Neural encoding of pain is robust within but unstable between individuals.

The perception of pain varies both within and between individuals, even when sensory input remains constant. Understanding how the brain encodes these intra- and inter-individual variations is central to elucidating the neural mechanisms of pain and to developing reliable brain-based markers for clinical use. Yet, previous findings have been inconsistent, and their robustness across time and populations remains unclear. Here, we used electroencephalography (EEG) in 161 healthy participants to re-investigate the neural patterns explaining intra- and inter-individual variations in the perception of brief painful stimuli independent of stimulus intensity. Using Bayesian multivariate multi-model regression, we related pain ratings to canonical EEG responses. To directly assess robustness, the experiment was repeated after 4 weeks in the same participants and replicated in an independent cohort (n = 111). Neural patterns associated with inter-individual differences in pain perception were repeatable over time but not replicable across cohorts. In contrast, neural patterns underlying intra-individual fluctuations were robust both over time and across cohorts. These findings indicate that within-person and between-person variability in pain perception is encoded by distinct neural patterns that differ fundamentally in their robustness. Furthermore, they show that brain-based markers are particularly suited for tracking intra-individual fluctuations of pain, while being less sensitive to inter-individual differences. More broadly, they highlight the importance of within-person approaches for advancing both mechanistic models of pain and the development of clinically useful biomarkers.