectivity results, represents reliable changes in network activity associated with MW suppression and attention refocusing.