arXiv: 2607.14833

念種作為潛在原因：專注冥想的雙重過程計算現象學

Thoughtseeds as Latent Causes: A Dual-Process Computational Phenomenology of Focused-Attention Meditation

July 16, 2026

作者: Prakash Chandra Kavi, Daniel Ari Friedman, Gustavo Patow

q-bio.NCq-bio.NC

摘要

冥想專業能力涉及持續的注意力、從分心中快速恢復的能力，以及大規模腦網絡的協調動力學。我們提出了一種針對專注冥想的計算現象學，該模型穿越四種吸引子狀態：專注呼吸、心智遊盪、後設覺察及重新導向注意力。在雙重過程主動推理的框架下，該模型實現了三層嵌套馬可夫毯結構：（L1）高維度的生理神經元基質，以隨機多變量奧恩斯坦-烏倫貝克過程模擬注意力相關的Yeo網絡活動；（L2）低維度的生成模型（系統一），編碼潛在心智內容為「思維種子」，並評估自主行動傾向；（L3）具代理性的後設認知監控器（系統二），實施全局神經工作空間（GNW）容量瓶頸，以選擇性地閘控這些傾向。在L3中，後設覺察作為GNW點火信號，源自策略先驗分歧，並經由組織者與干擾者思維種子之間的直接競爭進行動態閘控。策略選擇主動最小化期望自由能，而L2的動作為網絡活動提供下行預測，以閉合生成性感知-行動循環。訓練採用變分期望最大化（EM）方法，區分專家與新手表型。模擬結果再現了與觀察行為及靜觀神經科學實證發現一致的現象，為第一人稱現象學與客觀神經生理測量之間提供了可處理的連結。

English

Meditative expertise involves sustained attention, rapid recovery from distraction, and coordinated dynamics of large-scale brain networks. We present a computational phenomenology of focused-attention meditation traversing four attractor states: breath focus, mind-wandering, meta-awareness, and redirect attention. Within a dual-process active inference formulation, the model implements a three-layer nested Markov-blanket architecture: (L1) a high-dimensional physiological neuronal substrate modeled as a stochastic multivariate Ornstein--Uhlenbeck process over attentional Yeo networks; (L2) a low-dimensional generative model (System 1) that encodes latent mental content as thoughtseeds and evaluates autonomic action tendencies; and (L3) an agentic metacognitive monitor (System 2) that implements a Global Neuronal Workspace (GNW) capacity bottleneck to selectively gate these tendencies. In L3, meta-awareness functions as the GNW ignition signal, derived from policy-prior divergence and dynamically gated by direct competition between orchestrator and distractor thoughtseeds. Policy selection actively minimizes expected free energy, and L2 actions furnish descending predictions over network activity to close the enactive perception--action cycle. Training uses variational Expectation-Maximization (EM) across expert and novice phenotypes. Simulations reproduce behavior consistent with empirical observations and findings in contemplative neuroscience, providing a tractable link between first-person phenomenology and objective neurophysiological measures.