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Chen H, Hu J, Gui S, Li Q, Wang J, Yang X, Yang J. Longitudinal validation of cognitive reserve proxy measures: a cohort study in a rural Chinese community. Alzheimers Res Ther 2024; 16:87. [PMID: 38654379 PMCID: PMC11036581 DOI: 10.1186/s13195-024-01451-6] [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: 01/03/2024] [Accepted: 04/04/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND While evidence supports cognitive reserve (CR) in preserving cognitive function, longitudinal validation of CR proxies, including later-life factors, remains scarce. This study aims to validate CR's stability over time and its relation to cognitive function in rural Chinese older adults. METHODS Within the project on the health status of rural older adults (HSRO), the survey included baseline assessment (2019) and follow-up assessment (2022). 792 older adults (mean age: 70.23 years) were followed up. The confirmatory factor analysis (CFA) was constructed using cognitive reserve proxies that included years of formal education, social support, hobbies, and exercise. We examined the longitudinal validity of the CR factor using confirmatory factor analyses and measurement invariance and explored the association of CR with cognition using Spearman's correlation and Generalized Estimating Equations (GEE). RESULTS The results showed that CR's CFA structure was stable over time (T0, χ2/df: 3.21/2; RMSEA: 0.02, and T1, χ2/df: 7.47/2; RMSEA: 0.05) and that it accepted both configural and metric invariance (Δχ2/df = 2.28/3, P = 0.52). In addition, it was found that CR had a stable positive relationship with cognitive function across time (T0, r = 0.54; T1, r = 0.49). Furthermore, longitudinal CR were associated with MMSE (β = 2.25; 95%CI = 2.01 ~ 2.49). CONCLUSIONS This study provided valuable evidence on the stability and validity of cognitive reserve proxy measures in rural Chinese older adults. Our findings suggested that cognitive reserve is associated with cognitive function over time and highlighted the importance of accumulating cognitive reserve in later life.
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Affiliation(s)
- Hao Chen
- Department of Epidemiology and Health Statistics, School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Guizhou Medical University, Guiyang, China
- The Third People's Hospital of Guizhou Province, Guiyang, China
| | - Jin Hu
- Department of Epidemiology and Health Statistics, School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Guizhou Medical University, Guiyang, China
| | - Shiqi Gui
- Department of Epidemiology and Health Statistics, School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Guizhou Medical University, Guiyang, China
| | - Qiushuo Li
- Department of Epidemiology and Health Statistics, School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Guizhou Medical University, Guiyang, China
| | - Jing Wang
- Department of Epidemiology and Health Statistics, School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Guizhou Medical University, Guiyang, China
| | - Xing Yang
- School of Medicine and Health Management, Guizhou Medical University, Guiyang, China
| | - Jingyuan Yang
- Department of Epidemiology and Health Statistics, School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Guizhou Medical University, Guiyang, China.
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Devita M, Debiasi G, Anglani M, Ceolin C, Mazzonetto I, Begliomini C, Cauzzo S, Raffaelli C, Lazzarin A, Ravelli A, Bordignon A, De Rui M, Sergi G, Bertoldo A, Mapelli D, Coin A. The Role of Cognitive Reserve in Protecting Cerebellar Volumes of Older Adults with mild Cognitive Impairment. CEREBELLUM (LONDON, ENGLAND) 2024:10.1007/s12311-024-01695-w. [PMID: 38639874 DOI: 10.1007/s12311-024-01695-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/11/2024] [Indexed: 04/20/2024]
Abstract
The present study aims to investigate the relationship between cerebellar volumes and cognitive reserve in individuals with Mild Cognitive Impairment (MCI). A description of proxies of cerebellar cognitive reserve in terms of different volumes across lobules is also provided. 36 individuals with MCI underwent neuropsychological (MoCA, MMSE, Clock test, CRIq) assessment and neuroimaging acquisition with magnetic resonance imaging at 3 T. Simple linear correlations were applied between cerebellar volumes and cognitive measures. Multiple linear regression models were then used to estimate standardized regression coefficients and 95% confidence intervals. Simple linear correlations between cerebellar lobules volumes and cognitive features highlighted a significant association between CRIq_Working activity and specific motor cerebellar volumes: Left_V (ρ = 0.40, p = 0.02), Right_V (r = 0.42, p = 0.002), Vermis_VIIIb (ρ = 0.47, p = 0.003), Left_X (ρ = -0.46, p = 0.002) and Vermis_X (r = 0.35, p = 0.03). Furthermore, CRIq_Working activity scores correlated with certain cerebellar lobules implicated in cognition: Left_Crus_II, Vermis VIIb, Left_IX. MMSE was associated only with the Right_VIIB volume (r = 0.35, p = 0.02), while Clock Drawing Test scores correlated with both Left_Crus_I and Right_Crus_I (r = -0.42 and r = 0.42, p = 0.02, respectively). This study suggests that a higher cognitive reserve is associated with specific cerebellar lobule volumes and that Working activity may play a predominant role in this association. These findings contribute to the understanding of the relationship between cerebellar volumes and cognitive reserve, highlighting the potential modulatory role of Working activity on cerebellum response to cognitive decline.
