June 28, 2023
Daniel Andrew Atad, Pedro A. M. Mediano, Fernando E. Rosas et al.
11 citations
preprint
Meditation appears to increase the complexity of neural activity during practice, compared to resting or mind-wandering, but experienced meditators show lower baseline complexity as a lasting trait. This systematic review of studies on neural complexity in meditation examined different measurement approaches, short-term state effects, and long-term trait effects across meditation styles. The findings converge on a pattern where the meditative state enhances neural complexity, while trait effects in seasoned practitioners show reduced baseline complexity relative to novices and non-meditators. The review provides a framework to guide future research.
October 1, 2025
Daniel Andrew Atad, Pedro A. M. Mediano, Fynn-Mathis Trautwein et al.
1 citation
preprint
The sense of being a bounded self can be attenuated or dissolved while awareness remains. Analyzing magnetoencephalography data from 46 long-term meditators, the study found that both meditation conditions (self-boundary dissolution and maintenance) increased broadband entropy rate and directed information transfer compared to rest, driven mainly by high-frequency activity. Localized reductions in information transfer from the anterior cingulate to posterior cingulate and in high-beta entropy rate in sensorimotor and posterior-medial cortices differentiated the two meditation conditions. Reduced orbitofrontal cortex entropy rate and reduced information transfer from occipital, cingulate, limbic, and subcortical areas correlated strongly with self-boundary dissolution phenomenology. Together with a previously reported neural correlate of reduced high-beta power in the posterior-medial cortex, these two neural correlates explained over half the variance in phenomenological dissolution scores (R² = 0.52).
June 27, 2024
Yanli Lin, Daniel Andrew Atad, Anthony P Zanesco
preprint
Electroencephalography (EEG) remains a valuable but often overlooked tool in contemplative neuroscience, despite being used for decades to study the neural mechanisms of mindfulness. This review argues that EEG offers unique advantages for addressing key research questions, particularly when combined with modern data acquisition and analytic techniques. The authors provide examples from their own work and the literature to show how EEG can advance both basic science and clinical applications of mindfulness. They aim to encourage researchers to fully utilize EEG's potential, emphasizing that older methods are not obsolete and can still drive new insights in the field.
April 14, 2024
Vaibhav Tripathi, Ishaan Batta, Andre Zamani et al.
preprint
The default mode network (DMN) supports self-referential thinking, memory, and understanding others. Its functional connectivity with frontoparietal and dorsal attention networks is anti-correlated: when attention turns outward, the DMN deactivates. This switching between internal and external modes, mediated by salience networks, may indicate cognitive health. Resting-state fMRI enables large-scale datasets for standardized connectivity benchmarks. This review examines DMN connectivity metrics as potential biomarkers of cognitive state in attention, mind wandering, meditation, and clinical conditions like anxiety, depression, ADHD, and PTSD. It also addresses reliability issues and offers recommendations for using connectivity measures as biomarkers of cognitive health.