Computational neurorehabilitation: modeling plasticity and learning to predict recovery

Reinkensmeyer DJ, Burdet E, Casadio M, Krakauer JW, Kwakkel G, Lang CE, Swinnen SP, Ward NS, Schweighofer N (2016)
Journal of NeuroEngineering and Rehabilitation 13(1).

Download
No fulltext has been uploaded. References only!
Journal Article | Published | English

No fulltext has been uploaded

Author
; ; ; ; ; ; ; ;
Department
Publishing Year
ISSN
PUB-ID

Cite this

Reinkensmeyer DJ, Burdet E, Casadio M, et al. Computational neurorehabilitation: modeling plasticity and learning to predict recovery. Journal of NeuroEngineering and Rehabilitation. 2016;13(1).
Reinkensmeyer, D. J., Burdet, E., Casadio, M., Krakauer, J. W., Kwakkel, G., Lang, C. E., Swinnen, S. P., et al. (2016). Computational neurorehabilitation: modeling plasticity and learning to predict recovery. Journal of NeuroEngineering and Rehabilitation, 13(1). doi:10.1186/s12984-016-0148-3
Reinkensmeyer, D. J., Burdet, E., Casadio, M., Krakauer, J. W., Kwakkel, G., Lang, C. E., Swinnen, S. P., Ward, N. S., and Schweighofer, N. (2016). Computational neurorehabilitation: modeling plasticity and learning to predict recovery. Journal of NeuroEngineering and Rehabilitation 13.
Reinkensmeyer, D.J., et al., 2016. Computational neurorehabilitation: modeling plasticity and learning to predict recovery. Journal of NeuroEngineering and Rehabilitation, 13(1).
D.J. Reinkensmeyer, et al., “Computational neurorehabilitation: modeling plasticity and learning to predict recovery”, Journal of NeuroEngineering and Rehabilitation, vol. 13, 2016.
Reinkensmeyer, D.J., Burdet, E., Casadio, M., Krakauer, J.W., Kwakkel, G., Lang, C.E., Swinnen, S.P., Ward, N.S., Schweighofer, N.: Computational neurorehabilitation: modeling plasticity and learning to predict recovery. Journal of NeuroEngineering and Rehabilitation. 13, (2016).
Reinkensmeyer, David J., Burdet, Etienne, Casadio, Maura, Krakauer, John W., Kwakkel, Gert, Lang, Catherine E., Swinnen, Stephan P., Ward, Nick S., and Schweighofer, Nicolas. “Computational neurorehabilitation: modeling plasticity and learning to predict recovery”. Journal of NeuroEngineering and Rehabilitation 13.1 (2016).
This data publication is cited in the following publications:
This publication cites the following data publications:

8 Citations in Europe PMC

Data provided by Europe PubMed Central.

White matter microstructural organisation of interhemispheric pathways predicts different stages of bimanual coordination learning in young and older adults.
Zivari Adab H, Chalavi S, Beets IAM, Gooijers J, Leunissen I, Cheval B, Collier Q, Sijbers J, Jeurissen B, Swinnen SP, Boisgontier MP., Eur J Neurosci 47(5), 2018
PMID: 29363832
Two hands, one brain, and aging.
Maes C, Gooijers J, Orban de Xivry JJ, Swinnen SP, Boisgontier MP., Neurosci Biobehav Rev 75(), 2017
PMID: 28188888
Pattern of improvement in upper limb pointing task kinematics after a 3-month training program with robotic assistance in stroke.
Pila O, Duret C, Laborne FX, Gracies JM, Bayle N, Hutin E., J Neuroeng Rehabil 14(1), 2017
PMID: 29029633
Combining robotic training and inactivation of the healthy hemisphere restores pre-stroke motor patterns in mice.
Spalletti C, Alia C, Lai S, Panarese A, Conti S, Micera S, Caleo M., Elife 6(), 2017
PMID: 29280732
Editorial: Neural and Computational Modeling of Movement Control.
Lan N, Cheung VC, Gandevia SC., Front Comput Neurosci 10(), 2016
PMID: 27630557

Export

0 Marked Publications

Open Data PUB

Web of Science

View record in Web of Science®

Sources

PMID: 27130577
PubMed | Europe PMC

Search this title in

Google Scholar