Computational models of neuromotor recovery after a stroke might help to unveil the underlying physiological mechanisms and might suggest how to make recovery faster and more effective. At least in principle, these models could serve: (i) To provide testable hypotheses on the nature of recovery; (ii) To predict the recovery of individual patients; (iii) To design patient-specific "optimal" therapy, by setting the treatment variables for maximizing the amount of recovery or for achieving a better generalization of the learned abilities across different tasks. Here we review the state of the art of computational models for neuromotor recovery through exercise, and their implications for treatment. We show that to properly account for the computational mechanisms of neuromotor recovery, multiple levels of description need to be taken into account. The review specifically covers models of recovery at central, functional and muscle synergy level.
Casadio, M., Tamagnone, I., Summa, S., & Sanguineti, V. (2013). Neuromotor recovery from stroke: computational models at central, functional, and muscle synergy level. Frontiers in Computational Neuroscience, 7. https://doi.org/10.3389/fncom.2013.00097