Short-Term Variability Reveals Early Neural Mechanisms of Pain Chronification

Short-term fluctuations in perceived pain are often dismissed as noise. However, evidence from diverse neural systems indicates that moment-to-moment variability reflects fundamental network properties such as stability and flexibility, and in pain, reduced short-term variability has been previously linked to chronic pain conditions. Here, we tested the hypothesis that alterations in such variability mark an early mechanistic transition from subacute to chronic pain. Using a longitudinal dataset of 120 individuals with subacute back pain, followed over one year, we analysed continuous real-time pain ratings alongside fMRI activity during spontaneous pain. We show that patients who develop persistent pain exhibit a marked decrease in moment-to-moment variability by the end of the year, in contrast to recovering individuals whose variability increases over time. Neural activity associated with these fluctuations at pain onset--within thalamo-cortico-limbic and modulatory circuits, including the thalamus, amygdala, dorsomedial and orbitofrontal prefrontal cortices, anterior insula, and sensorimotor regions--successfully predicted clinical outcomes after one year. Gradient boosting classifiers trained on onset data robustly separated recovering and persistent individuals (mean ROC AUC over folds > .8). These findings suggest early loss of dynamical flexibility within pain-regulatory networks as a mechanistic hallmark of pain chronification and suggest short-term variability as a simple, interpretable, and clinically accessible risk marker for chronic pain.