Recent research has shown that different styles of meditation produce clear and measurable changes in the background noise and structural complexity of human brain waves. By scanning the brains of expert Buddhist monks, researchers demonstrated that during meditative states, brain activity becomes more flexible and less tied to past patterns. These results were published in the journal neuroscience of consciousness.
Meditation involves a variety of mental strategies aimed at focusing attention and promoting physical and mental health. For years, brain imaging tools have helped map the specific brain regions that are activated during these practices. Researchers are still trying to understand the exact physical mechanisms that allow these mental states to alter human consciousness.
Annalisa Pascarella, a researcher at the Italian National Research Council, led a team that investigated the brain activity of experienced meditators. The team wanted to measure mathematical concepts such as importance and complexity in the human brain. Criticality refers to a system existing entirely on the boundary between strict order and complete chaos.
Brains operating near this tipping point are thought to be highly efficient, with a balance of stability and the flexibility needed to process new information. Complexity refers to how rich, diverse, and unpredictable brain signals are over time. Highly complex brain signals often correspond to rich and diverse states of consciousness.
Previous research on meditation has yielded conflicting results regarding these specific mathematical measures. Many experiments in the past have grouped all meditation styles together or used tools that cannot track very fast brain changes. Pascarella and her colleagues sought to correct this problem by using sensitive equipment to compare two different forms of meditation.
The research team recruited 12 professional monks from a Buddhist monastery in Italy. These participants had engaged in extensive spiritual training and boasted an average of over 15,000 hours of meditation experience. The researchers focused on two specific techniques known as Samata and Vipassana.
Samata is a form of concentrated meditation in which the practitioner focuses completely on a single object, such as his or her breath. Vipassana is an open monitoring method that serves different purposes. In Vipassana, the practitioner maintains a broad awareness of every thought and feeling that passes through them, without judging or focusing on a single thought or feeling.
To find out what was going on in the participants’ heads, the researchers used magnetoencephalography. This technology measures tiny magnetic fields generated by electrical activity in the brain. Magnetoencephalography provides a high-resolution timeline of brain activity, capturing rapid changes that may be missed by other scanning methods.
The monks sat in the scanner with their eyes closed and completed a six-minute block of both Samata and Vipassana meditations. They also rested quietly for three minutes between meditation sessions. This allowed the researchers to compare the brain’s resting state with an active meditative state.
When analyzing the data, the team looked closely at different types of brain waves. Brain waves are rhythmic electrical pulses, but the brain also generates a steady stream of background electrical noise. In the past, scientists have sometimes struggled to separate rhythmic waves from this non-rhythmic background noise.
This background noise is often described mathematically as an aperiodic slope. The steepness of this slope is thought to reflect the balance between brain cells that stimulate activity and those that suppress it. Pascarella and her team used sophisticated software to filter out this background noise and examine purely rhythmic brain waves.
The results of this separation were unexpected. Before removing background noise, high-frequency brain waves known as gamma waves appeared to increase during meditation. This is consistent with what many older studies have reported about the meditative brain.
However, removing non-periodic background noise reduced the actual rhythmic gamma waves during both types of meditation. The researchers concluded that the increases reported so far were likely an illusion caused by changes in background noise throughout the brain, rather than a true increase in rhythmic gamma activity. The steepness of the background noise curve becomes flattened, indicating a higher ratio of neural excitation to inhibition.
This drop in true gamma waves may reflect quiescence in networks that normally process external distractions. Researchers noticed that these reductions were seen in areas such as the frontal and parietal lobes, which primarily deal with attention and body movement. By reducing rhythmic activity in these areas, the brain may be transitioning from active mental activity to a state of integrated consciousness.
The changes observed during meditation were mapped to specific networks in the brain. The researchers noted the strong influence of systems that are typically active when the mind wanders or daydreams. By changing the activity within this network, experienced meditators may be able to silence their internal chatter and maintain focus.
The researchers looked beyond wave frequency to examine the complexity of brain signals. They applied several mathematical tests to find out how often brain signals repeat. They found that during both Samata and Vipassana meditation, brain activity became much more complex and less predictable than in the resting state.
They also measured how closely current brain signals are related to past brain signals, a concept known as temporal correlation. Both types of meditation reduced these temporal correlations. This means that brain activity is no longer limited by the recent past, creating a more adaptive and flexible mental environment.
The researchers also investigated whether the monks’ total lifetime training time affected their brain patterns. They found trends suggesting that the most experienced monks exhibited brain dynamics during meditation that were very similar to those at rest. This suggests that thousands of hours of practice can permanently change the brain’s baseline resting behavior.
To test how reliably these mathematical features could identify meditative states, the researchers employed machine learning. They trained a computer algorithm to review all the brain data and infer whether participants were resting or meditating. This algorithm succeeded in identifying the correct brain state with high accuracy.
The algorithm ranked reduced temporal correlation as the most useful cue to distinguish between meditating and resting brains. This suggests that freeing the brain from past structural patterns is a hallmark of advanced meditation. The computer program also confirmed that these changes were widely distributed throughout the outer layers of the brain.
The researchers also measured the brain’s distance from the critical tipping point between order and chaos. They found significant differences between the two meditation styles on this measure. During Vipassana, the brain approaches this critical boundary.
In contrast, samatha meditation did not bring the brain closer to this critical tipping point. The researchers believe this may reflect the different cognitive goals of the two practices. Vipassana requires an open and highly sensitive awareness of the present moment, which is consistent with the flexible nature of the critical state.
Samata requires deep and steady concentration, which may require the brain to remain firmly in a more orderly state. These findings indicate that the brain adapts its basic operating rules to suit the specific demands of different meditation practices. Different meditation styles physically alter the brain’s relationship with order and chaos in unique ways.
The study authors acknowledge that their study has some limitations. The number of participants was small, which is a common problem when studying individuals with thousands of hours of highly specialized training. The results showed no statistically significant correlations for some of the age-related observations after applying mathematical corrections.
Additionally, this study did not include a control group with no meditation experience. This makes it difficult to know whether the observed brain changes are specific to experts or also occur in novices. The researchers hope to address these gaps in future experiments with larger and more diverse populations.
Future research could include building computer models that simulate these precise brain states. The researchers suggest that exploring other definitions of chaos may provide even deeper insights into human consciousness. Such research could ultimately help medical professionals tailor specific meditation techniques to treat individual psychological conditions.
The study, “Meditation induces changes in neural oscillations, brain complexity, and key dynamics: new insights from MEG,” was authored by Annalisa Pascarella, Philipp Thölke, David Meunier, Jordan O’Byrne, Tarek Lajnef, Antonino Raffone, Roberto Guidotti, Vittorio Pizzella, Laura Marzetti, and Karim Jerbi.
