Differential patterns of brain connectivity alterations in patients with back pain chronification versus recovery: A...

Functional magnetic resonance imaging studies have demonstrated that back pain, particularly chronic back pain, is associated with altered functional brain connectivity, especially in regions involved in the modulation of pain and emotion regulation. Our study investigated dysconnectivity patterns in subacute back pain patients to distinguish those who develop chronic back pain from those who recover. This work utilized a publicly available longitudinal resting-state functional magnetic resonance imaging dataset from the OpenPain database, including clinical assessments collected across multiple sessions, and recorded pain scores. The dataset consists of 46 subacute back pain patients and 27 healthy controls. Based on longitudinal pain scores, patients were classified into recovery and chronic back pain groups. In contrast to prior analyses of the OpenPain dataset, which primarily relied on specific brain region's connectivity or predictive modeling, this study applies a voxel-wise dysconnectivity count framework combined with data-driven clustering to identify spatially precise, whole-brain signatures of abnormal functional connectivity. This approach enables detection of anatomically specific dysconnectivity patterns at a resolution not achieved in previous work. Our findings therefore extend the OpenPain literature by providing a fine-grained, network-wide characterization of early connectivity disturbances that distinguish recovery from back pain chronification. The results showed that the chronic back pain group exhibited greater dysconnectivity in regions linked to emotion regulation, pain processing, and attentional control. In contrast, the recovery group displayed connectivity deviations in sensorimotor, visual, and cognitive control regions. PERSPECTIVE: Baseline whole-brain dysconnectivity patterns differ between patients who recover and those who develop chronic pain. These findings highlight distributed network alterations associated with pain trajectories and provide insight into neural mechanisms underlying pain chronification.