Mapping individual cortico-basal ganglia-thalamo-cortical circuits integrating structural and functional connectome: implications for upper limb motor impairment poststroke

被引:0
作者
Xue, Xin [1 ]
Wu, Jia-Jia [1 ,2 ]
Xing, Xiang-Xin [3 ]
Ma, Jie [1 ]
Zhang, Jun-Peng [4 ]
Xiang, Yun-Ting [4 ]
Zheng, Mou-Xiong [2 ,5 ]
Hua, Xu-Yun [2 ,5 ]
Xu, Jian-Guang [1 ,2 ,4 ]
机构
[1] Shanghai Univ Tradit Chinese Med, Yueyang Hosp Integrated Tradit Chinese & Western M, Dept Rehabil Med, Shanghai, Peoples R China
[2] Minist Educ, Engn Res Ctr Tradit Chinese Med Intelligent Rehabi, Shanghai, Peoples R China
[3] Shandong Univ, Qilu Hosp, Rehabil Ctr, Jinan, Peoples R China
[4] Shanghai Univ Tradit Chinese Med, Sch Rehabil Sci, Shanghai, Peoples R China
[5] Shanghai Univ Tradit Chinese Med, Yueyang Hosp Integrated Tradit Chinese & Western M, Dept Traumatol & Orthoped, Shanghai, Peoples R China
来源
MEDCOMM | 2024年 / 5卷 / 10期
基金
中国国家自然科学基金;
关键词
cortico-basal ganglia-thalamo-cortical circuits; motor impairment; stroke; CONNECTIVITY PATTERNS; STROKE; PLASTICITY; PREDICTION; NETWORKS; RECOVERY; ATLAS; FMRI;
D O I
10.1002/mco2.764
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
This study investigated alterations in functional connectivity (FC) within cortico-basal ganglia-thalamo-cortical (CBTC) circuits and identified critical connections influencing poststroke motor recovery, offering insights into optimizing brain modulation strategies to address the limitations of traditional single-target stimulation. We delineated individual-specific parallel loops of CBTC through probabilistic tracking and voxel connectivity profiles-based segmentation and calculated FC values in poststroke patients and healthy controls, comparing with conventional atlas-based FC calculation. Support vector machine (SVM) analysis distinguished poststroke patients from controls. Connectome-based predictive modeling (CPM) used FC values within CBTC circuits to predict upper limb motor function. Poststroke patients exhibited decreased ipsilesional connectivity within the individual-specific CBTC circuits. SVM analysis achieved 82.8% accuracy, 76.6% sensitivity, and 89.1% specificity using individual-specific parallel loops. Additionally, CPM featuring positive connections/all connections significantly predicted Fugl-Meyer assessment of upper extremity scores. There were no significant differences in the group comparisons of conventional atlas-based FC values, and the FC values resulted in SVM accuracy of 75.0%, sensitivity of 67.2%, and specificity of 82.8%, with no significant CPM capability. Individual-specific parallel loops show superior predictive power for assessing upper limb motor function in poststroke patients. Precise mapping of the disease-related circuits is essential for understanding poststroke brain reorganization. We delineated individual-specific parallel cortico-basal ganglia-thalamo-cortical (CBTC) circuits through probabilistic tracking and voxel connectivity profiles-based segmentation and calculated functional connectivity (FC) values within predefined loops in poststroke patients and healthy controls, comparing with conventional atlas-based FC calculation. Support vector machine (SVM) analysis distinguished poststroke patients from controls. Connectome-based predictive modeling (CPM) used FC values within CBTC circuits to predict upper limb motor function. image
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页数:14
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