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Leng J, Yu X, Wang C, Zhao J, Zhu J, Chen X, Zhu Z, Jiang X, Zhao J, Feng C, Yang Q, Li J, Jiang L, Xu F, Zhang Y. Functional connectivity of EEG motor rhythms after spinal cord injury. Cogn Neurodyn 2024; 18:3015-3029. [PMID: 39555294 PMCID: PMC11564577 DOI: 10.1007/s11571-024-10136-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 02/22/2024] [Accepted: 03/22/2024] [Indexed: 11/19/2024] Open
Abstract
Spinal cord injury (SCI), which is the injury of the spinal cord site resulting in motor dysfunction, has prompted the use of motor imagery (MI)-based brain computer interface (BCI) systems for motor function reconstruction. However, analyzing electroencephalogram signals and brain function mechanisms for SCI patients is challenging. This is due to their low signal-to-noise ratio and high variability. We propose using the phase locking value (PLV) to construct the brain network in α and β rhythms for both SCI patients and healthy individuals. This approach aims to analyze the changes in brain network connectivity and brain function mechanisms following SCI. The results show that the connection strength of the α rhythm in the healthy control (HC) group is stronger than that in the SCI group, and the connection strength in the β rhythm of the SCI group is stronger than that in the HC group. Moreover, we extract the PLV with common spatial pattern (PLV-CSP) feature from the MI data of the SCI group. The experimental results for 12 SCI patients include that the peak classification accuracy is 100%, and the average accuracy of the ten-fold cross-verification is 95.6%. Our proposed approach can be used as a potential valuable method for SCI pathological studies and MI-based BCI rehabilitation systems.
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Affiliation(s)
- Jiancai Leng
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Xin Yu
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Chongfeng Wang
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Jinzhao Zhao
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Jianqun Zhu
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Xinyi Chen
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Zhaoxin Zhu
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Xiuquan Jiang
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Jiaqi Zhao
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Chao Feng
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Qingbo Yang
- School of Mathematics and Statistics, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Jianfei Li
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Lin Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No.2006, Xiyuan Road West Hi-Tech District, Chengdu, 611731 Sichuan China
- School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, No.2006, Xiyuan Road West Hi-Tech District, Chengdu, 611731 Sichuan China
| | - Fangzhou Xu
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China
| | - Yang Zhang
- Rehabilitation and Physical Therapy Department, Shandong University of Traditional Chinese Medicine Affiliated Hospital, No.42, Wenhuaxi Road Lixia District, Jinan, 250012 Shandong China
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Tommas NM, Ferguson M. Suspected Mal de Debarquement Syndrome: A Case Report Highlighting the Difficulty in Diagnosis and Management. Mil Med 2024; 189:e2280-e2283. [PMID: 38330077 DOI: 10.1093/milmed/usae014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 12/12/2023] [Accepted: 01/15/2024] [Indexed: 02/10/2024] Open
Abstract
MdDS is syndrome of oscillating vertigo following cessation of passive motion. The pathogenesis of this disorder is not well understood, but functional imaging studies suggest cortical connectivity dysfunction in feedback loops of the vestibulo-ocular system and visuo-spatial system. Patients go through multiple appointments and often specialist referrals before being diagnosed. After diagnosis, optimal management is difficult. Several treatment modalities, including medication, vestibular rehabilitation, and neuromodulation, have had variable success in management. We present the case of a young, female active duty Air Force Captain who developed symptoms while deployed. She underwent multiple treatments with variable success. Her clinical course highlights the difficulties for patients and providers posed by suspected MdDS.
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Affiliation(s)
- Nathan M Tommas
- Transitional Year Residency Program, San Antonio Uniformed Services Health Education Consortium, Fort Sam Houston, TX 78234, USA
| | - Meagan Ferguson
- Family Medicine Department, CPT Jennifer Moreno Clinic, Fort Sam Houston, TX 78234, USA
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Chen Y, Tang JH, De Stefano LA, Wenger MJ, Ding L, Craft MA, Carlson BW, Yuan H. Electrophysiological resting state brain network and episodic memory in healthy aging adults. Neuroimage 2022; 253:118926. [PMID: 35066158 DOI: 10.1016/j.neuroimage.2022.118926] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/16/2021] [Accepted: 01/19/2022] [Indexed: 01/06/2023] Open
Abstract
Recent studies have emphasized the changes in large-scale brain networks related to healthy aging, with the ultimate purpose to aid in differentiating normal neurocognitive aging from neurodegenerative disorders that also arise with age. Emerging evidence from functional Magnetic Resonance Imaging (fMRI) indicates that connectivity patterns within specific brain networks, especially the Default Mode Network (DMN), distinguish those with Alzheimer's disease from healthy individuals. In addition, disruptive alterations in the large-scale brain systems that support high-level cognition are shown to accompany cognitive decline at the behavioral level, which is commonly observed in the aging populations, even in the absence of disease. Although fMRI is useful for assessing functional changes in brain networks, its high costs and limited accessibility discourage studies that need large populations. In this study, we investigated the aging-effect on large-scale networks of the human brain using high-density electroencephalography and electrophysiological source imaging, which is a less costly and more accessible alternative to fMRI. In particular, our study examined a group of healthy subjects in the age range from middle- to older-aged adults, which is an under-studied range in the literature. Employing a high-resolution computation model, our results revealed age associations in the connectivity pattern of DMN in a consistent manner with previous fMRI findings. Particularly, in combination with a standard battery of cognitive tests, our data showed that in the posterior cingulate / precuneus area of DMN higher brain connectivity was associated with lower performance on an episodic memory task. The findings demonstrate the feasibility of using electrophysiological imaging to characterize large-scale brain networks and suggest that changes in network connectivity are associated with normal aging.
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Affiliation(s)
- Yuxuan Chen
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, United States
| | - Julia H Tang
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
| | - Lisa A De Stefano
- Department of Psychology, University of Oklahoma, Norman, OK, United States; Graduate Program in Cellular and Behavioral Neurobiology, University of Oklahoma, Norman, OK, United States
| | - Michael J Wenger
- Department of Psychology, University of Oklahoma, Norman, OK, United States; Graduate Program in Cellular and Behavioral Neurobiology, University of Oklahoma, Norman, OK, United States
| | - Lei Ding
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States; Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, OK, United States
| | - Melissa A Craft
- Fran and Earl Ziegler College of Nursing, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Barbara W Carlson
- Fran and Earl Ziegler College of Nursing, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Han Yuan
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States; Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, OK, United States.
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