Withdrawal latency in a human hot plate analog tracks inter-individual differences in pain sensitivity

Authors

Keuter, L., Goltermann, O., Jessberger, J., Asan, L., Büchel, C.

Abstract

Pain research relies mainly on self-report in humans and nocifensive behavior in animals. This asymmetry limits cross-species translation and neglects movement as integral to human pain responses. We therefore developed a human analog of the rodent hot plate test and tested whether temporal and kinematic features of nocifensive withdrawal can capture inter-individual differences in pain sensitivity. Ninety-one healthy participants rested their forearm on a thermode that rapidly heated to and held a fixed noxious temperature (46 {degrees}C or 48 {degrees}C) and were instructed to withdraw once the percept reached their pain threshold or tolerance. From wrist accelerometry, we extracted withdrawal latency and peak acceleration, an index of withdrawal vigor, and related both to pain intensity ratings from a separate, temperature-matched task and to calibrated pain sensitivity. Participants withdrew earlier and with higher peak acceleration at 48 {degrees}C than at 46 {degrees}C. Crucially, withdrawal latency tracked inter-individual differences in pain sensitivity: Participants who withdrew earlier reported higher pain in the separate task (48 {degrees}C: r = -.47 and -.50) and showed lower pain thresholds and higher suprathreshold sensitivity during calibration. In contrast, withdrawal vigor showed no such relationship, despite high reliability. Withdrawal latency can thus serve as a behavioral readout of inter-individual differences in pain sensitivity, whereas vigor might reflect intra-individual motor scaling with stimulus intensity. By separating the decision to withdraw from its motor execution, this paradigm offers a behavioral complement to traditional self-report and provides a translational link between human and preclinical pain assays.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 23 Oct 2026.

Stats

1-terrible, 9-excellent. How would you rate this preprint? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.