Mangui Lin
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Mangui Lin has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Guoen Cai
Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, Fuzhou, China
1 shared publication - Guofa Cai
School of Information Engineering, Guangdong University of Technology, Guangzhou, China
1 shared publication - Rifeng Jiang
Department of Radiology, Fujian Medical University Union Hospital, Fuzhou 350001, China
1 shared publication - Yang Song
MR Research Collaboration Team, Siemens Healthineers Ltd., Shanghai, China
1 shared publication - Yifang Sun
Department of Radiology, Fujian Medical University Union Hospital, Fuzhou 350001, China
1 shared publication - YongJie Li
College of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China
1 shared publication
Latest Publications
- Open Access
- 1 January 2023
- Published by MDPI AG in Brain Sciences
- Vol. 13 (1) , 81
Association between Beta Oscillations from Subthalamic Nucleus and Quantitative Susceptibility Mapping in Deep Gray Matter Structures in Parkinson’s Disease
This study aimed to investigate the association between beta oscillations and brain iron deposition. Beta oscillations were filtered from the microelectrode recordings of local field potentials (LFP) in the subthalamic nucleus (STN), and the ratio of the power spectral density of beta oscillations (PSDXb) to that of the LFP signals was calculated. Iron deposition in the deep gray matter (DGM) structures was indirectly assessed using quantitative susceptibility mapping (QSM). The Unified Parkinson’s Disease Rating Scale (UPDRS), part III, was used to assess the severity of symptoms. Spearman correlation coefficients were applied to assess the associations of PSDXb with QSM values in the DGM structures and the severity of symptoms. PSDXb showed a significant positive correlation with the average QSM values in DGM structures, including caudate and substantia nigra (SN) (p = 0.008 and 0.044). Similarly, the PSDXb showed significant negative correlations with the severity of symptoms, including axial symptoms and the gait in the medicine-off state (p = 0.006 for both). The abnormal iron metabolism in the SN and striatum pathways may be one of the underlying mechanisms for the occurrence of abnormal beta oscillations in the STN, and beta oscillations may serve as important pathophysiological biomarkers of PD.
- 1 January 2023
- Published by MDPI AG in Brain Sciences
- Vol. 13 (1) , 81
Open AccessAssociation between Beta Oscillations from Subthalamic Nucleus and Quantitative Susceptibility Mapping in Deep Gray Matter Structures in Parkinson’s Disease
This study aimed to investigate the association between beta oscillations and brain iron deposition. Beta oscillations were filtered from the microelectrode recordings of local field potentials (LFP) in the subthalamic nucleus (STN), and the ratio of the power spectral density of beta oscillations (PSDXb) to that of the LFP signals was calculated. Iron deposition in the deep gray matter (DGM) structures was indirectly assessed using quantitative susceptibility mapping (QSM). The Unified Parkinson’s Disease Rating Scale (UPDRS), part III, was used to assess the severity of symptoms. Spearman correlation coefficients were applied to assess the associations of PSDXb with QSM values in the DGM structures and the severity of symptoms. PSDXb showed a significant positive correlation with the average QSM values in DGM structures, including caudate and substantia nigra (SN) (p = 0.008 and 0.044). Similarly, the PSDXb showed significant negative correlations with the severity of symptoms, including axial symptoms and the gait in the medicine-off state (p = 0.006 for both). The abnormal iron metabolism in the SN and striatum pathways may be one of the underlying mechanisms for the occurrence of abnormal beta oscillations in the STN, and beta oscillations may serve as important pathophysiological biomarkers of PD.