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Affiliation(s)
- Maria Devita
- Department of General Psychology (DPG), University of Padua, Via Venezia 8, Padua, Italy.
- Geriatrics Unit, Department of Medicine (DIMED), University of Padua, Via Giustiniani 2, Padua, Italy.
| | - Giulia Debiasi
- Department of Surgery, Oncology and Gastroenterology, University of Padua, Via Giustiniani 2, Padua, Italy
- Department of Information Engineering, University of Padua, Via Gardenigo 6/B, Padua, Italy
| | - Mariagiulia Anglani
- Neuroradiology Unit, University Hospital of Padua, Via Giustiniani 2, Padua, Italy
| | - Chiara Ceolin
- Geriatrics Unit, Department of Medicine (DIMED), University of Padua, Via Giustiniani 2, Padua, Italy
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Aging Research Center, Stockholm, Sweden
| | - Ilaria Mazzonetto
- Department of Information Engineering, University of Padua, Via Gardenigo 6/B, Padua, Italy
| | - Chiara Begliomini
- Department of General Psychology (DPG), University of Padua, Via Venezia 8, Padua, Italy
| | - Simone Cauzzo
- Parkinson's Disease and Movement Disorders Unit, Center for Rare Neurological Diseases, Department of Neurosciences, University of Padova, Via Belzoni 160, Padua, Italy
| | - Cecilia Raffaelli
- Geriatrics Unit, Ospedale Fracastoro, Via Circonvallazione 1, San Bonifacio, Verona, Italy
| | - Alessandro Lazzarin
- Geriatrics Unit, Department of Medicine (DIMED), University of Padua, Via Giustiniani 2, Padua, Italy
| | - Adele Ravelli
- Geriatrics Unit, Department of Medicine (DIMED), University of Padua, Via Giustiniani 2, Padua, Italy
| | | | - Marina De Rui
- Geriatrics Unit, Department of Medicine (DIMED), University of Padua, Via Giustiniani 2, Padua, Italy
| | - Giuseppe Sergi
- Geriatrics Unit, Department of Medicine (DIMED), University of Padua, Via Giustiniani 2, Padua, Italy
| | - Alessandra Bertoldo
- Department of Information Engineering, University of Padua, Via Gardenigo 6/B, Padua, Italy
- Padova Neuroscience Center, University of Padua, Via Orus 2/B, Padua, Italy
| | - Daniela Mapelli
- Department of General Psychology (DPG), University of Padua, Via Venezia 8, Padua, Italy
| | - Alessandra Coin
- Geriatrics Unit, Department of Medicine (DIMED), University of Padua, Via Giustiniani 2, Padua, Italy
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Fei B, Cheng Y, Liu Y, Zhang G, Ge A, Luo J, Wu S, Wang H, Ding J, Wang X. Intelligent cholinergic white matter pathways algorithm based on U-net reflects cognitive impairment in patients with silent cerebrovascular disease. Stroke Vasc Neurol 2024:svn-2023-002976. [PMID: 38569895 DOI: 10.1136/svn-2023-002976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 03/06/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND AND OBJECTIVE The injury of the cholinergic white matter pathway underlies cognition decline in patients with silent cerebrovascular disease (SCD) with white matter hyperintensities (WMH) of vascular origin. However, the evaluation of the cholinergic white matter pathway is complex with poor consistency. We established an intelligent algorithm to evaluate WMH in the cholinergic pathway. METHODS Patients with SCD with WMH of vascular origin were enrolled. The Cholinergic Pathways Hyperintensities Scale (CHIPS) was used to measure cholinergic white matter pathway impairment. The intelligent algorithm used a deep learning model based on convolutional neural networks to achieve WMH segmentation and CHIPS scoring. The diagnostic value of the intelligent algorithm for moderate-to-severe cholinergic pathway injury was calculated. The correlation between the WMH in the cholinergic pathway and cognitive function was analysed. RESULTS A number of 464 patients with SCD were enrolled in internal training and test set. The algorithm was validated using data from an external cohort comprising 100 patients with SCD. The sensitivity, specificity and area under the curve of the intelligent algorithm to assess moderate and severe cholinergic white matter pathway injury were 91.7%, 87.3%, 0.903 (95% CI 0.861 to 0.952) and 86.5%, 81.3%, 0.868 (95% CI 0.819 to 0.921) for the internal test set and external validation set. for the. The general cognitive function, execution function and attention showed significant differences among the three groups of different CHIPS score (all p<0.05). DISCUSSION We have established the first intelligent algorithm to evaluate the cholinergic white matter pathway with good accuracy compared with the gold standard. It helps more easily assess the cognitive function in patients with SCD.
