Study On Brain Function Mechanism Of Mindfulness Meditation Based On FMRI And EEG

Meditation can be defined as a spiritual training method aimed at improving one’s mental abilities,such as attention and emotional self-regulation.Many studies have shown that mindfulness interventions can help reduce a variety of psychological problems and physical disorders,including chronic pain,stress,anxiety,recurrent depression,and eating disorders.In the past few decades,mindfulness meditation has attracted more and more attention in the field of neuroscience.In recent years,neuroscience research on meditation mainly uses three biomedical engineering technologies: functional maganetic resonance imaging(fMRI),event related potentials(ERPs)and electroencephalogram(EEG).FMRI studies on mindfulness meditation have not been systematically investigated and reached consistent conclusions on the differences in neural mechanisms caused by different types of mindfulness meditation.However,the multi-center analysis of published research results based on the activation likelihood estimation(ALE)method has serious problems in the reliability of results due to the defects in the implementation of statistical methods in the analysis tools used,which need to be further summarized and verified.In the ERPs research field of meditation,due to the systematic errors of independent studies such as experimental design,measurement method and statistics,the reliability and applicability of the results of independent studies also need a higher level of multi-center analysis to obtain new and more reliable conclusions.In terms of EEG researches on meditation,most researches only focus on a single frequency band.No research has comprehensively explored all frequency bands of EEG signals.In view of the above,to explore the cognitive neuroscience mechanisms of meditation,considering the fMRI high spatial resolution and the characteristics of EEG high time resolution,we propose to perform mindfulness meditation research on functional brain regions using fMRI,time process of neural activity using ERPs,and neural oscillation using EEG.1.Multi-center analysis of fMRI studies on different types of meditations using activation likelihood estimation.This research integrates a large number of brain imaging research results and obtain stable brain activation areas through automatic statistical analysis.2.Multi-center analysis of ERPs data published in multiple studies using great grand average(GGA)method.As a supplement to the above fMRI studies,most of the activated brain areas obtained from fMRI studies are related to the retrieval of attention executive control and working memory.The proposed GGA study obtains consistent and reliable results of ERPs components related to attention.3.Scalp EEG signals classification of resting and meditative states using deep learning.This study visualizes the characteristics of all frequency bands of EEG signals related to the classification,so as to explore the differences between the meditative state and the resting state in all EEG frequency bands.ALE analysis of fMRI demonstrates that different types of meditation can lead to activation of different brain regions.Focus attention meditation activates brain regions related to attention,working memory and cognitive control,and open monitoring meditation activated brain regions related to psychological activity,spatial orientation,and divided attention.According to the statistical analysis of ERPs study with the large average method,the amplitude of P3 b components,N2,N1 and ERN in the meditators was significantly higher than that in the control group,indicating that the meditators’ attention participation increased under the condition of target stimulation.The amplitude of P3 a and P2 was significantly lower than that of the control group,indicating that the meditators ignored or paid less attention to irrelevant stimuli,which well proved that the meditators had better attention and executive control ability and could control their concentration according to their intention.MBSR data pattern classification results showed that mindfulness training indeed affected the eeg activity of the subjects according to the training duration and state,so as to achieve clear and classifiable results,and extract obvious features at each frequency band.