Validating a measure of the precision of ascending noxious signals

Pain perception can be described as a process of Bayesian inference, which generates sensory estimates based on prior expectations and afferent information. The inference is inherently affected by the precision (inverse variance) of the distribution of centrally-predicted ascending noxious signals. In this study, we examined the measurement validity of Bayesian likelihood precision in pain perception. Using a 2x2 fully factorial within-subject design, we measured and compared the precision of the distribution of centrally-predicted noxious stimuli in four tasks administered to 57 healthy adults: the cued-pain task (CPT) and the Focused Analgesia Test (FAST), in two noxious modalities, thermal and electrical. A hierarchical Bayesian model was applied to the CPT, and the FAST was employed as a validation criterion, given that it is known to correlate with clinical pain reports and the placebo response. We found that individuals with a more precise representation of ascending sensory signals in the cued-pain task produced less variable pain reports in the FAST. We validated the result by replicating this correlation across thermal and electrical pain. These results support the validity of our approach to the measurement of precision of ascending noxious signals. Their correlation with FAST scores supports their criterion validity and their correlation across noxious sub-modalities support the concurrent validity of this measurement. In the future, the precision of noxious inputs could be used to quantify individual placebo susceptibility, and thereby optimise the assay sensitivity of randomised clinical trials of new pain medication.