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Brain Patterns During Single- and Dual-Task Leg Movements

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The brain is able to engage in dual tasks such as motor imagery (MI) and action observation (AO) or motor execution (ME) with action observation. In this study, we have quantitatively compared event-related desynchronization (ERD) patterns during tasks of pure MI, MI with AO (O-MI), ME, and ME with AO (O-ME) of the leg to investigate the underlying neuronal mechanisms using EEG. Subjects were instructed to imagine or perform rhythmical actions while watching a video of leg movements during O-MI and O-ME tasks; In contrast, subjects imagined and performed the leg movements without observing any video during pure MI and ME tasks. We noticed that the amplitude of ERDs from MI, O-MI, ME and O-ME sequentially increases in central regions of the brain. These quantified ERD patterns in EEG were used to study the differences of brain oscillatory changes among the four tasks. We found that ERDs in motor area were more distinct in O-MI, compared with pure MI. These results suggest that O-MI produced stronger motor activations than MI. Plus, O-ME showed significantly greater activations than ME in the beta band. O-ME has produced stronger neurophysiological effects than MI, and stronger behavioral effects than ME. These empirical results do provide convincing evidence of the dual tasks such combined MI or ME with action observation on brain pattern changes. The video of the goal-directed leg movements is most likely able to improve the ability of performing or imagining movements. O-MI and O-ME may get better and closer therapeutic effects in leg rehabilitation and motor skill training. Furthermore, the extent analysis of ERD may provide the basis for evaluating the ability of O-MI and O-ME in leg rehabilitation and motor skill training.

Keywords: Action Observation (AO); Dual Task; Event-Related Desynchronization (ERD); Leg Rehabilitation; Motor Execution (ME); Motor Imagery (MI)

Document Type: Research Article

Affiliations: 1: School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin, 300384, China 2: Department of Computer and Network Engineering, College of Information Technology, United Arab Emirates University, Al Ain, 15551, United Arab Emirates 3: Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China 4: School of Computer Science, Tianjin University of Technology, Tianjin, 300384, China 5: School of Artificial Intelligence, Xidian University, Xian, 710071, China 6: School of Computer Science and Engineering, Northeastern University, Shenyang 110189, China 7: Department of Electronics and Mechatronics, Tokyo Polytechnic University, 243-0297, Japan 8: Department of Rehabilitation, Tianjin Medical University General Hospital, Tianjin, 300052, China

Publication date: March 1, 2021

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  • Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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