心理学
非线性系统
冥想
认知心理学
现象学(哲学)
先验与后验
人工智能
计算机科学
人工神经网络
相互信息
机器学习
神学
量子力学
认识论
物理
哲学
作者
Ruby M. Potash,Sean D. van Mil,Mar Estarellas,Andrés Canales‐Johnson,Matthew D. Sacchet
摘要
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.
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