Integrated phenomenology and brain connectivity demonstrate changes in nonlinear processing in jhana advanced meditation

Summary

The study shows that during an advanced meditation practice called jhana, non-oscillatory neural dynamics are more effective in distinguishing meditative states than oscillatory dynamics. It involved EEG recordings from a meditator with over 20,000 hours of practice across 29 sessions. The findings suggest that deeper jhana experiences lead to a balance between feedback and feedforward processes in the brain, enhancing our understanding of conscious states and attentional processes.

Study at a glance

Abstract

Abstract We present a neurophenomenological case study investigating distinct neural connectivity regimes during an advanced concentrative absorption meditation 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 hours of practice, we evaluated connectivity metrics tracking distinct large-scale neural interactions: nonlinear (WSMI and Directed Information), capturing non-oscillatory dynamics; and linear (WPLI) connectivity metrics, capturing oscillatory synchrony. Results demonstrate ACAM-J are better distinguished by non-oscillatory compared to oscillatory dynamics across multiple frequency ranges. Furthermore, combining attention-related phenomenological ratings with WSMI improves Bayesian decoding of ACAM-J compared to 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.