Meditation, encompassing diverse practices, enhances physiological functions and self-regulation. Western research often focuses on mindfulness, defined as present-moment awareness without judgment. Key classifications include Open Monitoring Meditation (OMM), involving non-reactive monitoring of experience, and Focused Attention Meditation (FAM), focusing on a chosen object. OMM activates brain regions crucial for body awareness and attention; FAM, known as concentrative meditation in Tibetan Buddhism, is widely studied and involves refocusing attention when the mind wanders, eventually leading to a state of calm abiding (Shamatha). Existing research using fMRI and EEG reveals that concentrative meditation affects the Default Mode Network, showing increased activity in regions related to cognitive and attention control, and decreased activity in areas linked to mind-wandering. Analytical meditation, the other main type in Tibetan Buddhism, involves deep analysis of concepts, similar to Vipassana. However, inconsistencies in meditation research highlight the need for more diverse samples and ecological studies. This study leveraged a collaboration with the Sera Jey Monastery to investigate the neural correlates of both analytical and concentrative meditation in a homogeneous sample of monks with varying experience levels, all within their natural environment.

The literature review highlights the heterogeneity of meditation practices and the challenges in comparing objective measurements with subjective experiences. Existing studies show that concentrative meditation is associated with increased alpha and theta power in EEG, potentially indicating enhanced awareness and well-being. While analytical meditation is less studied, it's understood to involve deep analysis of concepts within the Dharma. The researchers emphasize the need to address the limitations of past studies by collaborating directly with monastic communities, reducing the gap between objective measures and the meditators' subjective experiences.

This study involved 23 male monks and Geshes from the Sera Jey Monastery in India, categorized into beginners, intermediate, and advanced groups based on their experience. EEG data were collected within the monastery using a portable 19-channel system, minimizing the influence of a laboratory setting. Participants performed either analytical or concentrative meditation sessions, with a 5-minute baseline resting-state recording before each session. The length of meditation sessions was determined by each individual's capabilities, aiming at "their best performance". EEG data were preprocessed using several steps: downsampling, filtering, bad channel removal and recovery, ICA for artifact rejection and average referencing. Time-varying power spectral density (tvPSD) analysis was performed using a sliding-window approach, extracting features for Average Frequency Band (AFB) PSD and Continuous High Resolution (CHR) PSD. Statistical analysis included within-session Wilcoxon rank-sum tests to compare each 5-min window to the baseline and between-session linear mixed models to compare analytical and concentrative meditation across groups. A separate analysis focused on advanced meditators' retreat duration and its impact on alpha peak variation.

The study's key findings indicate that concentrative meditation induced more numerous and pronounced changes in EEG power compared to analytical meditation. Concentrative meditation primarily showed increases in theta, alpha, and beta frequency ranges compared to baseline. Direct comparison between the two meditation types revealed several significant differences in EEG features. Positive deviations from baseline were considerably higher during concentrative meditation across various frequency bands (θ, α1, α2, β1, β3, γ). The maximum variation of the alpha peak (Δα-peak) showed the most striking difference, being significantly higher in concentrative sessions. A marked peak (bump) in the beta frequency range was observed in many sessions, especially among advanced meditators, regardless of meditation type. Further observations include the temporary disappearance and reappearance of alpha peaks in some concentrative sessions. Also, an inverse relationship between theta/alpha and beta/gamma power was observed in some advanced meditators during concentrative sessions, indicating a possible counterbalancing mechanism within the brain. Finally, the duration of retreat had a significant effect on the maximum variation of the alpha peak, suggesting increased EEG changes with more experience.

The findings support the hypothesis that analytical and concentrative meditation have distinct neural correlates. Concentrative meditation's increased theta, alpha, and beta activity aligns with previous research linking these frequencies to inwardly directed attention, calmness, and well-being. The study's ecological design and the inclusion of a diverse sample enhance the validity of these results, especially regarding advanced meditators. The observed beta bump and the inverse relationship between theta/alpha and beta/gamma oscillations require further investigation to better interpret their meanings. Future research could incorporate subjective experience data and connectivity measures to deepen understanding.

This study provides novel insights into the neurophysiological differences between concentrative and analytical meditation. Concentrative meditation exhibited more prominent EEG changes, mainly increases in lower-frequency bands. The study's unique ecological approach contributes significantly to the field. Future research should focus on expanding the sample size, balancing the number of participants across experience levels and meditation types, and integrating subjective experience measures to enhance understanding of these complex practices.

The study's limitations include the unbalanced number of participants across experience levels and meditation types, potential influence of experience level on the results, and the absence of subjective experience data during the sessions. The relatively small sample size of the retreat duration analysis limits generalizability of those findings. Further refinements of the data acquisition and processing could be explored.