Literature DB >> 32685998

Identifying Resting-State Functional Connectivity Changes in the Motor Cortex Using fNIRS During Recovery from Stroke.

K M Arun1, K A Smitha1, P N Sylaja2, Chandrasekharan Kesavadas3.   

Abstract

Resting-state functional imaging has been used to study the functional reorganization of the brain. The application of functional near-infrared spectroscopy (fNIRS) to assess resting-state functional connectivity (rsFC) has already been demonstrated in recent years. The present study aimed to identify the difference in rsFC patterns during the recovery from the upper-limb deficit due to stroke. Twenty patients with mild stroke having an onset of four to eight weeks were recruited from the stroke clinic of our institute and an equal number of healthy volunteers were included in the study after ethical committee approval. The fNIRS signals were recorded bilaterally over the premotor area and supplementary motor area and over the primary motor cortex. Pearson Correlation is the method used to compute rsFC for the healthy group and patient group. For the healthy group, both intra-hemispheric and inter-hemispheric connections were stronger. RSFC analysis demonstrated changes from the healthy pattern for the patient group with an upper-limb deficit. The left hemisphere affected group showed disrupted ipsilesional and an increased contra-lesional connectivity. The longitudinal data analysis of rsFC showed improvement in the connections in the ipsilesional hemisphere between the primary motor area, somatosensory area, and premotor areas. In the future, the rsFC changes during the recovery could be used to predict the extent of recovery from stroke motor deficits.

Entities:  

Keywords:  Functional near-infrared spectroscopy; Resting-state functional connectivity; Stroke; Upper-limb deficit

Mesh:

Year:  2020        PMID: 32685998     DOI: 10.1007/s10548-020-00785-2

Source DB:  PubMed          Journal:  Brain Topogr        ISSN: 0896-0267            Impact factor:   3.020


  10 in total

1.  Task-State Cortical Motor Network Characteristics by Functional Near-Infrared Spectroscopy in Subacute Stroke Show Hemispheric Dominance.

Authors:  Ziwen Yuan; Weiwei Xu; Jiameng Bao; Hui Gao; Wen Li; Yu Peng; Lisha Wang; Ye Zhao; Siming Song; Jin Qiao; Gang Wang
Journal:  Front Aging Neurosci       Date:  2022-06-24       Impact factor: 5.702

2.  Time-Varying Effective Connectivity for Describing the Dynamic Brain Networks of Post-stroke Rehabilitation.

Authors:  Fangzhou Xu; Yuandong Wang; Han Li; Xin Yu; Chongfeng Wang; Ming Liu; Lin Jiang; Chao Feng; Jianfei Li; Dezheng Wang; Zhiguo Yan; Yang Zhang; Jiancai Leng
Journal:  Front Aging Neurosci       Date:  2022-05-24       Impact factor: 5.702

3.  Amplitude of fNIRS Resting-State Global Signal Is Related to EEG Vigilance Measures: A Simultaneous fNIRS and EEG Study.

Authors:  Yuxuan Chen; Julia Tang; Yafen Chen; Jesse Farrand; Melissa A Craft; Barbara W Carlson; Han Yuan
Journal:  Front Neurosci       Date:  2020-12-03       Impact factor: 4.677

4.  Independent contributions of structural and functional connectivity: Evidence from a stroke model.

Authors:  Lynsey M Keator; Grigori Yourganov; Alexandra Basilakos; Argye E Hillis; Gregory Hickok; Leonardo Bonilha; Christopher Rorden; Julius Fridriksson
Journal:  Netw Neurosci       Date:  2021-11-30

5.  Brain-Computer Interface-Robot Training Enhances Upper Extremity Performance and Changes the Cortical Activation in Stroke Patients: A Functional Near-Infrared Spectroscopy Study.

Authors:  Lingyu Liu; Minxia Jin; Linguo Zhang; Qiuzhen Zhang; Dunrong Hu; Lingjing Jin; Zhiyu Nie
Journal:  Front Neurosci       Date:  2022-04-08       Impact factor: 5.152

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Authors:  Yuqing Wang; Zhiqiang Yang; Hongfei Ji; Jie Li; Lingyu Liu; Jie Zhuang
Journal:  Front Psychol       Date:  2022-04-07

7.  Effectiveness of Tai Chi Yunshou motor imagery training for hemiplegic upper extremity motor function in poststroke patients: study protocol for a randomized clinical trial.

Authors:  Lin Hong Jiang; Li Juan Zhao; Yang Liu; Hong Zhang; Si Cong Zhang; Wei Qin Cong; Rui Qi
Journal:  Trials       Date:  2022-04-21       Impact factor: 2.728

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Authors:  Stefano Tortora; Gloria Beraldo; Francesco Bettella; Emanuela Formaggio; Maria Rubega; Alessandra Del Felice; Stefano Masiero; Ruggero Carli; Nicola Petrone; Emanuele Menegatti; Luca Tonin
Journal:  J Neuroeng Rehabil       Date:  2022-07-05       Impact factor: 5.208

9.  Exploring the ability of stroke survivors in using the contralesional hemisphere to control a brain-computer interface.

Authors:  Salem Mansour; Joshua Giles; Kai Keng Ang; Krishnan P S Nair; Kok Soon Phua; Mahnaz Arvaneh
Journal:  Sci Rep       Date:  2022-09-28       Impact factor: 4.996

10.  The disrupted topological properties of structural networks showed recovery in ischemic stroke patients: a longitudinal design study.

Authors:  Yongxin Li; Zeyun Yu; Ping Wu; Jiaxu Chen
Journal:  BMC Neurosci       Date:  2021-08-02       Impact factor: 3.288

  10 in total

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