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Liu Z, Zhang L, Bai L, Guo Z, Gao J, Lin Y, Zhou Y, Lai J, Tao J, Chen L. Repetitive Transcranial Magnetic Stimulation and Tai Chi Chuan for Older Adults With Sleep Disorders and Mild Cognitive Impairment: A Randomized Clinical Trial. JAMA Netw Open 2025; 8:e2454307. [PMID: 39792383 DOI: 10.1001/jamanetworkopen.2024.54307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2025] Open
Abstract
Importance Sleep disorders and mild cognitive impairment (MCI) commonly coexist in older adults, increasing their risk of developing dementia. Long-term tai chi chuan has been proven to improve sleep quality in older adults. However, their adherence to extended training regimens can be challenging. Repetitive transcranial magnetic stimulation (rTMS) is a neuromodulation technique that may enhance the benefits of exercise. Objective To investigate whether 1-Hz rTMS of the right dorsolateral prefrontal cortex could enhance the clinical benefits of tai chi chuan in improving sleep quality and cognitive function among older adults with sleep disorders and MCI. Design, Setting, and Participants This 2-arm, sham-controlled, assessor-masked randomized clinical trial was conducted at a university hospital in China between October 2022 and February 2024. Adults aged 60 to 75 years with sleep disorders and MCI were eligible. Data analysis was performed from February to May 2024. Intervention Participants were randomized in a 1:1 ratio to an experimental group (tai chi chuan and 1-Hz rTMS) or a sham group (tai chi chuan and sham rTMS). Each participant received 30 sessions of personalized rTMS targeting the right dorsolateral prefrontal cortex, and the sham group underwent the same procedure. The 2 groups received 30 sessions of 60 minutes of the 24-form simplified tai chi chuan, 5 times per week for 6 weeks. Main Outcomes and Measures The primary outcomes were subjective sleep quality assessed by the Pittsburgh Sleep Quality Index (PSQI), in which scores range from 0 to 21, with lower scores indicating a healthier sleep quality, and global cognitive function assessed by the Montreal Cognitive Assessment (MoCA), in which scores range from 0 to 30, with higher scores indicating less cognitive impairment. The secondary outcomes included measures of objective sleep actigraphy, anxiety and depression scales, and other cognitive subdomains. Assessments were performed at baseline, 6 weeks after the intervention, and at the 12-week follow-up. Results A total of 110 participants (mean [SD] age, 67.9 [4.6] years; 68 female [61.8%]) were randomized to the experimental group (n = 55) and the sham group (n = 55) and included in the intention-to-treat analysis. At 6 weeks after the intervention, compared with the sham group, the experimental group showed a lower PSQI score (between-group mean difference, -3.1 [95% CI, -4.2 to -2.1]; P < .001) and a higher MoCA score (between-group mean difference, 1.4 [95% CI, 0.7-2.1]; P < .001). The per-protocol dataset analyses and 12-week follow-up showed similar results. The generalized estimated equation model revealed an interaction effect between the PSQI score (mean difference, -2.1 [95% CI, -3.1 to -0.1]; P < .001) and the MoCA total score (mean difference, 0.9 [95% CI, 0.1-1.6]; P = .01). There were 7 nonserious, unrelated adverse events (experimental group: 2; sham group: 5) with no significant difference between the 2 groups. Conclusions and Relevance In this randomized clinical trial, the findings suggest that 1-Hz rTMS enhanced the clinical benefits of tai chi chuan in improving sleep quality and cognitive function among older adults with sleep disorders and MCI, which may be related to alterations in neural plasticity. These findings provide novel data on nonpharmacologic strategies for the rehabilitation of sleep disorders and may delay or even prevent MCI. Trial Registration Chinese Clinical Trial Registry Identifier: ChiCTR2200063274.
