How meditation work in our brain? This article identify the major brain regions and their dynamic connectivity during meditation. Brain network connectivity approaches to meditation neuroscience are currently accelerating at a rapid pace, propelled by the availability of ‘big fMRI data’, an expanding computational infrastructure, and the formation of large-scale research syndicates and multidisciplinary initiatives focused on mapping the brain connectivity during meditation.
Meditation neuroscience is an emerging research field that investigates the underlying mechanisms of different meditation practices, different stages and different states of practice as well as different effects of practice over the lifespan. The connectivity theory of meditation, which is recently gaining more popularity to explain the brain functions during meditation. Decades of brain research has built a consensus understanding of the brain as an interconnected network of as many as 300 distinct regional brain structures, each of them have their own specialized cognitive functions. During meditation people altered connectivity between these 300 different brain regions in various ways.
The goal of this research work is to identify the major brain regions and their dynamic connectivity during meditation. In this work we are more interested brain network connectivity while meditators are on the cushion. Here connectivity means the flow of information.
Graph Theory and Brain Network
The researchers analyzed the brain images with a technique based on graph theory, a mathematical approach that describes relationships between objects using nodes of a graph connected by lines. Each brain region, or node, is connected to many others. The method determines the strength of each connection based on the synchrony of their firing patterns during the meditation. The researchers also looked at meditator’s’ brain images using diffusion tensor imaging, which indirectly gauges the strength of connections by tracking the movement of water molecules. Different forms of meditation practice may involve in different brain networks or neuroplasticity. Brain connectivity behaviours related to the practice of an emotion-oriented meditation, and the loving-kindness meditation are different.
Functional connectivity analysis of deep meditation revealed that meditation works in six distinct network hubs. These six network hubs are highly responsive to a wide variety of meditation techniques both for off the cushion as well as on the cushion. These six network hubs are mostly related to: PFC (prefrontal cortex), Insula, Amygdala, PCC (posterior cingulate cortex), ACC (anterior cingulate cortex) and OFC (orbitofrontal cortex) . Other three sub-networks are identified. These sub-networks are mostly located in the posterior areas of brain. These sub-networks are associated with devotion and prayer based meditation techniques.
Our findings suggest that the connectivity of these six-network hubs are not fixed. They are highly dynamic in nature. We also observed that meditation training leads to functional connectivity changes between core default mode network (DMN) regions. We also noticed that individuals who had larger gray matter (GM) volume in the amygdale have different types of brain network hub connectivity. The connectivity between Insular cortex and amygdala and the connectivity between PFC and ACC are most prominent, while on the cushion. During meditation, the deactivations are frequently located in the “default-mode network”.
We studied the anatomical pattern of integration during Om meditation and non-judgmental mindfulness meditation. We observed longitudinal as well as orthogonal long-distance brain network connectivity during meditation. We observed local as well as global level brain network connectivity during meditation. We compared these patterns of brain network activity with the activities during fears and emotions. We noticed different forms of meditation practice involve in different brain networks. We noticed integration of functional brain network connectivity is optimal in case of deep Om meditation both on the cushion and out of the cushion.
Limitations of the Present Work:
For a non-invasive scan, fMRI has moderately good spatial resolution. However, the temporal resolution of fMRI method is very poor and not suitable for analyzing the dynamic nature of the brain network activities. fMRI scans are not fit for capturing dynamic neuronal communication. fMRI is not a truly quantitative measure of neural activities. Most FMRI investigators seek not to localize brain function but to map the parts of the system that act in different groupings for different tasks. To overcome the limitations of fMRI data, EEG and EMG data along with fMRI data are analyzed with quantitative methods.
While imaging studies are promising when it comes to potential breakthroughs in meditation research. However, increasingly the researchers across the world are realizing its limitations. To understand the deeper aspects of meditation, both imaging techniques as well as quantitative insights are used into general topological principles of brain network organization during meditation. Activities of six major network hubs are identified during meditation. These six network hubs are: PFC, Insula, Amygdala, PCC, ACC and OFC. However, more work is necessary to understand the deeper levels of brain networks during meditation.