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Affiliation(s)
- Beini Fei
- Department of Neurology, Zhongshan Hospital Fudan University, Shanghai, China
| | - Yu Cheng
- Fudan University Institute of Science and Technology for Brain-inspired Intelligence, Shanghai, China
| | - Ying Liu
- Department of Neurology, Zhongshan Hospital Fudan University, Shanghai, China
| | - Guangzheng Zhang
- Department of Neurology, Zhongshan Hospital Fudan University, Shanghai, China
| | - Anyan Ge
- Department of Neurology, Zhongshan Hospital Fudan University, Shanghai, China
| | - Junyi Luo
- Fudan University Institute of Science and Technology for Brain-inspired Intelligence, Shanghai, China
| | - Shan Wu
- The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China
| | - He Wang
- Department of Neurology, Zhongshan Hospital Fudan University, Shanghai, China
- Fudan University Institute of Science and Technology for Brain-inspired Intelligence, Shanghai, China
| | - Jing Ding
- Department of Neurology, Zhongshan Hospital Fudan University, Shanghai, China
| | - Xin Wang
- Department of Neurology, Zhongshan Hospital Fudan University, Shanghai, China
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Cui L, Hong H, Wang S, Zeng Q, Jiaerken Y, Yu X, Zhang R, Zhang Y, Xie L, Lin M, Liu L, Luo X, Li K, Liu X, Li J, Huang P, Zhang M. Small vessel disease and cognitive reserve oppositely modulate global network redundancy and cognitive function: A study in middle-to-old aged community participants. Hum Brain Mapp 2024; 45:e26634. [PMID: 38553856 PMCID: PMC10980841 DOI: 10.1002/hbm.26634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 01/05/2024] [Accepted: 02/08/2024] [Indexed: 04/02/2024] Open
Abstract
Cerebral small vessel disease (SVD) can disrupt the global brain network and lead to cognitive impairment. Conversely, cognitive reserve (CR) can improve one's cognitive ability to handle damaging effects like SVD, partly by optimizing the brain network's organization. Understanding how SVD and CR collectively influence brain networks could be instrumental in preventing cognitive impairment. Recently, brain redundancy has emerged as a critical network protective metric, providing a nuanced perspective of changes in network organization. However, it remains unclear how SVD and CR affect global redundancy and subsequently cognitive function. Here, we included 121 community-dwelling participants who underwent neuropsychological assessments and a multimodal MRI examination. We visually examined common SVD imaging markers and assessed lifespan CR using the Cognitive Reserve Index Questionnaire. We quantified the global redundancy index (RI) based on the dynamic functional connectome. We then conducted multiple linear regressions to explore the specific cognitive domains related to RI and the associations of RI with SVD and CR. We also conducted mediation analyses to explore whether RI mediated the relationships between SVD, CR, and cognition. We found negative correlations of RI with the presence of microbleeds (MBs) and the SVD total score, and a positive correlation of RI with leisure activity-related CR (CRI-leisure). RI was positively correlated with memory and fully mediated the relationships between the MBs, CRI-leisure, and memory. Our study highlights the potential benefits of promoting leisure activities and keeping brain redundancy for memory preservation in older adults, especially those with SVD.
