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Updated: Jun 23, 2025

Investigating Pain-Related Avoidance Behavior using a Robotic Arm-Reaching Paradigm
Published on: October 3, 2020
The fear-avoidance model as an embodied prediction of threat
Clovis Varangot-Reille1, Giovanni Pezzulo2, Mick Thacker3
1MSc Statistics and Computer Science for Data Science, University Lumière Lyon 2, Bron, France. cvarangotreille@gmail.com.
Abstract:
The fear-avoidance model is a well-established framework in the understanding of persistent pain. It proposes a dichotomous path: either the context is interpreted as safe; there is no fear reaction and, therefore, the individual engages in active (positive) coping; or the context is interpreted as threatening, leading to a self-reinforcing vicious circle of fear and (negative) avoidance. We propose an embodied interpretation of this phenomenon employing the joint framework of predictive coding and active inference. The key idea is that multisensory integration of exteroceptive, proprioceptive, and interoceptive sensory inputs can lead to dysfunctional experiences of threat in nonthreatening situations. Threat inference can promote fear responses, maladaptive strategies (i.e., avoidance) and self-provides evidence for threat in associated or future contexts, or both. Under this treatment, the prediction of nonrealized threat becomes self-evidencing and context-invariant, and hence self-perpetuating. Safety cues are unable to attenuate the interpretation of the negative context as the dominant inference of the context is threatful and gains more precision and becomes resistant over time. Our model provides an explanation for the emergence of a dysfunctional fear response in the clinical setting despite apparent safety based on modern concepts from theoretical (computational) neuroscience.
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