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Affiliation(s)
- Zhizhen Liu
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Lin Zhang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Linxin Bai
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Zhenxing Guo
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Jiahui Gao
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Yongsheng Lin
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, Guangdong, China
| | - Yongjin Zhou
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, Guangdong, China
- Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, Guangdong, China
| | - Jinghui Lai
- The Affiliated Rehabilitation Hospital, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
- Fujian Key Laboratory of Cognitive Rehabilitation, Fuzhou, Fujian, China
| | - Jing Tao
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Lidian Chen
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
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Xin W, Xue T, Cheng Y, Dong F, Wang J, Ma Y, Zhang S, Zhang F, Ding J, Song D, Wang J, Zhu Y, Ju H, Yuan K, Sheng X, Yu D. Reconfigurations of dynamic functional network connectivity after 1HZ repetitive transcranial magnetic stimulation in insomnia disorder. Sleep Med 2024; 126:239-247. [PMID: 39721360 DOI: 10.1016/j.sleep.2024.12.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Revised: 12/17/2024] [Accepted: 12/17/2024] [Indexed: 12/28/2024]
Abstract
AIMS The objective of the current study was to investigate the dynamic functional connectivity among large-scale brain networks in patients with insomnia, and to assess the efficacy of repetitive transcranial magnetic stimulation (rTMS) treatment in these individuals. METHODS Resting-state functional magnetic resonance imaging (rs-fMRI) data from 62 insomnia patients and 69 healthy controls were used to compare differences in dynamic functional connectivity between the two groups. A total of 26 insomnia patients underwent rTMS for four weeks. Changes in dynamic functional network connectivity was observed in insomnia patients following treatment. Additionally, the relationship between clinical symptoms and insomnia was analyzed using topological and correlation analyses. RESULTS Our findings demonstrated that insomnia patients exhibited a significantly lower fraction rate of negative connectivity between the dorsal default mode network (dDMN) and the visual network (VN) compared to healthy controls, while showing strong positive connectivity within the VN and the auditory network (AUN). It may be attributed to the restoration of normal dynamic functional connectivity between the dDMN and VN in insomnia patients following rTMS. Furthermore, the dynamic functional connectivity between the dDMN and VN was found to predict sleep quality and treatment outcome in insomnia patients. CONCLUSION Abnormal dynamic functional network connectivity between the dDMN and VN is a hallmark of insomnia, and may serve as a biomarker to assess the effects of rTMS treatment in insomnia patients.
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Affiliation(s)
- Wuyuan Xin
- School of Digital and Intelligent Industry (School of Cyber Science and Technology), Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Ting Xue
- School of Science College, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Yongxin Cheng
- School of Digital and Intelligent Industry (School of Cyber Science and Technology), Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Fang Dong
- School of Digital and Intelligent Industry (School of Cyber Science and Technology), Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Juan Wang
- School of Digital and Intelligent Industry (School of Cyber Science and Technology), Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Yuxin Ma
- School of Digital and Intelligent Industry (School of Cyber Science and Technology), Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Shan Zhang
- Life Sciences Research Center, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China
| | - Fan Zhang
- School of Digital and Intelligent Industry (School of Cyber Science and Technology), Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Jingjing Ding
- School of Automation and Electrical Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Daining Song
- School of Digital and Intelligent Industry (School of Cyber Science and Technology), Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Junxuan Wang
- School of Digital and Intelligent Industry (School of Cyber Science and Technology), Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Yifei Zhu
- Department of Psychosomatic Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050061, China
| | - Haitao Ju
- The Affiliated Hospital of Inner Mongolia Medical University, Huhehaote, Inner Mongolia, 010030, China
| | - Kai Yuan
- School of Digital and Intelligent Industry (School of Cyber Science and Technology), Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China; Life Sciences Research Center, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China; School of Automation and Electrical Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China; Hainan Free Trade Port Health Medical Research Institute, Baoting, Hainan, 572300, China.
| | - Xiaona Sheng
- Department of Psychosomatic Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050061, China.
| | - Dahua Yu
- School of Automation and Electrical Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China.
