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Neuroplasticity within and between Functional Brain Networks in Mental Training Based on Long-Term Meditation.

Roberto Guidotti, Cosimo Del Gratta, Mauro Gianni Perrucci, Gian Luca Romani, Antonino Raffone

Brain sciences August 18, 2021 DOI: 10.3390/brainsci11081086 via PubMed

Summary

AI-generated from the abstract

Long-term meditation practice reshapes functional connectivity patterns in large-scale brain networks, and the specific patterns depend on the type of meditation used. Using fMRI and multivariate pattern analysis, researchers found that connectivity patterns in key brain networks could predict both a meditator's expertise and age. Expertise-related patterns differed between Focused Attention (FA) and Open Monitoring (OM) meditation: FA involved networks for attention, while OM involved networks for cognitive control and emotion regulation. Age-related patterns were unaffected by meditation style. The findings indicate that intensive mental training induces neuroplastic changes in brain network connectivity that are specific to the form of meditation practiced.

Study at a glance

Characteristics Observational cross-sectional study Peer reviewed
Population Long-term meditators
Topics Meditation Neuroplasticity
Keywords Mvpa Brain networks FMRI Functional connectivity Machine learning
Citations 27
Key finding fMRI connectivity patterns in multiple brain networks can differentially predict meditation expertise and age, with expertise-predictive patterns varying by meditation style (FA vs OM) while age-predictive patterns do not.

Abstract

(1) The effects of intensive mental training based on meditation on the functional and structural organization of the human brain have been addressed by several neuroscientific studies. However, how large-scale connectivity patterns are affected by long-term practice of the main forms of meditation, Focused Attention (FA) and Open Monitoring (OM), as well as by aging, has not yet been elucidated. (2) Using functional Magnetic Resonance Imaging (fMRI) and multivariate pattern analysis, we investigated the impact of meditation expertise and age on functional connectivity patterns in large-scale brain networks during different meditation styles in long-term meditators. (3) The results show that fMRI connectivity patterns in multiple key brain networks can differentially predict the meditation expertise and age of long-term meditators. Expertise-predictive patterns are differently affected by FA and OM, while age-predictive patterns are not influenced by the meditation form. The FA meditation connectivity pattern modulated by expertise included nodes and connections implicated in focusing, sustaining and monitoring attention, while OM patterns included nodes associated with cognitive control and emotion regulation. (4) The study highlights a long-term effect of meditation practice on multivariate patterns of functional brain connectivity and suggests that meditation expertise is associated with specific neuroplastic changes in connectivity patterns within and between multiple brain networks.

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