bioRxiv Preprint Server
August 29, 2024
Saketh Malipeddi, Arun Sasidharan, Rahul Venugopal et al.
4 citations
preprint
Advanced meditators from the Isha Yoga tradition show shorter intrinsic neural timescales (INTs) during breath-watching, indicating deidentification with mental contents, and no significant differences in INTs between tasks, indicating non-dual awareness. Shorter INTs correlate with self-reported equanimity. The brain's intrinsic neural timescales may serve as a neural marker of equanimity.
bioRxiv Preprint Server
February 11, 2025
Saketh Malipeddi, Arun Sasidharan, Rahul Venugopal et al.
2 citations
preprint
Meditation alters brain activity, particularly in alpha and theta frequency bands, but most research has focused on average power changes from rest to meditation rather than how quickly these changes emerge. This gap means little is known about the time-to-onset and temporal dynamics of neural shifts during meditation practice.
bioRxiv Preprint Server
September 27, 2022
Sruthi Susan Kuriakose, Aishwarya Swamy, Rahul Venugopal et al.
2 citations
preprint
Meditation proficiency is hard to achieve without feedback because the mind easily wanders. EEG neurofeedback could help by providing real-time assessment. This work proposes a lightweight scheme using an autoencoder model trained on EEG features from long-term meditators. The model runs in real time on short data segments from a few channels, using reconstruction errors or latent variables as feedback parameters to measure meditation ability. However, results show that meditation states overlap substantially in multivariate EEG features and have prominent temporal dynamics, which simple one-class algorithms fail to capture. Multiple improvements to the autoencoder are described to address these issues and enable high-precision neurofeedback protocols.
bioRxiv (Cold Spring Harbor Laboratory)
June 26, 2025
Prakash Shrimali, Arun Sasidharan, Saketh Malipeddi et al.
1 citation
preprint
Meditation involves training attention inward, but the brain activity that distinguishes meditative from non-meditative states across different traditions is not well understood. Analyzing high-density EEG data from 170 participants—121 advanced meditators and 49 controls—across Vipassana, Brahma Kumaris Raja Yoga, Heartfulness, and Isha Yoga traditions, researchers used random forest classifiers to distinguish meditative from non-meditative states with 91% accuracy. Nonlinear features contributed most, indicating a core neurodynamic profile. Classification was higher in advanced meditators (92%) than controls (85%), with different feature importance: nonlinear and aperiodic features dominated in meditators, while oscillatory and timescale features dominated in controls. Each tradition showed distinct neurodynamic profiles, suggesting multiple pathways lead to meditative states.
Communications Biology
June 12, 2026
Saketh Malipeddi, Arun Sasidharan, Bianca Ventura et al.
Advanced meditators from the Isha Yoga tradition report stronger non-dual experiences—where the boundary between self and environment dissolves—during breath-watching meditation compared to novices and meditation-naïve controls. Using EEG-based intrinsic neural timescales (INT), researchers found that across all participants, INTs are longer during internal attention (breath-watching) than during an external cognitive task. However, advanced meditators show similar INT durations between internal and external attention, and this reduced difference correlates with stronger reported non-dual experiences. The findings suggest that similar intrinsic neural timescale durations across internal and external attention may be a neural signature of non-duality.
bioRxiv Preprint Server
May 27, 2026
Praerna Chowdhury, Ramajayam Govindaraj, Arun Sasidharan et al.
preprint
Meditation-related EEG patterns are often studied by comparing meditators to passive rest or by experience level, but such designs rarely test reliability or include active controls. This study used a multi-session within-subject design with experienced Brahmakumaris Rajayoga meditators to identify reliable, state-dependent EEG dynamics. The approach addressed prior limitations, providing more valid neurophysiological markers of meditative state.
Consciousness and cognition
July 1, 2025
Gulshan Kumar, Safoora Naaz, Nahida Jabin et al.
Dream recall is more frequent after REM sleep than N2 sleep. During dream recall, EEG beta activity increases, functional connectivity within the default mode network strengthens, and the medial frontal cortex activates, regardless of sleep stage. Auditory stimulation during sleep can influence the emotional content of dreams, suggesting that targeted memory reactivation may be possible. These findings help clarify how conscious experience arises during sleep.