Computational models and motor learning paradigms: Could they provide insights for neuroplasticity after stroke? An overview

Computational approaches for modelling the central nervous system (CNS) aim to develop theories on processes occurring in the brain that allow the transformation of all information needed for the execution of motor acts. Computational models have been proposed in several fields, not only to interpret the CNS functioning, but also its efferent behaviour. Computational model theories can provide insights into neuromuscular and brain function allowing us to reach a deeper understanding of neuroplasticity.
Source: Journal of the Neurological Sciences - Category: Neurology Authors: Source Type: research