Abstract
Fear of movement is a main driver of disability and a key treatment target in chronic pain, though its neurobiological bases remain poorly understood. Here, we combine functional MRI with machine learning to identify and evaluate a brain pattern of fear of neck movement in a sample of individuals with chronic whiplashassociated disorders. During fMRI, participants were shown photographs of neck positions. The multivariate pattern, which we term the PiFoneM (Picture-Induced Fear of Neck Movement), accurately predicted selfreported fear of neck movement (n = 56; cross-validated prediction-outcome r = 0.70) and demonstrated preliminary evidence of generalizability to an independent sample with acute whiplash (n = 12; r = 0.54). The pattern was distributed across the brain, with feature importance and stability analyses highlighting regions in primary somatosensory, lateral prefrontal, and temporal cortices. PiFoneM was not predicted by head motion, was not associated with visual features of neck position photographs in a pain-free validation sample (N=32). In a randomized controlled trial, modern pain neuroscience approach (MPNA; n = 30), a fear-targeting treatment, led to reduced brain marker expression (-0.16; 95%CI: 0.30, 0.01, Cohen’s d = 0.29, p=0.038) compared to conventional physical therapy (n = 29). Exploratory analyses indicated a possible relationship between higher baseline PiFoneM expression and greater clinical improvement after MPNA. Overall, these findings provide initial evidence that fear of neck movement can be modeled from distributed patterns of brain activity and that a fear-targeted intervention may reduce expression of this pattern, supporting hypothesized treatment mechanisms.
| Original language | English |
|---|---|
| Number of pages | 11 |
| Journal | The Journal of Pain |
| Volume | 40 |
| DOIs | |
| Publication status | Published - 2026 |
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