How control modulates pain

Currently, the umbrella term 'control' in the context of studies on pain subsumes very different entities. We offer a more systematic taxonomy of studies to better understand the role of control in the context of pain.Control over pain can be integrated into a Bayesian pain model via modulation of expectations. We suggest that changes in mean values and precision are mechanisms through which control modulates pain perception.Controllability is often confounded with predictability, attentional effects, and motor behavior, and thus experimental design is crucial. We argue for better-controlled neuroscientific studies.Control over pain affects neurocognitive mechanisms reflected in changes in activity in the anterior insula, middle frontal gyrus, anterior cingulate cortex, and sensory cortices. Pain, an indicator of potential tissue damage, ideally falls under individual control. Although previous work shows a trend towards reduced pain in contexts where pain is controllable, there is a large variability across studies that is probably related to different aspects of control. We therefore outline a taxonomy of different aspects of control relevant to pain, sketch how control over pain can be integrated into a Bayesian pain model, and suggest changes in expectations and their precision as potential mechanisms. We also highlight confounding cognitive factors, particularly predictability, that emphasize the necessity for careful experimental designs. Finally, we describe the neurobiological underpinnings of how control affects pain processing in studies using different types of control, and highlight the roles of the anterior insula, middle frontal gyrus (MFG), and anterior cingulate cortex (ACC). Pain, an indicator of potential tissue damage, ideally falls under individual control. Although previous work shows a trend towards reduced pain in contexts where pain is controllable, there is a large variability across studies that is probably related to different aspects of control. We therefore outline a taxonomy of different aspects of control relevant to pain, sketch how control over pain can be integrated into a Bayesian pain model, and suggest changes in expectations and their precision as potential mechanisms. We also highlight confounding cognitive factors, particularly predictability, that emphasize the necessity for careful experimental designs. Finally, we describe the neurobiological underpinnings of how control affects pain processing in studies using di