A causal effect study of cortical morphology and related covariate networks in classical trigeminal neuralgia patients

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.

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Publication Details

Journal
Cerebral Cortex
Published
2024-08-01
DOI
https://doi.org/10.1093/cercor/bhae337
Citations
1
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.40

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article

A causal effect study of cortical morphology and related covariate networks in classical trigeminal neuralgia patients

Guangyao Liu, Kai Ai, Jingqi Jiang, Pengfei Zhang et al.
1 citations
Cerebral Cortex
Advanced Neuroimaging Techniques and Applications
0.40
article

A causal effect study of cortical morphology and related covariate networks in classical trigeminal neuralgia patients

Guangyao Liu, Kai Ai, Jingqi Jiang, Pengfei Zhang, Jing Zhang, Xin-Ding Zhang, Yang Liu, Danyang Wang, Xinyue Wan
article en
1 citations

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.

Cerebral CortexVol. 34(8)
Sichuan University (CN), Fudan University (CN), Philips (China) (CN), West China Hospital of Sichuan University (CN), Lanzhou University Second Hospital (CN), Huashan Hospital (CN), Lanzhou University (CN)
National Natural Science Foundation of China, Science and Technology Program of Gansu Province
Openalex Percentile: Top 36%
Advanced Neuroimaging Techniques and Applications
0.40
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