Modeling the Action–Perception Loop and its role in Phantom Limb Pain using Active Inference
The paper develops a mathematical model of phantom limb pain within the active inference framework, which extends classical Bayesian inference by incorporating action selection alongside sensory perception. Using this model, the authors provide a conceptual account of how loss of limb control, ambiguous sensory information about limb position, residual noxious input, and pre-amputation pain could each contribute to the emergence and persistence of phantom limb pain after amputation. The authors also state that the model may help explain mechanisms underlying common interventions and variable efficacy across individuals, while acknowledging that the approach offers conceptual modeling rather than resolving disputed biological mechanisms. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.
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- last seen: 2026-05-20T01:45:00.602351+00:00