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Updated: Jun 17, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
A causal effect study of cortical morphology and related covariate networks in classical trigeminal neuralgia
Pengfei Zhang1,2,3,4, Xinyue Wan5, Jingqi Jiang2,3,4
1Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu, Sichuan 610041, China.
Abstract:
Structural covariance networks and causal effects within can provide critical information on gray matter reorganization and disease-related hierarchical changes. Based on the T1WI data of 43 classical trigeminal neuralgia patients and 45 controls, we constructed morphological similarity networks of cortical thickness, sulcal depth, fractal dimension, and gyrification index. Moreover, causal structural covariance network analyses were conducted in regions with morphological abnormalities or altered nodal properties, respectively. We found that patients showed reduced sulcal depth, gyrification index, and fractal dimension, especially in the salience network and the default mode network. Additionally, the integration of the fractal dimension and sulcal depth networks was significantly reduced, accompanied by decreased nodal efficiency of the bilateral temporal poles, and right pericalcarine cortex within the sulcal depth network. Negative causal effects existed from the left insula to the right caudal anterior cingulate cortex in the gyrification index map, also from bilateral temporal poles to right pericalcarine cortex within the sulcal depth network. Collectively, patients exhibited impaired integrity of the covariance networks in addition to the abnormal gray matter morphology in the salience network and default mode network. Furthermore, the patients may experience progressive impairment in the salience network and from the limbic system to the sensory system in network topology, respectively.

