vascular-clamp

name	vascular-clamp
description	Vascular Clamp Hypothesis (VCH) — vascular contraction freezes local neural patterns and plasticity for its duration, storing a specific active-inference prediction as vascular tension = medium-term memory. Use when modeling predictions-as-tension, the FEP-AI top-down model store, or the witness/hold step of vasocomputation.
license	MIT
metadata	{"trit":0,"source":"https://opentheory.net/2023/07/principles-of-vasocomputation-a-unification-of-buddhist-phenomenology-active-inference-and-physical-reflex-part-i/"}

vascular-clamp

The Vascular Clamp Hypothesis (VCH) (Johnson 2023): a vascular contraction freezes local neural patterns and plasticity for the duration of the contraction — like collapsing a superposition, clamping a harmonic system, or pinching a critical network into a definite circuit. Specific vascular constrictions correspond to specific predictions in the Active Inference framework and function as medium-term memory. This is the 0 / witness leg of the vasocomputation timescale triad: the clamp that holds what was collapsed.

Use When

• Modeling an active-inference prediction stored as a held vascular constriction (the missing FEP-AI top-down store)
• Representing medium-term memory as sustained tension rather than synaptic change
• Bridging "to-do list as predictions" (untrue observations held until acted upon) to a somatic accumulator
• The witness/hold phase between the fast CVH sweep and the durable LHH latch

Core Concepts

• Prediction = constriction: each held prediction is a specific vascular tension; the pattern of constrictions is the top-down model.
• Freeze, don't rewrite: VCH suspends plasticity locally — the underlying SOHM ground-truth perception is preserved (not corrupted), giving near-infinite capacity for hypotheticals without damaging perception. One system perceives; one clamps/judges/plans.
• Three discharge routes: tension is released by action, consolidated by neural annealing, or rendered superfluous by remodeling (held long enough → becomes default → see neural-potentiation).
• Witness, not commitment: a clamp is reversible and energy-costly to maintain; only a sustained clamp engages the latch (→ latched-hyperprior).

GF(3) Balanced Triad

compressive-vasomotion (+1) ⊗ vascular-clamp (0) ⊗ latched-hyperprior (−1) = 0 (mod 3)

Skill Trit: 0 (Witness — the held clamp is the witnessed obligation; cf. EnsureJustification returning a still-open relation).

Concomitant Skills

Skill	Trit	Interface
compressive-vasomotion	+1	upstream: the sweep that this freezes
latched-hyperprior	−1	downstream: sustained clamp → latch
vasocomputation	+1	umbrella / vascular substrate
active-inference-robotics	0	predictions-as-operators on a world model
reafference-corollary-discharge	0	held prediction discharged by action
able-markets	0	obligation held until resolved (clearing)

Current literature (2024–2026)

• Hai & Murphy (1988); Hudson et al. (2022, PNAS) — smooth-muscle latch state: dephosphorylated, non-cycling cross-bridges hold tension at near-zero ATP, longer in tonic (vascular) muscle. The skill's strongest physical anchor.
• Hartmann et al. (2021, Nat Neurosci; 2022, Annu Rev Physiol) — capillary pericytes set basal tone and modulate flow slowly (s–min): kinetics matching "medium-term" storage. Relocate the clamp to pericytes / precapillary sphincters, not fast arterioles.
• Sirotin & Das (2009, Nature) — anticipatory arterial dilation entrained to expectation, in darkness, not predicted by local activity: haemodynamics already carry prediction, not just metabolic demand.
• Kim et al. (2016, J Neurosci) — vasculo-neuronal coupling: increased tone decreases pyramidal firing — the missing return arc by which held tension biases computation.
• Stokes (2015); Masse et al. (2019) — "activity-silent" working memory: information held in non-spiking states (precedent for a non-firing substrate).
• Hook: two-photon pericyte-Ca²⁺/diameter imaging during a delay task should show content-specific sustained micro-constriction; optogenetic pericyte relaxation should degrade medium-term retention.
• Grounded: latch economy, pericyte tone, vasculo-neuronal coupling, anticipatory flow. Speculative: a single constriction freezing a decodable prediction.

References

• Johnson, M.E. (2023). Principles of Vasocomputation, Part I. opentheory.net (§V, VCH).
• Friston, K. et al. (2017). Active Inference: A Process Theory. Neural Computation 29(1).
• Juliani, Safron, Kanai (2023). Deep CANALs: SOHMs + vascular tension = inference landscape.