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      Motor network reorganization after motor imagery training in stroke patients with moderate to severe upper limb impairment

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          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.

          Abstract

          The neural mechanism of motor imagery training in stroke patients with moderate to severe upper limb motor impairments was investigated using task‐based fMRI. The results revealed that motor imagery training during motor recovery decreased overaction at both hemispheres and reorganized the motor network within the ipsilesional hemisphere.

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          Most cited references70

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          Parallel organization of functionally segregated circuits linking basal ganglia and cortex.

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            Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks.

            Resting state functional connectivity reveals intrinsic, spontaneous networks that elucidate the functional architecture of the human brain. However, valid statistical analysis used to identify such networks must address sources of noise in order to avoid possible confounds such as spurious correlations based on non-neuronal sources. We have developed a functional connectivity toolbox Conn ( www.nitrc.org/projects/conn ) that implements the component-based noise correction method (CompCor) strategy for physiological and other noise source reduction, additional removal of movement, and temporal covariates, temporal filtering and windowing of the residual blood oxygen level-dependent (BOLD) contrast signal, first-level estimation of multiple standard functional connectivity magnetic resonance imaging (fcMRI) measures, and second-level random-effect analysis for resting state as well as task-related data. Compared to methods that rely on global signal regression, the CompCor noise reduction method allows for interpretation of anticorrelations as there is no regression of the global signal. The toolbox implements fcMRI measures, such as estimation of seed-to-voxel and region of interest (ROI)-to-ROI functional correlations, as well as semipartial correlation and bivariate/multivariate regression analysis for multiple ROI sources, graph theoretical analysis, and novel voxel-to-voxel analysis of functional connectivity. We describe the methods implemented in the Conn toolbox for the analysis of fcMRI data, together with examples of use and interscan reliability estimates of all the implemented fcMRI measures. The results indicate that the CompCor method increases the sensitivity and selectivity of fcMRI analysis, and show a high degree of interscan reliability for many fcMRI measures.
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              Guidelines for Adult Stroke Rehabilitation and Recovery: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association

              The aim of this guideline is to provide a synopsis of best clinical practices in the rehabilitative care of adults recovering from stroke.
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                Author and article information

                Contributors
                meagle@sjtu.edu.cn
                tracy611@sina.com
                Journal
                CNS Neurosci Ther
                CNS Neurosci Ther
                10.1111/(ISSN)1755-5949
                CNS
                CNS Neuroscience & Therapeutics
                John Wiley and Sons Inc. (Hoboken )
                1755-5930
                1755-5949
                27 December 2022
                February 2023
                : 29
                : 2 ( doiID: 10.1002/cns.v29.2 )
                : 619-632
                Affiliations
                [ 1 ] Department of Rehabilitation Medicine Huashan Hospital Fudan University Shanghai China
                [ 2 ] School of Biomedical Engineering Shanghai Jiaotong University Shanghai China
                [ 3 ] Shanghai Key Laboratory of Magnetic Resonance East China Normal University Shanghai China
                Author notes
                [*] [* ] Correspondence

                Limin Sun, Department of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China.

                Email: tracy611@ 123456sina.com

                Xiaoli Guo, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.

                Email: meagle@ 123456sjtu.edu.cn

                Author information
                https://orcid.org/0000-0001-7632-0607
                https://orcid.org/0000-0002-6346-1846
                Article
                CNS14065 CNSNT-2022-717.R1
                10.1111/cns.14065
                9873524
                36575865
                d2c4253f-9168-4c4e-a190-0c1f0fa73591
                © 2022 The Authors. CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 22 November 2022
                : 12 September 2022
                : 06 December 2022
                Page count
                Figures: 7, Tables: 1, Pages: 14, Words: 8418
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 81974356
                Award ID: 61771313
                Award ID: 82102665
                Funded by: National Key R&D Program of China , doi 10.13039/501100012166;
                Award ID: 2020YFC2004200
                Funded by: Shanghai Sailing Program
                Award ID: 21YF1404600
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                February 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.3 mode:remove_FC converted:24.01.2023

                Neurosciences
                functional connectivity,motor imagery training,stroke rehabilitation,task‐based fmri,upper limb function

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