Motor imagery (MI) and action observation (AO) have traditionally been viewed as two separate techniques, which can both be used alongside physical practice to enhance motor learning and rehabilitation. Their independent use has largely been shown to be effective, and there is clear evidence that the two processes can elicit similar activity in the motor system. Building on these well-established findings, research has now turned to investigate the effects of their combined use. In this article, we first review the available neurophysiological and behavioral evidence for the effects of combined action observation and motor imagery (AO+MI) on motor processes. We next describe a conceptual framework for their combined use, and then discuss several areas for future research into AO+MI processes. In this review, we advocate a more integrated approach to AO+MI techniques than has previously been adopted by movement scientists and practitioners alike. We hope that this early review of an emergent body of research, along with a related set of research questions, can inspire new work in this area. We are optimistic that future research will further confirm if, how, and when this combined approach to AO+MI can be more effective in motor learning and rehabilitation settings, relative to the more traditional application of MI or AO independently.
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http://dx.doi.org/10.3389/fnins.2016.00514 | DOI Listing |
Ann Phys Rehabil Med
January 2025
Healthy Brain & Mind Research Centre (HBM), School of Behavioural and Health Sciences, Australian Catholic University, 115 Victoria Parade, Fitzroy, VIC, 3065 Australia.
Background: Inaccurate perception of one's physical abilities is potentially related to age-related declines in motor planning and can lead to changes in walking. Motor imagery training is effective at improving balance and walking in older adults, but most research has been conducted on older adults following surgery or in those with a history of falls. Deficits in motor imagery ability are associated with reduced executive function in older adults with cognitive impairment.
View Article and Find Full Text PDFClin Rehabil
January 2025
School of Nursing, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Objective: To map evidence on the characteristics, effectiveness, and potential mechanisms of motor imagery interventions targeting cognitive function and depression in adults with neurological disorders and/or mobility impairments.
Data Sources: Six English databases (The Cochrane Library, PubMed, Embase, Scopus, Web of Sciences, and PsycINFO), two Chinese databases (CNKI and WanFang), and a gray literature database were searched from inception to December 2024.
Review Methods: This scoping review followed the Joanna Briggs Institute Scoping Review methodology.
Comput Methods Programs Biomed
January 2025
College of Medical Instruments, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, PR China; Shanghai Yangpu Mental Health Center, Shanghai, 200093, PR China. Electronic address:
Background And Objective: The hybrid brain computer interfaces (BCI) combining electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) have attracted extensive attention for overcoming the decoding limitations of the single-modality BCI. With the deepening application of deep learning approaches in BCI systems, its significant performance improvement has become apparent. However, the scarcity of brain signal data limits the performance of deep learning models.
View Article and Find Full Text PDFJ Neurol
January 2025
Western Institute of Neuroscience, Western University, London, Canada.
Background: Repeat neurological assessment is standard in cases of severe acute brain injury. However, conventional measures rely on overt behavior. Unfortunately, behavioral responses may be difficult or impossible for some patients.
View Article and Find Full Text PDFJ Neural Eng
January 2025
Department of Biomedical Engineering, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, AUSTRALIA.
Multiple Sclerosis (MS) is a heterogeneous autoimmune-mediated disorder affecting the central nervous system, commonly manifesting as fatigue and progressive limb impairment. This can significantly impact quality of life due to weakness or paralysis in the upper and lower limbs. A Brain-Computer Interface (BCI) aims to restore quality of life through control of an external device, such as a wheelchair.
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