concept
active
concept:vasocomputation

Vasocomputation

Unifying framework proposing that Buddhist tanha operates through vascular smooth muscle cells as the brain's compression/prediction infrastructure.

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Papers (1)

paper

Frameworks (3)

framework
  • Active Inference
    extendsimplements
    Foundational framework by Karl Friston; the paper extends it to three hierarchical levels for modeling meta-awareness.
  • Adam Safron's theory positing Self-Organized Harmonic Modes as neural building blocks.
  • Michael Johnson's prior work on how neural networks (and brains) can be 'annealed' to find optimal states.

Communities (1)

community

Artifacts (1)

artifact

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

  • Mike Johnson's 2023 framework unifying Buddhist phenomenology, Active Inference, and physical reflex; introduces tanha as mental motion.
  • Vasomotion reflexconcept0.730
    The rhythmic contraction and relaxation of vascular smooth muscle; proposed to function as a compression sweep on neural resonances.
  • Vasomotion reflex functions as compression sweep collapsing neural ambivalence into definite states; vasomotion motifs are reflexive reactions to uncertainty.
  • Polycomputationconcept0.722
    Biological architecture where multiple competing/cooperating multi-scale agents develop interpretations of molecular and biophysical states rather than committing to single interpretation.
  • Vascular clampconcept0.719
    Contraction of VSMCs that freezes local neural patterns and plasticity for the duration of contraction, functioning as medium-term memory.
  • Procedure extracting concept vectors as difference of mean activations between concept-exemplifying and baseline/negative sentences
  • Attribute-aligned shifts added to the residual stream to steer LLM generation toward desired personality traits
  • Longstanding tradition the paper situates itself within, treating computational complexity as manifesting via physical dynamical phenomena.