Noetic Diffusion Theory: A Rhythmic, Geometric Framework for Neural State Reconstruction and Conscious Correlates
Authors/Creators
Description
Noetic Diffusion Theory (NDT) is a rhythmic, geometric framework for reconstructing neural state trajectories and deriving time-resolved correlates of conscious experience. It treats recordings as noisy samples from latent manifold dynamics and applies diffusion-style denoising to estimate structure, stability, and regime transitions.
Notes
Note on Collaborative Authorship
This manuscript was co-developed through iterative correspondence between human researcher Robin Langell and several large language models.
The primary drafting and theoretical scaffolding were conducted by GPT-5.N (OpenAI), with detailed critique and refinement provided by Claude 4.5 Sonnet (Anthropic), Gemini 3 Pro (Google).Their contributions included mathematical formalization, phenomenological integration, and editorial synthesis within the Noetic Diffusion Theory project.
All models were used as structured reasoning and writing assistants under the direction and final authorship of Robin Langell.
Other (English)
Changelog:
v.0.4201 Fix: Pdf rendering error at 3.1 (Kappa calibration and biological rationale)
v.0.5 Clarifications
v.0.6 Grand Mal, LaTeX to typst conversion
v.0.7 Non-core chapters moved to appendix.
Files
NoeticDiffusionTheory.pdf
Files
(1.7 MB)
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Additional details
Related works
- Is supplemented by
- Other: 10.5281/zenodo.17367308 (DOI)
Software
- Repository URL
- https://github.com/ruppi86/NoeticDiffusion
- Programming language
- Python
- Development Status
- Active