Literature DB >> 35492507

Brain Connectivity Changes During Bimanual and Rotated Motor Imagery.

Jung-Tai King1, Alka Rachel John2, Yu-Kai Wang2, Chun-Kai Shih1, Dingguo Zhang3, Kuan-Chih Huang1,4, Chin-Teng Lin1,2.   

Abstract

Motor imagery-based brain-computer interface (MI-BCI) currently represents a new trend in rehabilitation. However, individual differences in the responsive frequency bands and a poor understanding of the communication between the ipsilesional motor areas and other regions limit the use of MI-BCI therapy. Objective: Bimanual training has recently attracted attention as it achieves better outcomes as compared to repetitive one-handed training. This study compared the effects of three MI tasks with different visual feedback.
Methods: Fourteen healthy subjects performed single hand motor imagery tasks while watching single static hand (traditional MI), single hand with rotation movement (rmMI), and bimanual coordination with a hand pedal exerciser (bcMI). Functional connectivity is estimated by Transfer Entropy (TE) analysis for brain information flow.
Results: Brain connectivity of conducting three MI tasks showed that the bcMI demonstrated increased communications from the parietal to the bilateral prefrontal areas and increased contralateral connections between motor-related zones and spatial processing regions. Discussion/
Conclusion: The results revealed bimanual coordination operation events increased spatial information and motor planning under the motor imagery task. And the proposed bimanual coordination MI-BCI (bcMI-BCI) can also achieve the effect of traditional motor imagery tasks and promotes more effective connections with different brain regions to better integrate motor-cortex functions for aiding the development of more effective MI-BCI therapy. Clinical and Translational Impact Statement The proposed bcMI-BCI provides more effective connections with different brain areas and integrates motor-cortex functions to promote motor imagery rehabilitation for patients' impairment.

Entities:  

Keywords:  Bimanual coordination; brain connectivity; motor imagery

Mesh:

Year:  2022        PMID: 35492507      PMCID: PMC9041539          DOI: 10.1109/JTEHM.2022.3167552

Source DB:  PubMed          Journal:  IEEE J Transl Eng Health Med        ISSN: 2168-2372


  56 in total

1.  Feature extraction for on-line EEG classification using principal components and linear discriminants.

Authors:  K Lugger; D Flotzinger; A Schlögl; M Pregenzer; G Pfurtscheller
Journal:  Med Biol Eng Comput       Date:  1998-05       Impact factor: 2.602

2.  Blind separation of auditory event-related brain responses into independent components.

Authors:  S Makeig; T P Jung; A J Bell; D Ghahremani; T J Sejnowski
Journal:  Proc Natl Acad Sci U S A       Date:  1997-09-30       Impact factor: 11.205

3.  Correlation-based channel selection and regularized feature optimization for MI-based BCI.

Authors:  Jing Jin; Yangyang Miao; Ian Daly; Cili Zuo; Dewen Hu; Andrzej Cichocki
Journal:  Neural Netw       Date:  2019-07-15

4.  A novel deep learning approach for classification of EEG motor imagery signals.

Authors:  Yousef Rezaei Tabar; Ugur Halici
Journal:  J Neural Eng       Date:  2016-11-30       Impact factor: 5.379

5.  Effect of Virtual Reality-based Bilateral Upper Extremity Training on Upper Extremity Function after Stroke: A Randomized Controlled Clinical Trial.

Authors:  Suhyun Lee; Yumi Kim; Byoung-Hee Lee
Journal:  Occup Ther Int       Date:  2016-07-15       Impact factor: 1.448

6.  Transfer entropy--a model-free measure of effective connectivity for the neurosciences.

Authors:  Raul Vicente; Michael Wibral; Michael Lindner; Gordon Pipa
Journal:  J Comput Neurosci       Date:  2010-08-13       Impact factor: 1.621

7.  Bilateral and unilateral arm training improve motor function through differing neuroplastic mechanisms: a single-blinded randomized controlled trial.

Authors:  Jill Whitall; Sandy McCombe Waller; John D Sorkin; Larry W Forrester; Richard F Macko; Daniel F Hanley; Andrew P Goldberg; Andreas Luft
Journal:  Neurorehabil Neural Repair       Date:  2010-10-07       Impact factor: 3.919

8.  Coupled bilateral movements and active neuromuscular stimulation: intralimb transfer evidence during bimanual aiming.

Authors:  James H Cauraugh; Sang Bum Kim; Aaron Duley
Journal:  Neurosci Lett       Date:  2005-03-17       Impact factor: 3.046

9.  Z-score linear discriminant analysis for EEG based brain-computer interfaces.

Authors:  Rui Zhang; Peng Xu; Lanjin Guo; Yangsong Zhang; Peiyang Li; Dezhong Yao
Journal:  PLoS One       Date:  2013-09-13       Impact factor: 3.240

10.  Post-stroke Rehabilitation Training with a Motor-Imagery-Based Brain-Computer Interface (BCI)-Controlled Hand Exoskeleton: A Randomized Controlled Multicenter Trial.

Authors:  Alexander A Frolov; Olesya Mokienko; Roman Lyukmanov; Elena Biryukova; Sergey Kotov; Lydia Turbina; Georgy Nadareyshvily; Yulia Bushkova
Journal:  Front Neurosci       Date:  2017-07-20       Impact factor: 4.677

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