top-down empirical priors

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

• Top-down predictive modelsconcept0.802
  Generative models in the brain that predict sensory input; proposed to be physically stored in VSMC motifs.
• Such priors suppress the inherent contextuality of the boundary.claim0.763
  Explains why the boundary appears fixed: the prior hides its context-dependent nature.
• Prior Beliefsconcept0.755
  Beliefs about states before data; used to transcribe task instructions into agent's generative model
• Prior Preferencesconcept0.751
  Target distribution over states or outcomes encoded in the generative model; goal states.
• Top-down Causationconcept0.747
  How higher organizational levels constrain and facilitate the behavior of parts by deforming their energy landscapes.
• Self-Priorframework0.746
  The key novel contribution: an internal model that learns the density of familiar multisensory experiences and drives mark-removal behavior through mismatch with the free energy principle
• Prior Preferences over Outcomesconcept0.742
  Replaces explicit reward signal in active inference; encodes agent's preferred observations independent of environment.
• top-down controlconcept0.741
  Higher levels (tissue, organ, bioelectric pattern) causally influence lower-level events; key for evolutionary and engineering interventions.