Altered cortical morphology and morphological similarity network patterns in classical trigeminal neuralgia patients

Motivation: Morphological covariance in classical trigeminal neuralgia is not well understood. Goal(s): To characterize the brain morphometry, and further construct individual-level morphological similarity networks. Approach: We performed volume and surface-based morphometry analyses respectively. Using cortical indicators combined with Kullback-Leibler divergence, we further investigated the topological properties of structural covariance network. Results: Patients presented decreased cortical indicators in salience and default mode network, along with increased volume and cortical complexity. Topological analysis revealed impaired information integration of the fractal dimension and sulcus depth networks, and the opposite trend in cortical thickness network. Gray matter covariation provides connectome evidence for central plasticity in chronic pain. Impact: The present study, for the first time, revealed the impairments of individual-level morphological covariance networks in CTN chronic pain patients, highlighting the combined effects of pain and mood disorders. Additionally, volume and surface integration analyses help to provide complementary information.