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Affiliation(s)
- Lei Cui
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Hui Hong
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Shuyue Wang
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Qingze Zeng
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Yeerfan Jiaerken
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Xinfeng Yu
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Ruiting Zhang
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Yao Zhang
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Linyun Xie
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Miao Lin
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Lingyun Liu
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Xiao Luo
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Kaicheng Li
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Xiaocao Liu
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Jixuan Li
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Peiyu Huang
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
| | - Minming Zhang
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
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Sampatakakis SN, Mourtzi N, Charisis S, Mamalaki E, Ntanasi E, Hatzimanolis A, Ramirez A, Lambert JC, Yannakoulia M, Kosmidis MH, Dardiotis E, Hadjigeorgiou G, Sakka P, Scarmeas N. Genetic Predisposition for White Matter Hyperintensities and Risk of Mild Cognitive Impairment and Alzheimer's Disease: Results from the HELIAD Study. Curr Issues Mol Biol 2024; 46:934-947. [PMID: 38275674 PMCID: PMC10814944 DOI: 10.3390/cimb46010060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 01/13/2024] [Accepted: 01/19/2024] [Indexed: 01/27/2024] Open
Abstract
The present study investigated the association of genetic predisposition for white matter hyperintensities (WMHs) with incident amnestic mild cognitive impairment (aMCI) or Alzheimer's disease (AD), as well as whether such an association was influenced by age, sex, and cognitive reserve. Overall, 537 individuals without aMCI or dementia at baseline were included. Among them, 62 individuals developed aMCI/AD at follow up. Genetic propensity to WMH was estimated using a polygenic risk score for WMHs (PRS WMH). The association of PRS WMH with aMCI/AD incidence was examined using COX models. A higher PRS WMH was associated with a 47.2% higher aMCI/AD incidence (p = 0.015) in the fully adjusted model. Subgroup analyses showed significant results in the older age group, in which individuals with a higher genetic predisposition for WMHs had a 3.4-fold higher risk for developing aMCI/AD at follow up (p < 0.001), as well as in the lower cognitive reserve (CR, proxied by education years) group, in which individuals with a higher genetic predisposition for WMHs had an over 2-fold higher risk (p = 0.013). Genetic predisposition for WMHs was associated with aMCI/AD incidence, particularly in the group of participants with a low CR. Thus, CR might be a modifier in the relationship between genetic predisposition for WMHs and incident aMCI/AD.
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Affiliation(s)
- Stefanos N. Sampatakakis
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (E.M.); (E.N.)
| | - Niki Mourtzi
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (E.M.); (E.N.)
| | - Sokratis Charisis
- Department of Neurology, UT Health San Antonio, San Antonio, TX 78229, USA;
| | - Eirini Mamalaki
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (E.M.); (E.N.)
| | - Eva Ntanasi
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (E.M.); (E.N.)
| | - Alexandros Hatzimanolis
- Department of Psychiatry, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece;
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, 50923 Cologne, Germany
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, 53127 Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE Bonn), 53127 Bonn, Germany
- Department of Psychiatry, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, TX 78229, USA
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, 50923 Cologne, Germany
| | - Jean-Charles Lambert
- Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE Facteurs de Risque et Déterminants Moléculaires des Maladies Liés au Vieillissement, University of Lille, 59000 Lille, France;
| | - Mary Yannakoulia
- Department of Nutrition and Dietetics, Harokopio University, 17676 Athens, Greece;
| | - Mary H. Kosmidis
- Lab of Neuropsychology and Behavioral Neuroscience, School of Psychology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
| | - Efthimios Dardiotis
- Department of Neurology, University Hospital of Larissa, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41334 Larissa, Greece;
| | | | - Paraskevi Sakka
- Athens Association of Alzheimer’s Disease and Related Disorders, 11636 Marousi, Greece;
| | - Nikolaos Scarmeas
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (E.M.); (E.N.)
