Abstract
This study examines the effects of focused-attention meditation on functional brain states in novice meditators. There are a number of feature metrics for functional brain states, such as functional connectivity, graph theoretical metrics, and amplitude of low frequency fluctuation (ALFF). It is necessary to choose appropriate metrics and also to specify the region of interests (ROIs) from a number of brain regions. Here, we use a Tucker3 clustering method, which simultaneously selects the feature vectors (graph theoretical metrics and fractional ALFF) and the ROIs that can discriminate between resting and meditative states based on the characteristics of the given data. In this study, breath-counting meditation, one of the most popular forms of focused-attention meditation, was used and brain activities during resting and meditation states were measured by functional magnetic resonance imaging. The results indicated that the clustering coefficients of the eight brain regions, Frontal Inf Oper L, Occipital Inf R, ParaHippocampal R, Cerebellum 10 R, Cingulum Mid R, Cerebellum Crus1 L, Occipital Inf L, and Paracentral Lobule R increased through the meditation. Our study also provided the framework of data-driven brain functional analysis and confirmed its effectiveness on analyzing neural basis of focused-attention meditation.
Highlights
Mindfulness meditation is said to be influential in physicality, cognition, and mentality, and has positive effects on well-being (Carmody and Baer, 2008; Chiesa and Serretti, 2009)
We investigated the differences between restingand meditative brain states induced by focused-attention meditation in novice meditators
Functional changes in brain states were analyzed by the Tucker3 clustering (T3Clus) method applied to the three graph theoretical metrics, degree centrality, betweenness centrality, and clustering coefficient and one spontaneous local activity measure, fractional ALFF (fALFF), calculated from the fMR images measured
Summary
Mindfulness meditation is said to be influential in physicality, cognition, and mentality, and has positive effects on well-being (Carmody and Baer, 2008; Chiesa and Serretti, 2009). Hasenkamp et al have revealed that there were four cognitive states during meditation: FOCUS (representing maintenance of attentional focus on the breath), MW (representing mind wandering or loss of focus), AWARE (representing the awareness of mind wandering), and SHIFT (representing shifting of focus back to the breath). They found that the different brain regions were activated in each cognitive state (Hasenkamp et al, 2012). Their proposed model has been widely used to interpret the dynamics of the cognitive states during meditation. They have reported that the functional connectivity between the dlPFC in the central executive network (CEN) and the right insula in the salience network (SN) was higher in experienced, long-term meditators compared with short-term meditators (Hasenkamp and Barsalou, 2012)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
