Background: Clinically, chronic pain and depression often coexist in multiple diseases and reciprocally reinforce each other, which greatly escalates the difficulty of treatment. The alteration in neural networks underlying the chronic pain/depression comorbidity remains unclear.
Methods: Spared nerve injury (SNI) was performed to establish a rat model of comorbidity of chronic pain and depression. Multimodal fMRI was utilized to acquire neuroimaging data of the rat brain, with BOLD and DTI data used to analyze adaptive changes in brain regions and networks associated with comorbidity.
Results: By integrating static and dynamic ALFF analyses with DTI parameters, six key brain regions (OFR_L, CA1_L, CA3_L, PL_L, Stri_L, and Stri_R) were identified. These regions showed significant associations with both pain-related and depressive-like behaviors and formed a comorbidity-related network centered on the prefrontal cortex, hippocampus, striatum, and primary sensory cortex. Further analyses indicated that the relationship between fMRI features and depressive-like behavior was largely mediated by pain-related processes.
Conclusions: This study reveals network-level neural alterations underlying chronic pain-depression comorbidity and supports a pain-mediated pathway linking brain activity to affective disturbances. These findings provide new insights into the neural mechanisms of this comorbidity and highlight the importance of integrated pain-depression interactions.
Keywords: Amplitude of low-frequency fluctuation; Brain activity; Chronic pain; Comorbidity; Depression; Dynamic functional connectivity; Neural network.