Integrated Phenomenology and Brain Connectivity Demonstrate Changes in Nonlinear Processing in Jhana Advanced Meditation

We present a neurophenomenological case study investigating distinct neural connectivity regimes during an advanced concentrative absorption meditation series called jhana (ACAM-J), characterized by highly stable attention and mental absorption. Using EEG recordings and phenomenological ratings (29 sessions) from a meditator with +20,000 hr of practice, we evaluated connectivity metrics tracking distinct large-scale neural interactions: nonlinear (weighted symbolic mutual information and directed information), capturing non-oscillatory dynamics, and linear (weighted phase lag index) connectivity metrics, capturing oscillatory synchrony. Results demonstrate ACAM-J are better distinguished by non-oscillatory compared with oscillatory dynamics across multiple frequency ranges. Furthermore, combining attention-related phenomenological ratings with weighted symbolic mutual information improves Bayesian decoding of ACAM-J compared with neural metrics alone. Crucially, deeper ACAM-J indicate an equalization of feedback and feedforward processes, suggesting a balance of internally and externally driven information processing. The results from this intensively sampled case study are a promising initial step in revealing the distinct neural dynamics during ACAM-J, offering insights into refined conscious states and highlighting the value of nonlinear neurophenomenological approaches to studying attentional states.

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Publication Details

Journal
Journal of Cognitive Neuroscience
Published
2025-01-01
DOI
https://doi.org/10.1162/jocn.a.50
Citations
4
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
5.72

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article

Integrated Phenomenology and Brain Connectivity Demonstrate Changes in Nonlinear Processing in Jhana Advanced Meditation

Mar Estarellas, Andrés Canales‐Johnson, Ruby M. Potash, Matthew D. Sacchet et al.
4 citations
Journal of Cognitive Neuroscience
EEG and Brain-Computer Interfaces
5.72
article

Integrated Phenomenology and Brain Connectivity Demonstrate Changes in Nonlinear Processing in Jhana Advanced Meditation

Mar Estarellas, Andrés Canales‐Johnson, Ruby M. Potash, Matthew D. Sacchet, Sean D. van Mil
article en
4 citations

Abstract

We present a neurophenomenological case study investigating distinct neural connectivity regimes during an advanced concentrative absorption meditation series called jhana (ACAM-J), characterized by highly stable attention and mental absorption. Using EEG recordings and phenomenological ratings (29 sessions) from a meditator with +20,000 hr of practice, we evaluated connectivity metrics tracking distinct large-scale neural interactions: nonlinear (weighted symbolic mutual information and directed information), capturing non-oscillatory dynamics, and linear (weighted phase lag index) connectivity metrics, capturing oscillatory synchrony. Results demonstrate ACAM-J are better distinguished by non-oscillatory compared with oscillatory dynamics across multiple frequency ranges. Furthermore, combining attention-related phenomenological ratings with weighted symbolic mutual information improves Bayesian decoding of ACAM-J compared with neural metrics alone. Crucially, deeper ACAM-J indicate an equalization of feedback and feedforward processes, suggesting a balance of internally and externally driven information processing. The results from this intensively sampled case study are a promising initial step in revealing the distinct neural dynamics during ACAM-J, offering insights into refined conscious states and highlighting the value of nonlinear neurophenomenological approaches to studying attentional states.

Journal of Cognitive NeuroscienceVol. 37(11)
University of Helsinki (FI), Harvard University (US), Queen Mary University of London (GB), University of Cambridge (GB), Catholic University of the Maule (CL), Massachusetts General Hospital (US), University of Amsterdam (NL)
Ad Astra Chandaria Foundation, National Institute of Mental Health
Openalex Percentile: Top 4%
EEG and Brain-Computer Interfaces
5.72
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