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      Meditation training modulates brain electric microstates and felt states of awareness

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          Abstract

          Meditation practice is believed to foster states of mindful awareness and mental quiescence in everyday life. If so, then the cultivation of these qualities with training ought to leave its imprint on the activity of intrinsic functional brain networks. In an intensive longitudinal study, we investigated associations between meditation practitioners' experiences of felt mindful awareness and changes in the spontaneous electrophysiological dynamics of functional brain networks. Experienced meditators were randomly assigned to complete 3 months of full‐time training in focused‐attention meditation (during an initial intervention) or to serve as waiting‐list controls and receive training second (during a later intervention). We collected broadband electroencephalogram (EEG) during rest at the beginning, middle, and end of the two training periods. Using a data‐driven approach, we segmented the EEG into a time series of transient microstate intervals based on clustering of topographic voltage patterns. Participants also provided daily reports of felt mindful awareness and mental quiescence, and reported daily on four experiential qualities of their meditation practice during training. We found that meditation training led to increases in mindful qualities of awareness, which corroborate contemplative accounts of deepening mental calm and attentional focus. We also observed reductions in the strength and duration of EEG microstates across both interventions. Importantly, changes in the dynamic sequencing of microstates were associated with daily increases in felt attentiveness and serenity during training. Our results connect shifts in subjective qualities of meditative experience with the large‐scale dynamics of whole brain functional EEG networks at rest.

          Abstract

          We identified sequences of brain electric microstates across 3 months of residential training in meditation. Training‐related changes in the dynamic sequencing of microstates were associated with daily changes in self‐reported states of mindful awareness. These results connect subjective qualities of meditative experience with the dynamics of functional brain networks at rest.

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            The human brain is intrinsically organized into dynamic, anticorrelated functional networks.

            During performance of attention-demanding cognitive tasks, certain regions of the brain routinely increase activity, whereas others routinely decrease activity. In this study, we investigate the extent to which this task-related dichotomy is represented intrinsically in the resting human brain through examination of spontaneous fluctuations in the functional MRI blood oxygen level-dependent signal. We identify two diametrically opposed, widely distributed brain networks on the basis of both spontaneous correlations within each network and anticorrelations between networks. One network consists of regions routinely exhibiting task-related activations and the other of regions routinely exhibiting task-related deactivations. This intrinsic organization, featuring the presence of anticorrelated networks in the absence of overt task performance, provides a critical context in which to understand brain function. We suggest that both task-driven neuronal responses and behavior are reflections of this dynamic, ongoing, functional organization of the brain.
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              Electrophysiological signatures of resting state networks in the human brain.

              Functional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographically organized in discrete brain networks, and by much faster (1-80 Hz) electrical oscillations. To investigate the relationship between hemodynamic and electrical oscillations, we have adopted a completely data-driven approach that combines information from simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Using independent component analysis on the fMRI data, we identified six widely distributed resting state networks. The blood oxygenation level-dependent signal fluctuations associated with each network were correlated with the EEG power variations of delta, theta, alpha, beta, and gamma rhythms. Each functional network was characterized by a specific electrophysiological signature that involved the combination of different brain rhythms. Moreover, the joint EEG/fMRI analysis afforded a finer physiological fractionation of brain networks in the resting human brain. This result supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies.
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                Author and article information

                Contributors
                apz13@miami.edu
                Journal
                Hum Brain Mapp
                Hum Brain Mapp
                10.1002/(ISSN)1097-0193
                HBM
                Human Brain Mapping
                John Wiley & Sons, Inc. (Hoboken, USA )
                1065-9471
                1097-0193
                30 March 2021
                July 2021
                : 42
                : 10 ( doiID: 10.1002/hbm.v42.10 )
                : 3228-3252
                Affiliations
                [ 1 ] Department of Psychology University of Miami Miami Florida USA
                [ 2 ] Department of Psychology University of California Davis California USA
                [ 3 ] Center for Mind and Brain University of California Davis California USA
                [ 4 ] The MIND Institute, University of California Davis California USA
                Author notes
                [*] [* ] Correspondence

                Anthony P. Zanesco, Department of Psychology, University of Miami, 5665 Ponce de Leon Blvd, Coral Gables, FL 33146.

                Email: apz13@ 123456miami.edu

                Author information
                https://orcid.org/0000-0003-3476-3375
                https://orcid.org/0000-0002-9697-7603
                https://orcid.org/0000-0002-2280-4996
                Article
                HBM25430
                10.1002/hbm.25430
                8193519
                33783922
                00d5350c-1f09-491a-9058-fd1a2e5470e4
                © 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 24 February 2021
                : 15 November 2020
                : 15 March 2021
                Page count
                Figures: 11, Tables: 5, Pages: 25, Words: 18594
                Funding
                Funded by: Fetzer Institute , open-funder-registry 10.13039/100001614;
                Award ID: #2191
                Funded by: John Templeton Foundation , open-funder-registry 10.13039/100000925;
                Award ID: #39970
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                July 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.2 mode:remove_FC converted:11.06.2021

                Neurology
                eeg,meditation,microstates,mindful awareness,resting state
                Neurology
                eeg, meditation, microstates, mindful awareness, resting state

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