Dataset Information

Revealing Changes in Brain Functional Networks Caused by Focused-Attention Meditation Using Tucker3 Clustering.

ABSTRACT: This study examines the effects of focused-attention meditation on functional brain states in novice meditators. There are a number of feature metrics for functional brain states, such as functional connectivity, graph theoretical metrics, and amplitude of low frequency fluctuation (ALFF). It is necessary to choose appropriate metrics and also to specify the region of interests (ROIs) from a number of brain regions. Here, we use a Tucker3 clustering method, which simultaneously selects the feature vectors (graph theoretical metrics and fractional ALFF) and the ROIs that can discriminate between resting and meditative states based on the characteristics of the given data. In this study, breath-counting meditation, one of the most popular forms of focused-attention meditation, was used and brain activities during resting and meditation states were measured by functional magnetic resonance imaging. The results indicated that the clustering coefficients of the eight brain regions, Frontal Inf Oper L, Occipital Inf R, ParaHippocampal R, Cerebellum 10 R, Cingulum Mid R, Cerebellum Crus1 L, Occipital Inf L, and Paracentral Lobule R increased through the meditation. Our study also provided the framework of data-driven brain functional analysis and confirmed its effectiveness on analyzing neural basis of focused-attention meditation.

SUBMITTER: Miyoshi T

PROVIDER: S-EPMC6990115 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Revealing Changes in Brain Functional Networks Caused by Focused-Attention Meditation Using Tucker3 Clustering.

Miyoshi Takuma T Tanioka Kensuke K Yamamoto Shoko S Yadohisa Hiroshi H Hiroyasu Tomoyuki T Hiwa Satoru S

Frontiers in human neuroscience 20200122

This study examines the effects of focused-attention meditation on functional brain states in novice meditators. There are a number of feature metrics for functional brain states, such as functional connectivity, graph theoretical metrics, and amplitude of low frequency fluctuation (ALFF). It is necessary to choose appropriate metrics and also to specify the region of interests (ROIs) from a number of brain regions. Here, we use a Tucker3 clustering method, which simultaneously selects the featu ...[more]

PMID: 32038204

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Project description:Cortical oscillations serve as an index of both sensory and cognitive processes and represent one of the most promising candidates for training and targeting the top-down mechanisms underlying executive functions. Research findings suggest that theta (?) oscillations (3-7 Hz) recorded over frontal-midline electrodes are broadly associated with a number of higher-order cognitive processes and may serve as the mechanistic backbone for cognitive control. Frontal-midline theta (FM?) oscillations have also been shown to inversely correlate with activity in the default mode network (DMN), a network in the brain linked to spontaneous thought processes such as mind-wandering and rumination. In line with these findings, we previously observed increased FM? oscillations in expert meditation practitioners during reported periods of focused-attention meditation practice when compared to periods of mind-wandering. In an effort to narrow the explanatory gap by directly connecting observed neurophysiological activity in the brain to the phenomenological nature of reported experience, we designed a methodologically novel and adaptive neurofeedback protocol with the aim of modulating FM? while having meditation novice participants implement breath-focus strategies derived from focused-attention mediation practices. Participants who received eight sessions of the adaptive FM?-meditation neurofeedback protocol were able to significantly modulate FM? over frontal electrodes using focused-attention meditation strategies relative to their baseline by the end of the training and demonstrated significantly faster reaction times on correct trials during the n-back working memory task assessed before and after the FM?-meditation neurofeedback protocol. No significant differences in frontal theta activity or behavior were observed in the active control participants who received age and gender matched sham neurofeedback. These findings help lay the groundwork for the development of brain training protocols and neurofeedback applications that aim to train features of the mental states and traits associated with focused-attention meditation.

Dataset Information

Revealing Changes in Brain Functional Networks Caused by Focused-Attention Meditation Using Tucker3 Clustering.

Publications

Revealing Changes in Brain Functional Networks Caused by Focused-Attention Meditation Using Tucker3 Clustering.

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