A recent study reveals that different styles of meditation produce distinct, measurable changes in the background noise and structural complexity of human brain waves. By scanning the brains of expert Buddhist monks, researchers demonstrated that meditative states make brain activity more flexible and less bound to past patterns. These results were published in the journal Neuroscience of Consciousness.
Meditation involves a variety of mental strategies aimed at directing attention and cultivating physical and mental well-being. Over the years, brain imaging tools have helped map the specific brain regions that activate during these practices. Researchers are still trying to understand the precise physical mechanisms that allow these mental states to alter human consciousness.
Annalisa Pascarella, a researcher at the National Research Council in Italy, led a team to investigate the brain activity of highly experienced meditators. The team wanted to measure mathematical concepts like criticality and complexity in the human brain. Criticality describes a system resting perfectly on the boundary between strict order and total chaos.
A brain operating near this tipping point is thought to be highly efficient, balancing stability with 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, varied states of consciousness.
Previous research on meditation has produced contradictory results regarding these specific mathematical measures. Many past experiments grouped all meditation styles together or used tools that could not track very fast brain changes. Pascarella and her colleagues sought to correct this by comparing two distinct forms of meditation using highly sensitive equipment.
The research team recruited twelve professional monks from a Buddhist monastery in Italy. These participants had engaged in extensive mental training, boasting an average of over fifteen thousand hours of meditation experience. The researchers focused on two specific techniques known as Samatha and Vipassana.
Samatha is a form of focused attention meditation where the practitioner concentrates entirely on a single object, such as their own breathing. Vipassana is an open monitoring technique that serves a different purpose. In Vipassana, the practitioner maintains a broad awareness of any passing thoughts or sensations without judging or focusing on any single one.
To see what was happening inside the participants’ heads, the researchers used magnetoencephalography. This technology measures the tiny magnetic fields produced by electrical activity in the brain. Magnetoencephalography provides a high-resolution timeline of brain activity, capturing rapid changes that other scanning methods might miss.
The monks sat in the scanner with their eyes closed and completed six-minute blocks of both Samatha and Vipassana meditation. They also rested quietly for three-minute intervals between the meditation sessions. This allowed the researchers to compare the brain’s resting state to its active meditative states.
When analyzing the data, the team looked closely at different types of brain waves. Brain waves are rhythmic electrical pulses, but the brain also produces a steady stream of background electrical noise. In the past, scientists sometimes struggled to separate the 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 inhibit it. Pascarella and her team used advanced software to strip away this background noise and look purely at the rhythmic brain waves.
The results of this separation were unexpected. Before removing the background noise, it appeared that high-frequency brain waves, known as gamma waves, increased during meditation. This would match what many older studies had reported about the meditative brain.
However, once the aperiodic background noise was factored out, the actual rhythmic gamma waves decreased during both types of meditation. The researchers concluded that the previously reported increases were likely an illusion caused by a shift in the brain’s overall background noise, rather than a true increase in rhythmic gamma activity. The steepness of the background noise curve flattened out, which points to a higher ratio of neural excitation to inhibition.
This drop in true gamma waves might reflect the calming of networks that normally process external distractions. The researchers noticed these decreases mainly in areas like the frontal and parietal lobes, which handle attention and physical movement. By reducing rhythmic activity in these areas, the brain might be shifting away from active mental engagement toward a state of integrated awareness.
The changes observed during meditation were mapped to specific networks within the brain. The researchers noted strong effects in a system usually active when the mind is wandering or daydreaming. Altering the activity in this network is likely what allows experienced meditators to silence internal chatter and maintain focus.
Beyond the wave frequencies, the researchers examined the complexity of the brain signals. They applied several mathematical tests to see how much a brain signal repeated itself. They found that brain activity became much more complex and less predictable during both Samatha and Vipassana meditation compared to the resting state.
They also measured how tightly a current brain signal is linked to past brain signals, a concept known as a temporal correlation. During both types of meditation, these temporal correlations dropped. This means the brain’s activity became less restricted by its recent past, creating a more adaptable and flexible mental environment.
The researchers also investigated whether a monk’s total hours of lifetime practice influenced their brain patterns. They discovered a trend suggesting that the most experienced monks exhibited brain dynamics during meditation that looked very similar to their resting states. This hints that thousands of hours of practice might permanently alter the brain’s baseline resting behavior.
To test how reliably these mathematical features could identify a meditative state, the researchers employed machine learning. They trained a computer algorithm to review all the brain data and guess whether a participant was resting or meditating. The algorithm successfully identified the correct brain state with a high degree of accuracy.
The algorithm ranked the drop in temporal correlations as the most helpful clue for distinguishing a meditating brain from a resting brain. This suggests that the brain’s release from past structural patterns is a defining feature of advanced meditation. The computer program also confirmed that these changes were distributed widely across the outer layers of the brain.
The team also measured the brain’s distance from the critical tipping point between order and chaos. They found a notable difference between the two meditation styles in this metric. During Vipassana, the brain moved closer to this critical boundary.
By contrast, Samatha meditation did not push the brain closer to this critical tipping point. The researchers suspect this reflects the different cognitive goals of the two practices. Vipassana requires an open, highly sensitive awareness of the present moment, which matches the flexible nature of a critical state.
Samatha requires deep, stable concentration, which may require the brain to stay firmly within a more ordered state. These findings show that the brain adapts its fundamental operating rules to match the specific demands of different contemplative practices. Different meditation styles physically alter the brain’s relationship with order and chaos in unique ways.
The study authors acknowledge a few limitations in their work. The pool of participants was small, which is a common problem when studying individuals with thousands of hours of highly specialized training. The results did not show a statistically significant correlation for some of the age-related observations after mathematical corrections were applied.
Additionally, the study lacked a control group of people with no meditation experience. This makes it difficult to know if the observed brain changes are unique to experts or if they would also happen in beginners. The researchers hope to address these gaps in future experiments with larger and more diverse groups of people.
Future research will likely involve building computer models to simulate these precise brain states. The team suggests that exploring other definitions of chaos could yield even deeper insights into human consciousness. Such work could eventually help medical professionals tailor specific meditation techniques to treat distinct psychological conditions.
The study, “Meditation induces shifts in neural oscillations, brain complexity, and critical dynamics: novel 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.
