Brain Network Convergence of Abnormal Gray Matter and Functional Activity of Pathological Dissociative Symptoms

AIM: Pathological dissociation is a complex clinical symptom widely observed across various psychiatric disorders. Dissociative symptoms prolong the duration of hospitalization and are associated with a poor clinical prognosis. Although several pathological models (e.g., the frontal-limbic overmodulation model and the defense cascade model) have been proposed to interpret dissociative symptoms, heterogeneous regional-level imaging findings impede our comprehension of the neural changes underlying dissociative symptoms across diagnoses. METHODS: Using the functional connectivity network mapping method, this study systematically screened 45 cross-diagnostic reports of dissociation-related structural and functional brain changes. By integrating resting-state imaging data from healthy individuals (n = 872), we constructed dissociative task-induced activation, gray matter volume (GMV), and resting-state activity impairment networks. Additionally, we performed spatial correlation analyses between the damage networks and 19 neurotransmitter distribution maps. RESULTS: The task-induced damage network showed the largest proportional overlap with the anterior salience network (SN, 12.25%), basal ganglia network (BGN, 13.57%), and dorsal default mode network (DMN, 17.74%). For the GMV damage network, the main overlap proportions were observed with the dorsal DMN (12.33%) and the anterior SN (7.67%). The resting-state activity damage network showed the greatest overlap with the anterior SN (5.17%), posterior SN (5.73%), auditory (5.47%), and sensorimotor network (4.50%). Spatial correlation analyses found associations between network changes and the distribution of N-methyl-D-aspartate receptors, vesicular acetylcholine transporter, cannabinoid receptor CB1, serotonin transporter, and mu-opioid receptor. CONCLUSION: This study further elucidated the neuroimaging changes underlying across-diagnostic dissociation and provided new insights for identifying network intervention targets to improve dissociative symptoms.