Short-term meditation induces changes in brain resting EEG theta networks

Xue, Shao‐Wei; Tang, Yi‐Yuan; Tang, Rongxiang; Posner, Michael I.

doi:10.1016/j.bandc.2014.02.008

Cited by 72 publications

(47 citation statements)

References 35 publications

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“…This group observed that a meditation intervention increased network efficiency (which can be considered a measure of network integration) in the theta band as assessed by the harmonic mean of the shortest path length between each pair of electrodes (Xue et al, 2014). Differences between this finding and the observation of no association between meditation experience and network integration in the theta-band in the present study may be explained by the present study’s cross-sectional design, the present study’s focus on effortless awareness during meditation, and the difference in network integration measures used.…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, there is some neuroimaging evidence that meditation may be associated with increased network integration. In a recent EEG study, assessing the relationship between meditation and network integration in the theta band, it was found that a meditation intervention increased global and local network efficiency (which can be considered measures of network integration) during resting-state (Xue et al, 2014). However, in this study, synchronization likelihood was used to calculate functional connectivity, which is sensitive to volume conduction and EEG reference effects.…”

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confidence: 99%

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Meditation is associated with increased brain network integration

et al. 2017

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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.

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Section: Discussionmentioning

confidence: 99%

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Meditation is associated with increased brain network integration

et al. 2017

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“…In alignment with this interpretation, the meditators in the current sample also showed no differences in the Nogo N2 to stimulus locked activity (Bailey et al in preparation) (an ERP also generated by the ACC and thought to reflect theta modulation (Cavanagh, Zambrano-Vazquez, & Allen, 2012)). However, it should be noted that other research has shown differences between meditators and controls in the N2 and in theta activity (Aftanas & Golosheykin, 2005; Cheng, Chang, Han, & Lee, 2017; Sanger & Dorjee, 2016; Xue, Tang, Tang, & Posner, 2014). Our suggested explanation for the variation in result between studies is that meditation may increase the ability to dynamically modulate neural oscillations (with both increases and potentially decreases across multiple frequencies), when frequency modulations are beneficial to meeting task demands or goals, rather than ubiquitous increases in specific oscillation frequencies (Bailey et al in preparation).…”

Section: Discussionmentioning

confidence: 79%

Mindfulness meditators do not show differences in electrophysiological measures of error processing

Bailey

Raj

Freedman

et al. 2018

Preprint

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Mindfulness meditation may improve attention and self-regulation. One component of attention and self-regulation that may allow these improvements is performance monitoring. Neural correlates of performance monitoring can be objectively measured with electroencephalogram (EEG) via the error related negativity (ERN) and error positivity (Pe). Previous research assessing the ERN and Pe in meditators has resulted in inconsistent findings; some have reported alteration in peak amplitudes from both very brief meditation practice and long-term meditation practice, while others have failed to provide evidence for differences in the ERN or Pe. However, recently developed EEG analysis techniques allow for more rigorous analyses than have been used in past investigations. The current study measured the ERN and Pe, as well as post-error alpha suppression, during a Go/Nogo task, and emotional and colour Stroop tasks. The measures were compared between 22 experienced meditators (mean of 8 years of practice) and 20 healthy controls. The results suggested no differences in the ERN, Pe, or post-error alpha suppression (all p > 0.05), even when varying multiple analysis parameters. The study showed equivalent statistical power to previous research, and > 85% power to detect medium effect sizes present in previous research. Bayes Factor analysis indicated the null hypotheses were > 3.5 more likely than any of the alternative hypotheses for the ERN or Pe. These results suggest that meditation may not alter neural activity related to error processing, despite prior research suggesting that it does.

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“…There is considerable evidence that meditation training produces a frontal theta rhythm (Xue, Tang, Tang, & Posner, 2014). Frontal theta is also produced during tasks involving cognitive control (Jiang, Zhang & van Gaal, 2015; Wolmelsdorf, Johnson, Vinck, & Everling, 2010) and is associated with plastic changes in learning and memory.…”

Section: Brain Changesmentioning

confidence: 99%

How changes in white matter might underlie improved reaction time due to practice

Voelker

Piscopo

Weible

et al. 2016

Cognitive Neuroscience

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Why does training on a task reduce the reaction time for performing it? New research points to changes in white matter pathways as one likely mechanism. These pathways connect remote brain areas involved in performing the task. Genetic variations may be involved in individual differences in the extent of this improvement. If white matter change is involved in improved reaction time with training, it may point the way toward understanding where and how generalization occurs. We examine the hypothesis that brain pathways shared by different tasks may result in improved performance of cognitive tasks remote from the training.

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Short-term meditation induces changes in brain resting EEG theta networks

Cited by 72 publications

References 35 publications

Meditation is associated with increased brain network integration

Meditation is associated with increased brain network integration

Mindfulness meditators do not show differences in electrophysiological measures of error processing

How changes in white matter might underlie improved reaction time due to practice

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