{
  "title": "Dynamic Attentional Agents in Focused Attention Meditation: Hierarchical Computational Modeling of Expert-Novice Differences",
  "domain": "Active Inference",
  "type": "Paper",
  "creators": [
    {
      "name": "P. C. Kavi"
    },
    {
      "name": "Daniel Ari Friedman"
    },
    {
      "name": "G. Patow"
    }
  ],
  "description": "Three-level hierarchical Active Inference framework for focused attention meditation: thoughtseed agents (Markov blankets) couple to DMN/VAN/DAN/FPN; simulations reproduce 49% lower free energy and DMN suppression in expert meditators.",
  "abstract": "We develop a three-level hierarchical framework to model the attentional dynamics of focused attention (FA) meditation, laying a foundation for advanced active inference (AIF) implementations. Grounded in the Free Energy Principle and Neuronal Packet Hypothesis, we conceptualize meditation as a predictive processing system where “thoughtseeds”—transient, agent-like entities forming Markov blankets—minimize variational free energy via bidirectional coupling with attentional networks (DMN, VAN, DAN, FPN). Simulations across biologically plausible parameters reproduce expert–novice differences: 49% lower free energy during breath focus, suppressed DMN activity (0.18 vs. 0.31), and faster distraction recovery.",
  "keywords": [
    "Active Inference",
    "focused attention meditation",
    "thoughtseeds",
    "Free Energy Principle",
    "hierarchical modeling",
    "expert-novice differences",
    "DMN",
    "precision weighting",
    "Neuronal Packet Hypothesis",
    "contemplative neuroscience"
  ],
  "methods": [
    {
      "name": "Free energy minimization",
      "description": "Applied free energy minimization approach"
    },
    {
      "name": "Bayesian modeling and inference",
      "description": "Applied bayesian modeling and inference approach"
    }
  ],
  "key_findings": [
    "Three-level hierarchical Active Inference framework for focused attention meditation: thoughtseed agents (Markov blankets) couple to DMN/VAN/DAN/FPN; simulations reproduce 49% lower free energy and DM"
  ],
  "related_papers": [
    "2018_WoodliceAndMen",
    "2020_BehaviorEngineering",
    "2021_ModelingConflict"
  ],
  "checked_at": "2026-07-01T20:50:01Z"
}