A computational model of use-dependent motor recovery following a stroke: Optimizing corticospinal activations via reinforcement learning can explain residual capacity and other strength recovery dynamics

David J. Reinkensmeyer, Emmanuel Guigon, Marc A. Maier. A computational model of use-dependent motor recovery following a stroke: Optimizing corticospinal activations via reinforcement learning can explain residual capacity and other strength recovery dynamics. Neural Networks, 29:60-69, 2012. [doi]

@article{ReinkensmeyerGM12,
  title = {A computational model of use-dependent motor recovery following a stroke: Optimizing corticospinal activations via reinforcement learning can explain residual capacity and other strength recovery dynamics},
  author = {David J. Reinkensmeyer and Emmanuel Guigon and Marc A. Maier},
  year = {2012},
  doi = {10.1016/j.neunet.2012.02.002},
  url = {http://dx.doi.org/10.1016/j.neunet.2012.02.002},
  researchr = {https://researchr.org/publication/ReinkensmeyerGM12},
  cites = {0},
  citedby = {0},
  journal = {Neural Networks},
  volume = {29},
  pages = {60-69},
}