Does meditation lead to a stable mind? Synchronous stability and time-varying graphs in meditators

The dynamical approach represents a new branch in the understanding of functional brain networks. Using simple indices to represent time connectivity and topological stability, we evaluated the hypothesis of increased brain stability during the meditative state in comparison to the relaxation state. We used a new way to consider the time evolution of synchronization patterns in electroencephalography (EEG) data. The time-varying graph approach and the motif synchronization method were combined to build a set of graphs representing time evolution for the synchronization of 29 EEG electrodes. We analysed these graphs during meditation and relaxation states in 17 experienced meditators. As result, we found significant increasing of time connectivity (t(15) $= -2.50$, p $= 0.023$) and topological stability (t(15) $= 1.23$, p $= 0.020$) in the meditation state when compared to the relaxation state. These findings suggest that dynamical properties of the synchronization network may revel aspects of brain activity in altered states of consciousness not possible to measure using a static approach. We concluded that the topological patterns evolution in the functional networks of experienced meditators are more stable in the meditative state than in the relaxation state.

[1]  Ricardo Sevilla-Escoboza,et al.  Ordinal synchronization: Using ordinal patterns to capture interdependencies between time series , 2018, Chaos, Solitons & Fractals.

[2]  J. Wu,et al.  The effects of music on brain functional networks: A network analysis , 2013, Neuroscience.

[3]  V. Latora,et al.  Complex networks: Structure and dynamics , 2006 .

[4]  W. M. van der Flier,et al.  Functional neural network analysis in frontotemporal dementia and Alzheimer's disease using EEG and graph theory , 2009, BMC Neuroscience.

[5]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[6]  J. Gray,et al.  Meditation experience is associated with differences in default mode network activity and connectivity , 2011, Proceedings of the National Academy of Sciences.

[7]  G. Deco,et al.  Characterizing the Dynamical Complexity Underlying Meditation , 2019, bioRxiv.

[8]  Hua Yang,et al.  Meditation is associated with increased brain network integration , 2017, NeuroImage.

[9]  João Ricardo Sato,et al.  Meditation training increases brain efficiency in an attention task , 2012, NeuroImage.

[10]  R. M G,et al.  Efficacy of rajayoga meditation on positive thinking: an index for self-satisfaction and happiness in life. , 2013, Journal of clinical and diagnostic research : JCDR.

[11]  V Latora,et al.  Small-world behavior in time-varying graphs. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  Britta K. Hölzel,et al.  Mindfulness practice leads to increases in regional brain gray matter density , 2011, Psychiatry Research: Neuroimaging.

[13]  Eduardo Pondé de Sena,et al.  Alfa no estado alterado de consciência: meditação raja yoga , 2019, Revista de Ciências Médicas e Biológicas.

[14]  R. Davidson,et al.  Alterations in Brain and Immune Function Produced by Mindfulness Meditation , 2003, Psychosomatic medicine.

[15]  Jun Soo Kwon,et al.  Increased default mode network connectivity associated with meditation , 2011, Neuroscience Letters.

[16]  F. Augustovski,et al.  [CONSORT 2010 Declaration: updated guideline for reporting parallel group randomised trials]. , 2011, Medicina clinica.

[17]  L. Pbert,et al.  Effectiveness of a meditation-based stress reduction program in the treatment of anxiety disorders. , 1992, The American journal of psychiatry.

[18]  Govinda R. Poudel,et al.  Time-varying effective connectivity of the cortical neuroelectric activity associated with behavioural microsleeps , 2016, NeuroImage.

[19]  L. Barsalou,et al.  Effects of Meditation Experience on Functional Connectivity of Distributed Brain Networks , 2012, Front. Hum. Neurosci..

[20]  Vince D. Calhoun,et al.  Questions and controversies in the study of time-varying functional connectivity in resting fMRI , 2020, Network Neuroscience.

[21]  Antônio Jaeger,et al.  Source Memory and Cognitive Control in Gurdjieff Meditators , 2018 .

[22]  Daniel Fraiman,et al.  Biological Motion Coding in the Brain: Analysis of Visually Driven EEG Functional Networks , 2014, PloS one.

[23]  Pedro Montoya,et al.  Spreading Effect of tDCS in Individuals with Attention-Deficit/Hyperactivity Disorder as Shown by Functional Cortical Networks: A Randomized, Double-Blind, Sham-Controlled Trial , 2015, Front. Psychiatry.

[24]  H. Berendse,et al.  The application of graph theoretical analysis to complex networks in the brain , 2007, Clinical Neurophysiology.

[25]  S. Hollup,et al.  Increased theta and alpha EEG activity during nondirective meditation. , 2009, Journal of alternative and complementary medicine.

[26]  Hao He,et al.  Assessing dynamic brain graphs of time-varying connectivity in fMRI data: Application to healthy controls and patients with schizophrenia , 2015, NeuroImage.

[27]  M. A. Muñoz,et al.  Motif-Synchronization: A new method for analysis of dynamic brain networks with EEG , 2015 .

[28]  D. Goleman The Buddha on Meditation and States of Consciousness , 2017 .

[29]  U. Kiran,et al.  The Role of Rajyoga Meditation for Modulation of Anxiety and Serum Cortisol in Patients Undergoing Coronary Artery Bypass Surgery: A Prospective Randomized Control Study , 2017, Annals of cardiac anaesthesia.

[30]  Yi-Yuan Tang,et al.  Short-term meditation induces changes in brain resting EEG theta networks , 2014, Brain and Cognition.

[31]  H. Stanton Gurdjieff and ego-enhancement: a powerful alliance. , 1997, The American journal of clinical hypnosis.

[32]  Klaus Lehnertz,et al.  Capturing time-varying brain dynamics , 2017 .

[33]  Edward T. Bullmore,et al.  Large-Scale Functional Brain Network Reorganization During Taoist Meditation , 2016, Brain Connect..

[34]  B. Kutty,et al.  Just a minute meditation: Rapid voluntary conscious state shifts in long term meditators , 2017, Consciousness and Cognition.

[35]  Mitsuru Kikuchi,et al.  Changes in EEG and autonomic nervous activity during meditation and their association with personality traits. , 2005, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[36]  M. Chun,et al.  Functional connectome fingerprinting: Identifying individuals based on patterns of brain connectivity , 2015, Nature Neuroscience.

[37]  E. Bass,et al.  Meditation programs for psychological stress and well-being: a systematic review and meta-analysis. , 2014, JAMA internal medicine.