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Yu L, Peng W, Lin W, Luo Y, Hu D, Zhao G, Xu H, Dou Z, Zhang Q, Hong X, Yu S. Electroencephalography connectome changes in chronic insomnia disorder are correlated with neurochemical signatures. Sleep 2024; 47:zsae080. [PMID: 38520362 DOI: 10.1093/sleep/zsae080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 03/12/2024] [Indexed: 03/25/2024] Open
Abstract
STUDY OBJECTIVES This study aimed to investigate the alterations in resting-state electroencephalography (EEG) global brain connectivity (GBC) in patients with chronic insomnia disorder (CID) and to explore the correlation between macroscale connectomic variances and microscale neurotransmitter distributions. METHODS We acquired 64-channel EEG from 35 female CID patients and 34 healthy females. EEG signals were source-localized using individual brain anatomy and orthogonalized to mitigate volume conduction. Correlation coefficients between band-limited source-space power envelopes of the DK 68 atlas were computed and averaged across regions to determine specific GBC values. A support vector machine (SVM) classifier utilizing GBC features was employed to differentiate CID patients from controls. We further used Neurosynth and a 3D atlas of neurotransmitter receptors/transporters to assess the cognitive functions and neurotransmitter landscape associated with CID cortical abnormality maps, respectively. RESULTS CID patients exhibited elevated GBC within the medial prefrontal cortex and limbic cortex, particularly at the gamma carrier frequency, compared to controls (pFDR < .05). GBC patterns were found to effectively distinguish CID patients from controls with a precision of 90.8% in the SVM model. The cortical abnormality maps were significantly correlated with meta-analytic terms like "cognitive control" and "emotion regulation." Notably, GBC patterns were associated with neurotransmitter profiles (pspin < .05), with neurotransmitter systems such as norepinephrine, dopamine, and serotonin making significant contributions. CONCLUSIONS This work characterizes the EEG connectomic profile of CID, facilitating the cost-effective clinical translation of EEG-derived markers. Additionally, the linkage between GBC patterns and neurotransmitter distribution offers promising avenues for developing targeted treatment strategies for CID.
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Affiliation(s)
- Liyong Yu
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Wei Peng
- Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Wenting Lin
- School of Rehabilitation and Health Preservation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yucai Luo
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Daijie Hu
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Guangli Zhao
- School of Rehabilitation and Health Preservation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Hao Xu
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zeyang Dou
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Qi Zhang
- Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Xiaojuan Hong
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Siyi Yu
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
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Subramaniyan M, Reifman J. Can electroencephalography reveal network connectivity alterations in insomnia disorder? Sleep 2024; 47:zsae111. [PMID: 38746993 DOI: 10.1093/sleep/zsae111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2024] Open
Affiliation(s)
- Manivannan Subramaniyan
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Jaques Reifman
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD, USA
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Shen C, Wang ZD, Qian WJ, Wu CF, Qian SR, Tang T. Bibliometric Analysis of Brain Stimulation Technologies in Sleep Disorders. Med Sci Monit 2024; 30:e942687. [PMID: 38439525 PMCID: PMC10924428 DOI: 10.12659/msm.942687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 12/17/2023] [Indexed: 03/06/2024] Open
Abstract
BACKGROUND Sleep disorders are a common disease faced by people today and can lead to fatigue, lack of concentration, impaired memory, and even death. In recent years, the development of brain stimulation techniques has provided a new perspective for the treatment of sleep disorders. However, there is a lack of bibliometric analyses related to sleep disorders and brain stimulation techniques. Therefore, this study analyzed the application status and trend of brain stimulation technology in sleep disorder research. MATERIAL AND METHODS Articles and reviews published between 1999 and 2023 were retrieved from the Web of Science. CiteSpace was used to visually analyze the publications, countries, institutions, journals, authors, references, and keywords. RESULTS A total of 459 publications were obtained. The number of studies was shown to be on a general upward trend. The country with the largest number of publications was the United States; UDICE-French Research Universities had the highest number of publications; Neurology had the highest citation frequency; 90% of the top 10 references cited were from Journal Citation Reports Q1; Brigo was the author with the highest number of publications; and the most frequent keywords were "transcranial magnetic stimulation", "deep brain stimulation", and "Parkinson disease". CONCLUSIONS Our study used CiteSpace software to analyze 459 studies published since 1999 on brain stimulation techniques for the treatment of sleep disorders, revealing research trends and the current state of the field. Our results will help researchers to understand the existing research quickly and provide direction for future research.