- Department of Neurology, The Gertrude H. Sergievsky Center, Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY 10027, USA
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Wang H, Xiong X, Zhang K, Wang X, Sun C, Zhu B, Xu Y, Fan M, Tong S, Guo X, Sun L. Motor network reorganization after motor imagery training in stroke patients with moderate to severe upper limb impairment. CNS Neurosci Ther 2022; 29:619-632. [PMID: 36575865 PMCID: PMC9873524 DOI: 10.1111/cns.14065] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 11/22/2022] [Accepted: 12/06/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Motor imagery training (MIT) has been widely used to improve hemiplegic upper limb function in stroke rehabilitation. The effectiveness of MIT is associated with the functional neuroplasticity of the motor network. Currently, brain activation and connectivity changes related to the motor recovery process after MIT are not well understood. AIM We aimed to investigate the neural mechanisms of MIT in stroke rehabilitation through a longitudinal intervention study design with task-based functional magnetic resonance imaging (fMRI) analysis. METHODS We recruited 39 stroke patients with moderate to severe upper limb motor impairment and randomly assigned them to either the MIT or control groups. Patients in the MIT group received 4 weeks of MIT therapy plus conventional rehabilitation, while the control group only received conventional rehabilitation. The assessment of Fugl-Meyer Upper Limb Scale (FM-UL) and Barthel Index (BI), and fMRI scanning using a passive hand movement task were conducted on all patients before and after treatment. The changes in brain activation and functional connectivity (FC) were analyzed. Pearson's correlation analysis was conducted to evaluate the association between neural functional changes and motor improvement. RESULTS The MIT group achieved higher improvements in FM-UL and BI relative to the control group after the treatment. Passive movement of the affected hand evoked an abnormal bilateral activation pattern in both groups before intervention. A significant Group × Time interaction was found in the contralesional S1 and ipsilesional M1, showing a decrease of activation after intervention specifically in the MIT group, which was negatively correlated with the FM-UL improvement. FC analysis of the ipsilesional M1 displayed the motor network reorganization within the ipsilesional hemisphere, which correlated with the motor score changes. CONCLUSIONS MIT could help decrease the compensatory activation at both hemispheres and reshape the FC within the ipsilesional hemisphere along with functional recovery in stroke patients.
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Affiliation(s)
- Hewei Wang
- Department of Rehabilitation MedicineHuashan Hospital Fudan UniversityShanghaiChina
| | - Xin Xiong
- School of Biomedical EngineeringShanghai Jiaotong UniversityShanghaiChina
| | - Kexu Zhang
- School of Biomedical EngineeringShanghai Jiaotong UniversityShanghaiChina
| | - Xu Wang
- School of Biomedical EngineeringShanghai Jiaotong UniversityShanghaiChina
| | - Changhui Sun
- Department of Rehabilitation MedicineHuashan Hospital Fudan UniversityShanghaiChina
| | - Bing Zhu
- Department of Rehabilitation MedicineHuashan Hospital Fudan UniversityShanghaiChina
| | - Yiming Xu
- Department of Rehabilitation MedicineHuashan Hospital Fudan UniversityShanghaiChina
| | - Mingxia Fan
- Shanghai Key Laboratory of Magnetic ResonanceEast China Normal UniversityShanghaiChina
| | - Shanbao Tong
- School of Biomedical EngineeringShanghai Jiaotong UniversityShanghaiChina
| | - Xiaoli Guo
- School of Biomedical EngineeringShanghai Jiaotong UniversityShanghaiChina
| | - Limin Sun
- Department of Rehabilitation MedicineHuashan Hospital Fudan UniversityShanghaiChina
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