Arxiv260714833

# arxiv260714833

## Paper: Thoughtseeds as Latent Causes: A Dual-Process Computational Phenomenology of Focused-Attention Meditation
- Authors: Prakash Chandra Kavi, Daniel Ari Friedman, Gustavo Patow
- arXiv: 2607.14833v1
- Abstract: 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.

## Methodology
This skill implements the dual-process computational phenomenology framework for focused-attention meditation. The method combines active inference with a three-layer nested Markov-blanket architecture to model meditation states and transitions.

## Core Idea
The core idea is to model meditation as a dual-process system where:
- System 1 (L2) generates latent mental content as "thoughtseeds" and evaluates autonomic responses
- System 2 (L3) acts as a metacognitive monitor implementing a Global Neuronal Workspace capacity bottleneck
- The system alternates between four attractor states: breath focus, mind-wandering, meta-awareness, and redirect attention

## Application Steps
1. **Model the physiological substrate modeling**: Model the high-dimensional neuronal substrate as a stochastic multivariate Ornstein--Uhlenbeck process over attentional Yeo networks
2. **Latent mental content generation**: Use a low-dimensional generative model (System 1) to encode mental content as thoughtseeds and evaluate autonomic action tendencies
3. **Metacognitive monitoring**: Implement System 2 as an agentic monitor with Global Neuronal Workspace capacity bottleneck that selectively gates tendencies
4. **Attractor state dynamics**: Model transitions between four attractor states: breath focus, mind-wandering, meta-awareness, and redirect attention
5. **Policy selection**: Use active inference to minimize expected free energy for action selection
6. **Perception-action closure**: Use L2 actions to furnish descending predictions over network activity
7. **Training**: Apply variational Expectation-Maximization across expert and novice phenotypes
8. **Validation**: Compare simulations with empirical observations from contemplative neuroscience

## References
- [arXiv:2607.14833] Thoughtseeds as Latent Causes: A Dual-Process Computational Phenomenology of Focused-Attention Meditation

## Activation Keywords
260714833, thoughtseeds, dual-process, active inference, focused-attention meditation, meta-awareness, Global Neuronal Workspace, computational phenomenology