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Lu L, Liao L, Zheng J, Lin W, Wang T, Wen X. Protocol for a randomized controlled trial exploring the brain mechanism and therapeutic effect of electroacupuncture on cognitive function and sleep quality in chronic insomnia. BMC Complement Med Ther 2023; 23:401. [PMID: 37940916 PMCID: PMC10631103 DOI: 10.1186/s12906-023-04242-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 10/31/2023] [Indexed: 11/10/2023] Open
Abstract
BACKGROUND Insomnia is a prevalent sleep disorder that affects up to 15% of the population worldwide and is the second most common mental health issue. There is increasing interest in the effects of long-term insomnia on cognitive function. Electroacupuncture can effectively improve cognitive function and sleep quality, yet the underlying brain network mechanisms remain unclear. This study aims to explore the network regulatory mechanisms associated with enhanced cognitive function and sleep quality, providing theoretical support for the use of electroacupuncture in the clinical treatment of chronic insomnia. METHODS This study is divided into two parts. Sixteen individuals with chronic insomnia and 16 healthy controls of similar age and gender will be recruited in Study 1 to examine the brain network topology of individuals with chronic insomnia. Study 2 will be a randomized controlled trial with 120 chronic insomnia patients divided into three groups: Group A (electroacupuncture plus placebo drug), Group B (drug plus placebo electroacupuncture), and Group C (placebo electroacupuncture plus placebo drug). Participants will be exposed to 24 treatments over an 8-week period (3 times per week) and monitored for 12 additional weeks. The primary outcome measure will be changes in brainwave data from before to after the treatment. In addition, the Wisconsin Card Sorting Test and the Pittsburgh Sleep Quality Index will be utilized as secondary outcomes to measure from before to after treatment and during the follow-up. A correlation analysis will be conducted to explore links among modifications in brainwave patterns, Wisconsin Card Sorting Test scores, and Pittsburgh Sleep Quality Index scores. Additionally, any adverse events will be strictly monitored. DISCUSSION Electroacupuncture may represent an alternative treatment for chronic insomnia, and this trial is expected to reveal the brain mechanism by which electroacupuncture improves cognitive function and sleep quality in chronic insomnia patients. TRIAL REGISTRATION ChiCTR2200060150 (Chinese Clinical Trial Registry, http://www.chictr.org.cn , registered on 20 May 2022).
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Affiliation(s)
- Linhao Lu
- School of Health Science, Guangdong Pharmaceutical University, Guangzhou, 51000, China
- Guangdong Provincial Engineering and Technology Research Center of Light and Health, Guangzhou, 51000, China
| | - Lizhen Liao
- School of Health Science, Guangdong Pharmaceutical University, Guangzhou, 51000, China
| | - Jiaorong Zheng
- School of Health Science, Guangdong Pharmaceutical University, Guangzhou, 51000, China
| | - Weiyi Lin
- School of Health Science, Guangdong Pharmaceutical University, Guangzhou, 51000, China
- Guangdong Provincial Engineering and Technology Research Center of Light and Health, Guangzhou, 51000, China
| | - TaiShun Wang
- School of Health Science, Guangdong Pharmaceutical University, Guangzhou, 51000, China
- Guangdong Provincial Engineering and Technology Research Center of Light and Health, Guangzhou, 51000, China
| | - Xiuyun Wen
- School of Health Science, Guangdong Pharmaceutical University, Guangzhou, 51000, China.
- Guangdong Provincial Engineering and Technology Research Center of Light and Health, Guangzhou, 51000, China.
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