Trait and state mindfulness modulate EEG microstates

Abstract

Here, we aimed to characterized microstate dynamics induced by open-monitoring meditation (OM), which emphasizes a non-reactive stance toward lived experience, while participants were passively exposed to auditory stimuli. We recorded EEG signals from eighteen trained meditators before, during, and after an OM, that we compared to a matched control group at rest. To characterize brain state, we used a multidimensional-based analysis including source localization EEG microstates, phenomenological reports and personality trait questionnaires. We showed that microstate A was negatively correlated with mindfulness trait and decreased in frequency after OM compared to before in meditators. Microstate B was longer and was positively correlated to non-reactivity trait after OM in the meditator group. Microstate C was less frequent and shorter at rest before OM in meditators compared to non-meditators, and decreased in frequency after OM in meditators. Further, the occurrence of microstate C was negatively correlated to non-reactivity trait of meditators. Source localization analysis revealed that the mindfulness trait effect on microstate C at rest was explained by lower activity of the salience network (identified in the anterior cingulate cortex, thalamus and insula), while the mindfulness state effect relied on a strong contribution of (anterior and posterior) cerebellum during OM. While the decreased microstate A occurrence would be related to the mitigation of phonological aspect of thinking processes, the decrease of microstate C occurrence would represent an index of the cognitive defusion enabled by non-reactive monitoring underlying mindfulness meditation, for which the cerebellum appears to play a crucial role.SIGNIFICANCE STATEMENTWhile benefit of mindfulness meditations are extensively documented in wide range of scientific field, their neural mechanisms remain difficult to catch. Here, we characterize EEG microstate dynamics induced by open-monitoring meditation (OM) triangulated by multimodal approach including source localization, phenomenological reports and personality trait questionnaires. We found that temporal parameters of microstates related to phonological processes and mind wandering are negatively correlated to mindfulness trait and are modulated by OM. Source localization analysis revealed that the trait effect at rest was explained by lower activity of the salience network, while the state effect relied on a strong contribution of the cerebellum during OM. These findings suggested that EEG microstates could represent biomarkers of the cognitive effects of mindfulness.

EEG-based investigation of effects of mindfulness meditation training on state and trait by deep learning and traditional machine learning

“…Meditation expertise increases through training and practice, and there will be both state and trait effects which can be characterized in either behavioral data or brain activities such as resting EEG for trait effect and meditating EEG for state effect ( Cahn and Polich, 2006 ; Zarka et al, 2022 ). There is lack of studies on classification of brain states for different training and practicing stages longitudinally for individual meditation practitioners, but some efforts have been spent on classifying subjects with different levels of meditation expertise using EEG in either the meditating states ( Shaw and Routray, 2016 ; Lee et al, 2017 ; Pandey and Miyapuram, 2021 ) or the resting states ( Sharma et al, 2019 ), as detailed in Table 6 , where the results of our study in this paper on meditation stage classification using meditation EEG (MBSR1/MBSR2) and resting state EEG (REST1/REST2), are also presented for ease of comparison.…”