Literature DB >> 33875691

Task-related brain functional network reconfigurations relate to motor recovery in chronic subcortical stroke.

Hsiao-Ju Cheng1,2, Kwun Kei Ng1, Xing Qian1, Fang Ji1, Zhong Kang Lu3, Wei Peng Teo4, Xin Hong5, Fatima Ali Nasrallah5,6, Kai Keng Ang3,7, Kai-Hsiang Chuang5,6, Cuntai Guan7, Haoyong Yu2, Effie Chew8,9, Juan Helen Zhou10,11,12,13.   

Abstract

Stroke leads to both regional brain functional disruptions and network reorganization. However, how brain functional networks reconfigure as task demand increases in stroke patients and whether such reorganization at baseline would facilitate post-stroke motor recovery are largely unknown. To address this gap, brain functional connectivity (FC) were examined at rest and motor tasks in eighteen chronic subcortical stroke patients and eleven age-matched healthy controls. Stroke patients underwent a 2-week intervention using a motor imagery-assisted brain computer interface-based (MI-BCI) training with or without transcranial direct current stimulation (tDCS). Motor recovery was determined by calculating the changes of the upper extremity component of the Fugl-Meyer Assessment (FMA) score between pre- and post-intervention divided by the pre-intervention FMA score. The results suggested that as task demand increased (i.e., from resting to passive unaffected hand gripping and to active affected hand gripping), patients showed greater FC disruptions in cognitive networks including the default and dorsal attention networks. Compared to controls, patients had lower task-related spatial similarity in the somatomotor-subcortical, default-somatomotor, salience/ventral attention-subcortical and subcortical-subcortical connections, suggesting greater inefficiency in motor execution. Importantly, higher baseline network-specific FC strength (e.g., dorsal attention and somatomotor) and more efficient brain network reconfigurations (e.g., somatomotor and subcortical) from rest to active affected hand gripping at baseline were related to better future motor recovery. Our findings underscore the importance of studying functional network reorganization during task-free and task conditions for motor recovery prediction in stroke.

Entities:  

Year:  2021        PMID: 33875691     DOI: 10.1038/s41598-021-87789-5

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  50 in total

Review 1.  Modulation of interhemispheric activation balance in motor-related areas of stroke patients with motor recovery: Systematic review and meta-analysis of fMRI studies.

Authors:  Qing Tang; Guangming Li; Tao Liu; Anguo Wang; Shenggang Feng; Xiang Liao; Yu Jin; Zhiwei Guo; Bin He; Morgan A McClure; Guoqiang Xing; Qiwen Mu
Journal:  Neurosci Biobehav Rev       Date:  2015-09-05       Impact factor: 8.989

Review 2.  Movement-dependent stroke recovery: a systematic review and meta-analysis of TMS and fMRI evidence.

Authors:  Lorie G Richards; Kim C Stewart; Michelle L Woodbury; Claudia Senesac; James H Cauraugh
Journal:  Neuropsychologia       Date:  2007-08-24       Impact factor: 3.139

3.  Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke.

Authors:  Joshua Sarfaty Siegel; Lenny E Ramsey; Abraham Z Snyder; Nicholas V Metcalf; Ravi V Chacko; Kilian Weinberger; Antonello Baldassarre; Carl D Hacker; Gordon L Shulman; Maurizio Corbetta
Journal:  Proc Natl Acad Sci U S A       Date:  2016-07-11       Impact factor: 11.205

4.  Upper limb recovery after stroke is associated with ipsilesional primary motor cortical activity: a meta-analysis.

Authors:  Isabelle Favre; Thomas A Zeffiro; Olivier Detante; Alexandre Krainik; Marc Hommel; Assia Jaillard
Journal:  Stroke       Date:  2014-02-13       Impact factor: 7.914

5.  Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.

Authors:  B Biswal; F Z Yetkin; V M Haughton; J S Hyde
Journal:  Magn Reson Med       Date:  1995-10       Impact factor: 4.668

6.  Alteration and Role of Interhemispheric and Intrahemispheric Connectivity in Motor Network After Stroke.

Authors:  Jungsoo Lee; Eunhee Park; Ahee Lee; Won Hyuk Chang; Dae-Shik Kim; Yun-Hee Kim
Journal:  Brain Topogr       Date:  2018-04-18       Impact factor: 3.020

7.  Measuring functional connectivity in stroke: Approaches and considerations.

Authors:  Joshua S Siegel; Gordon L Shulman; Maurizio Corbetta
Journal:  J Cereb Blood Flow Metab       Date:  2017-05-25       Impact factor: 6.200

Review 8.  Resting-State Functional MRI: Everything That Nonexperts Have Always Wanted to Know.

Authors:  H Lv; Z Wang; E Tong; L M Williams; G Zaharchuk; M Zeineh; A N Goldstein-Piekarski; T M Ball; C Liao; M Wintermark
Journal:  AJNR Am J Neuroradiol       Date:  2018-01-18       Impact factor: 3.825

9.  Disrupted functional network integrity and flexibility after stroke: Relation to motor impairments.

Authors:  Sara Larivière; Nick S Ward; Marie-Hélène Boudrias
Journal:  Neuroimage Clin       Date:  2018-06-09       Impact factor: 4.881

10.  Resting-state functional connectivity and its association with multiple domains of upper-extremity function in chronic stroke.

Authors:  M A Urbin; Xin Hong; Catherine E Lang; Alex R Carter
Journal:  Neurorehabil Neural Repair       Date:  2014-02-18       Impact factor: 4.895

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  3 in total

1.  Influence of Transcranial Direct Current Stimulation Dosage and Associated Therapy on Motor Recovery Post-stroke: A Systematic Review and Meta-Analysis.

Authors:  Alan-Michael D Chow; Jeonghwa Shin; Hongwu Wang; Jeremy Mikhail Kellawan; Hugo M Pereira
Journal:  Front Aging Neurosci       Date:  2022-03-18       Impact factor: 5.750

2.  Alteration of brain functional networks induced by electroacupuncture stimulation in rats with ischemia-reperfusion: An independent component analysis.

Authors:  Si-Si Li; Xiang-Xin Xing; Xu-Yun Hua; Yu-Wen Zhang; Jia-Jia Wu; Chun-Lei Shan; Mou-Xiong Zheng; He Wang; Jian-Guang Xu
Journal:  Front Neurosci       Date:  2022-08-03       Impact factor: 5.152

3.  Brain Functional Changes in Stroke Following Rehabilitation Using Brain-Computer Interface-Assisted Motor Imagery With and Without tDCS: A Pilot Study.

Authors:  Mengjiao Hu; Hsiao-Ju Cheng; Fang Ji; Joanna Su Xian Chong; Zhongkang Lu; Weimin Huang; Kai Keng Ang; Kok Soon Phua; Kai-Hsiang Chuang; Xudong Jiang; Effie Chew; Cuntai Guan; Juan Helen Zhou
Journal:  Front Hum Neurosci       Date:  2021-07-16       Impact factor: 3.169

  3 in total

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