Thoughtseeds

Methods & Techniques

• Employs a hierarchical model structured as nested Markov blankets.
• Simulates focused-attention Vipassana meditation using rule-based training informed by neuroscience.
• Utilizes computational modeling combined with phenomenological insights.
• Applies the framework to investigate meditative states and mind-wandering episodes.

Key Findings

• Identifies four emergent states from thoughtseed interactions: breath_control, mind_wandering, meta_awareness, and redirect_breath.
• Shows that experts maintain control dominance for focused attention, while novices experience frequent mind-wandering.
• Demonstrates self-organizing dynamics in thought processes during meditation.
• Provides testable predictions about meditation skill development and cognitive processes.

Prerequisites

• Probability theory and Bayesian inference basics
• Free Energy Principle and generative models

🎯 Consulting & Tutoring

Daniel Ari Friedman, PhD is available for AI Research Consulting and Tutoring related to this skill.

Related Skills

See BIBLIOGRAPHY.md for the complete publication catalog and related papers.