Meditation can be conceptualized as a family of complex emotional and attentional regulatory training regimes (Lutz, Slagter, Dunne, & Davidson, 2008). In research and clinical contexts, mindfulness meditation is often defined as a practice with nonjudgmental attention to experiences in the present moment (Kabat-Zinn, 1990). However, one of the major issues in the literature is the inconsistency of operational definitions of meditation (Awasthi, 2013, Cahn and Polich, 2006 and Williams and Kabat-Zinn, 2011). For example, Bishop et al. (2004) proposed an operational definition including self-regulation of attention, which would seem to be one of the key ingredients believed to be active in mindfulness. Nevertheless, mindfulness neuroscience or contemplative neuroscience is an emerging research field that investigates the underlying mechanisms of different mindfulness practices, different stages and different states of practice as well as different effects of practice over the lifespan. Mindfulness neuroscience research integrates theory and methods from eastern contemplative traditions, western psychology and neuroscience, and from neuroimaging techniques, physiological measures and behavioral tests (Tang & Posner, 2013).
Meditation has recently received increasing attention as a vehicle for understanding training-related brain plasticity. Previous studies have reported meditation relates to changes in brain structure and function such as increased regional cortical thickness (Lazar et al., 2005), grey matter densities (Luders et al., 2009 and Vestergaard-Poulsen et al., 2009), white mater connectivity (Luders et al., 2011, Tang et al., 2012 and Tang et al., 2010), reorganization of cognitive resources (Hölzel et al., 2011 and Slagter et al., 2007), and the default mode network connectivity (Brewer et al., 2011 and Jang et al., 2011).
Integrative Body–Mind Training (IBMT) is one form of mindfulness meditation that originates from ancient eastern contemplative traditions, including traditional Chinese medicine, Zen, etc. IBMT shares several key components with other forms of meditation, including relaxation, mental imagery, and mindfulness. IBMT stresses no effort or less effort to control thoughts, and the achievement of a state of restful alertness that allows a high degree of awareness and balance of the body, mind, and environment (Tang, Rothbart, & Posner, 2012). A number of randomized clinical trials indicate that IBMT improves attention and self-regulation and induces neuroplasticity through interaction between the central and the autonomic nervous systems (Tang et al., 2007, Tang et al., 2009 and Tang et al., 2010). For example, 4-week IBMT has been reported to increase network efficiency of the anterior cingulate cortex (Xue, Tang, & Posner, 2011) and connectivity of the white matter surrounding the anterior cingulate cortex (Tang et al., 2010 and Tang et al., 2012).
Recently, brain networks derived from functional magnetic resonance imaging (fMRI) or electroencephalography (EEG) have been consistently reported to exhibit an optimal organization pattern for information processing, such as high clustering coefficient and short path lengths (Stam, Jones, Nolte, Breakspear, & Scheltens, 2007), and high efficiency of information transfer for low wiring costs (Achard & Bullmore, 2007), suggesting the balance of functional integration and segregation (Rubinov & Sporns, 2010). Recent studies indicated differences in the network topological parameters associated with an array of factors including diseases (Seeley, Crawford, Zhou, Miller, & Greicius, 2009) and different task conditions (Bullmore & Sporns, 2009). Besides, using network science to evaluate exercise-associated brain changes is also becoming increasingly attractive (Bassett et al., 2011 and Burdette et al., 2010).
Electrophysiological studies have observed altered theta activity is linked to meditation practice (Cahn and Polich, 2006, Rubia, 2009 and Tang et al., 2009). Our previous study has also reported five days of IBMT induced increased EEG power in the theta frequency band at frontal midline electrodes (Tang et al., 2009). Based on these studies, we hypothesize that meditation experience is associated with changes in brain networks derived from resting-state EEG theta activity. We thus combine synchronization likelihood method, network analysis, and IBMT to test the hypothesis.
