Compressive Vasomotion Hypothesis (CVH) — vasomotion as a fast compression sweep that collapses ambivalent neural resonances (the Bayesian-blur problem) into a definite state. Use when modeling the ~100ms taṇhā 'grab', precision-weighting as compression forcefulness, or the generative collapse step of vasocomputational active inference.
Scanned 9/6/2026
Install to Claude Code
npx -y skills add plurigrid/asi --skill compressive-vasomotion --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Compressive Vasomotion?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/plurigrid-compressive-vasomotion)More formats (shields.io, HTML) on the badges page.
---
name: compressive-vasomotion
description: "Compressive Vasomotion Hypothesis (CVH) — vasomotion as a fast compression sweep that collapses ambivalent neural resonances (the Bayesian-blur problem) into a definite state. Use when modeling the ~100ms taṇhā 'grab', precision-weighting as compression forcefulness, or the generative collapse step of vasocomputational active inference."
license: MIT
metadata:
trit: 1
source: "https://opentheory.net/2023/07/principles-of-vasocomputation-a-unification-of-buddhist-phenomenology-active-inference-and-physical-reflex-part-i/"
---
# compressive-vasomotion
The **Compressive Vasomotion Hypothesis (CVH)** (Johnson 2023): the vasomotion reflex — the undulation of VSMCs wrapping every blood vessel — functions as a **compression sweep on nearby neural resonances**, collapsing and merging fragile, ambivalent patterns (the "Bayesian blur") into a more durable, definite state. This is the **+1 / generate** leg of the vasocomputation timescale triad: the fast initial "grab" that *creates* specificity.
## Use When
- Modeling the ~25–100 ms taṇhā "fast grabby thing" as a physical compression event
- Reframing precision-weighting as two terms: sensory clarity available vs. compression *forcefulness* applied (the KL divergence between them ≈ a number for taṇhā)
- Representing the generative collapse step where a superposition of interpretations is jostled into one
- Coupling local electromagnetic-field dissonance → vasomotion trigger → resonance collapse
## Core Concepts
- **Compression sweep**: motifs of vasomotion, reflexive reactions to uncertainty, and patterns of taṇhā are *equivalent*. The brain pushes "what is" toward stable, satisfactory, controllable — the three marks inverted.
- **Bayesian blur**: an ambivalent SOHM superposition that has not yet committed; CVH collapses it (cf. collapsing a probability distribution / pinching a critical network into a definite circuit).
- **Trigger**: VSMC contractions are expected to be triggered by *local dissonance in the electromagnetic field* and to act back on neurons via ephaptic coupling, reduced blood flow, and altered local resonance.
- **Right amount ≠ zero**: a finite brain *must* compress away patterns or drown in sensory chaos; the cost is metabolic + epistemic. CVH is unskillful only when over-applied.
## GF(3) Balanced Triad
```
compressive-vasomotion (+1) ⊗ vascular-clamp (0) ⊗ latched-hyperprior (−1) = 0 (mod 3)
```
**Skill Trit**: +1 (Play / generate — the sweep *produces* a candidate collapse; cf. match-fires in the PAM RETE).
## Concomitant Skills
| Skill | Trit | Interface |
|-------|------|-----------|
| `vascular-clamp` | 0 | downstream: freezes what the sweep collapsed |
| `latched-hyperprior` | −1 | downstream: cements a sustained collapse |
| `vasocomputation` | +1 | umbrella / vascular substrate |
| `kolmogorov-compression` | +1 | compression progress as a drive (Schmidhuber) |
| `fokker-planck-analyzer` | +1 | stationary collapse of a resonance landscape |
| `information-geometry` | 0 | precision-weighting / KL of clarity vs. grab |
## Current literature (2024–2026)
- **van Veluw et al. (2020), Neuron** — spontaneous ~0.1 Hz vasomotion drives paravascular clearance; amplitude is tunable.
- **Hauglund / Nedergaard et al. (2025), Cell** — locus-coeruleus NE infraslow oscillations drive slow vasomotion → glymphatic clearance in NREM; zolpidem suppresses it.
- **Kedarasetti & Drew (2024), Neuron** — vasomotion travels as **long-wavelength waves**; resting modulation exceeds evoked. Recasts the "compression sweep" as a literal traveling wave, not a global clock.
- **Atasoy et al. (2016), Nat Commun** — connectome harmonics; with Safron's SOHMs gives the "out-of-tune harmonic → contraction" claim a formal substrate.
- **Pinotsis & Miller (2023), Prog Neurobiol** — cytoelectric coupling: endogenous fields sculpt activity (grounds the ephaptic loop; VSMC→field causation still unestablished).
- **Sharpening**: specify *which* ~0.1 Hz band (myogenic vs LC/NE vs Mayer) drives compression — the 2025 literature warns these are conflated.
- **Hook**: vasomotion phase should predict bistable-percept switching; optogenetic VSMC constriction should narrow local neural dynamic range / lower LFP entropy.
- **Grounded**: vasomotion exists + glymphatic role + ephaptic fields. **Speculative**: vasomotion as a Bayesian-collapse mechanism.
## References
- Johnson, M.E. (2023). *Principles of Vasocomputation, Part I*. opentheory.net (§V, CVH).
- Schmidhuber, J. (2008). *Driven by Compression Progress*. arXiv.
- Safron, A. (2020). *IWMT*. Frontiers in AI 3. (SOHMs as autoencoders/symmetry detectors.)
- Carhart-Harris & Friston (2019). *REBUS and the Anarchic Brain*. Pharmacol. Rev. 71(3).
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!