Chronic Pain HMM Parameters

Sticky transitions (pain→pain=0.8, nopain→nopain=0.7) and ambiguous emissions (both states 0.6 noxious) representing maladaptive perception

Neighborhood — ranked by edge-count

paper

framework

Chronic Pain Perception Model
implements
HMM parameterization with sticky transitions and ambiguous emissions representing maladaptive pain perception

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.

Normal Pain HMM Parametersconcept0.848
Transition (pain→pain=0.3, nopain→pain=0.2), emission (pain→noxious=0.8), initial (pain=0.223) favoring recovery
Chronic pain agent achieves M=4235.5, SD=180.3 COR in non-stationary All category (n=300), highest across all chronic resultsfinding0.736
Peak performance of chronic pain agents across all reward categories in non-stationary environment
Bayesian Model of Painframework0.731
Conceptualization of pain perception as inference over hidden nociceptive causes, from Eckert et al. 2022
The chronic pain model outperforms the normal pain model in non-stationary environments despite producing negative well-beingclaim0.726
Surprising finding that maladaptive perception can yield superior task performance in changing environments
Why does a maladaptive chronic pain perception outperform normal pain in non-stationary environments?question0.698
Empirical puzzle raised by the surprising chronic model results
Normal Pain Perception Modelframework0.685
HMM parameterization representing healthy pain perception with informative transitions and emissions
Normal Pain Model as Low-Pass Filterclaim0.680
Author's interpretation that the normal pain model smooths the happiness signal into a stable belief state providing exploration bonus
Chronic pain agent's momentary well-being recovers to zero only when visiting the food statefinding0.680
Demonstrates relief-seeking behavior pattern analogous to addiction in the chronic agent