期刊
BRAIN IMAGING AND BEHAVIOR
卷 10, 期 4, 页码 1198-1205出版社
SPRINGER
DOI: 10.1007/s11682-015-9484-3
关键词
Brachial plexus injury; Independent component analysis; Functional network connectivity; Executive control network; Central reorganization
类别
资金
- New Cutting Edge Technology Joint Development Program of Shanghai Municipal Hospitals
Brachial plexus injury (BPI) is a type of severe peripheral nerve trauma that leads to central remodeling in the brain, as revealed by functional MRI analysis. However, previously reported remodeling is mostly restricted to sensorimotor areas of the brain. Whether this disturbance in the sensorimotor network leads to larger-scale functional remodeling remains unknown. We sought to explore the higher-level brain functional abnormality pattern of BPI patients from a large-scale network function connectivity dimension in 15 right-handed BPI patients. Resting-state functional MRI data were collected and analyzed using independent component analysis methods. Five components of interest were recognized and compared between patients and healthy subjects. Patients showed significantly altered brain local functional activities in the bilateral fronto-parietal network (FPN), sensorimotor network (SMN), and executive-control network (ECN) compared with healthy subjects. Moreover, functional connectivity between SMN and ECN were significantly less in patients compared with healthy subjects, and connectivity strength between ECN and SMN was negatively correlated with patients' residual function of the affected limb. Functional connectivity between SMN and right FPN were also significantly less than in controls, although connectivity between ECN and default mode network (DMN) was greater than in controls. These data suggested that brain functional disturbance in BPI patients extends beyond the sensorimotor network and cascades serial remodeling in the brain, which significantly correlates with residual hand function of the paralyzed limb. Furthermore, functional remodeling in these higher-level functional networks may lead to cognitive alterations in complex tasks.
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