Author: van Lutterveld R1, van Dellen E2, Pal P3, Yang H3, Stam CJ4, Brewer J3
Affiliation: <sup>1</sup>Center for Mindfulness, University of Massachusetts Medical School, Worcester, MA, USA. Electronic address: Remko.vanLutterveld@umassmed.edu.
<sup>2</sup>Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands.
<sup>3</sup>Center for Mindfulness, University of Massachusetts Medical School, Worcester, MA, USA.
<sup>4</sup>Department of Clinical Neurophysiology and MEG Centre, VU University Medical Center, Amsterdam, The Netherlands.
Conference/Journal: Neuroimage.
Date published: 2017 Jun 26
Other:
Pages: S1053-8119(17)30542-6 , Special Notes: doi: 10.1016/j.neuroimage.2017.06.071. [Epub ahead of print] , Word Count: 283
INTRODUCTION: This study aims to identify novel quantitative EEG measures associated with mindfulness meditation. As there is some evidence that meditation is associated with higher integration of brain networks, we focused on EEG measures of network integration.
METHODS: Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators performed a basic meditation practice that supported effortless awareness, which is an important quality of experience related to mindfulness practices, while their EEG was recorded. Experienced meditators performed a self-selected meditation practice that supported effortless awareness. Network integration was analyzed with maximum betweenness centrality and leaf fraction (which both correlate positively with network integration) as well as with diameter and average eccentricity (which both correlate negatively with network integration), based on a phase-lag index (PLI) and minimum spanning tree (MST) approach. Differences between groups were assessed using repeated-measures ANOVA for the theta (4-8 Hz), alpha (8-13 Hz) and lower beta (13-20 Hz) frequency bands.
RESULTS: Maximum betweenness centrality was significantly higher in experienced meditators than in novices (P = 0.012) in the alpha band. In the same frequency band, leaf fraction showed a trend toward being significantly higher in experienced meditators than in novices (P = 0.056), while diameter and average eccentricity were significantly lower in experienced meditators than in novices (P = 0.016 and P = 0.028 respectively). No significant differences between groups were observed for the theta and beta frequency bands.
CONCLUSION: These results show that alpha band functional network topology is better integrated in experienced meditators than in novice meditators during meditation. This novel finding provides the rationale to investigate the temporal relation between measures of functional connectivity network integration and meditation quality, for example using neurophenomenology experiments.
Copyright © 2017. Published by Elsevier Inc.
PMID: 28663069 DOI: 10.1016/j.neuroimage.2017.06.071