Brief mental training reorganizes large-scale brain networks

Yi Yuan Tang, Yan Tang, Rongxiang Tang, Jarrod A. Lewis-Peacock

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Emerging evidences have shown that one form of mental training—mindfulness meditation, can improve attention, emotion regulation and cognitive performance through changing brain activity and structural connectivity. However, whether and how the short-term mindfulness meditation alters large-scale brain networks are not well understood. Here, we applied a novel data-driven technique, the multivariate pattern analysis (MVPA) to resting-state fMRI (rsfMRI) data to identify changes in brain activity patterns and assess the neural mechanisms induced by a brief mindfulness training—integrative body–mind training (IBMT), which was previously reported in our series of randomized studies. Whole brain rsfMRI was performed on an undergraduate group who received 2 weeks of IBMT with 30 min per session (5 h training in total). Classifiers were trained on measures of functional connectivity in this fMRI data, and they were able to reliably differentiate (with 72% accuracy) patterns of connectivity from before vs. after the IBMT training. After training, an increase in positive functional connections (60 connections) were detected, primarily involving bilateral superior/middle occipital gyrus, bilateral frontale operculum, bilateral superior temporal gyrus, right superior temporal pole, bilateral insula, caudate and cerebellum. These results suggest that brief mental training alters the functional connectivity of large-scale brain networks at rest that may involve a portion of the neural circuitry supporting attention, cognitive and affective processing, awareness and sensory integration and reward processing.

Original languageEnglish
Article number6
JournalFrontiers in Systems Neuroscience
Volume11
DOIs
StatePublished - Feb 28 2017

Keywords

  • Functional connectivity
  • Integrative body–mind training (IBMT)
  • Large-scale brain networks
  • Multivariate pattern analysis (MVPA)
  • Resting-state fMRI

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