Introduction: Numerous treatments suggest that brain plasticity changes after peripheral nerve injury (PNI), and most studies examining functional magnetic resonance imaging focused on abnormal changes in specific brain regions. However, it is the large-scale interaction of neuronal networks instead of isolated brain regions contributed to the functional recovery after PNI. In the present study, we examined the intra- and internetworks alterations between the related functional resting-state networks (RSNs) in a sciatic nerve injury rat model.
Methods: Ninety-six female rats were divided into a control and model group. Unilateral sciatic nerve transection and direct anastomosis were performed in the latter group. We used an independent component analysis (ICA) algorithm to observe the changes in RSNs and assessed functional connectivity between different networks using the functional networks connectivity (FNC) toolbox.
Results: Six RSNs related to PNI were identified, including the basal ganglia network (BGN), sensorimotor network (SMN), salience network (SN), interoceptive network (IN), cerebellar network (CN), and default mode network (DMN). The model group showed significant changes in whole-brain FC changes within these resting-state networks (RSNs), but four of these RSNs exhibited a conspicuous decrease. The interalterations performed that significantly decreased FNC existed between the BGN and SMN, BGN and IN, and BGN and DMN (p < .05, corrected). A significant increase in FNC existed between DMN and CN and between CN and SN (p < .05, corrected).
Conclusion: The results showed the large-scale functional reorganization at the network level after PNI. This evidence reveals new implications to the pathophysiological mechanisms in brain plasticity of PNI.
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http://dx.doi.org/10.1002/brb3.1747 | DOI Listing |
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Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130.
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Institute of Neurology, Anhui University of Chinese Medicine, No. 357 Changjiang Middle Road, Luyang District, Hefei 230061, China.
Brain functional networks are associated with parkinsonism in observational studies. However, the causal effects between brain functional networks and parkinsonism remain unclear. We aimed to assess the potential bidirectional causal associations between 191 brain resting-state functional magnetic resonance imaging (rsfMRI) phenotypes and parkinsonism including Parkinson's disease (PD) and drug-induced parkinsonism (DIP).
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