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 hr of practice, we evaluated connectivity metrics tracking distinct large-scale neural interactions: nonlinear (weighted symbolic mutual information and directed information), capturing nonoscillatory dynamics, and linear (weighted phase lag index) connectivity metrics, capturing oscillatory synchrony. Results demonstrate ACAM-J are better distinguished by nonoscillatory 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.