The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Motor imagery and action observation: cognitive tools for rehabilitation
Open accessAbstract
Rehabilitation, for a large part may be seen as a learning process where old skills have to be re-acquired and new ones have to be learned on the basis of practice. Active exercising creates a flow of sensory (afferent) information. It is known that motor recovery and motor learning have many aspects in common. Both are largely based on response-produced sensory information. In the present article it is asked whether active physical exercise is always necessary for creating this sensory flow. Numerous studies have indicated that motor imagery may result in the same plastic changes in the motor system as actual physical practice. Motor imagery is the mental execution of a movement without any overt movement or without any peripheral (muscle) activation. It has been shown that motor imagery leads to the activation of the same brain areas as actual movement. The present article discusses the role that motor imagery may play in neurological rehabilitation. Furthermore, it will be discussed to what extent the observation of a movement performed by another subject may play a similar role in learning. It is concluded that, although the clinical evidence is still meager, the use of motor imagery in neurological rehabilitation may be defended on theoretical grounds and on the basis of the results of experimental studies with healthy subjects.
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Cites
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Cited by
Schuster, C., Hilfiker, R., Amft, O., Scheidhauer, A., Andrews, B., Butler, J., Kischka, U., & Ettlin, T. (2011) · BMC Medicine · doi:10.1186/1741-7015-9-75 · Cited by 450
An end-to-end deep learning approach to MI-EEG signal classification for BCIs
Dose, H., Møller, J. S., Iversen, H. K., & Puthusserypady, S. (2018) · Expert Systems with Applications · doi:10.1016/j.eswa.2018.08.031 · Cited by 382
Action observation treatment: a novel tool in neurorehabilitation
Buccino, G. (2014) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2013.0185 · Cited by 367
Neural Decoding of EEG Signals with Machine Learning: A Systematic Review
Saeidi, M., Karwowski, W., Farahani, F. V., Fiok, K., Taiar, R., Hancock, P. A., & Al-Juaid, A. (2021) · Brain Sciences · doi:10.3390/brainsci11111525 · Cited by 258
Task‐oriented training in rehabilitation after stroke: systematic review
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Metadata
- Authors
- Mulder, T.
- Venue
- Journal of Neural Transmission
- Published
- 2007-06-20
- Volume
- 114
- Issue
- 10
- Pages
- 1265-1278
- ISSN
- 0300-9564 (ISSN-L)
- 1435-1463
- OpenAlex
- W2051652848
- Cited by
- 650
- References
- 17
- FWCI
- 10.81
- Type
- journal article
- Language
- en
- Open access
- hybrid
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