Abstract
Although spontaneous use of the more-affected arm and hand after stroke is an important determinant of participation and quality of life, a number of patients exhibit decreases in use following rehabilitative therapy. Our general hypothesis that there exists a threshold for function of the paretic arm and hand after therapy. If function is above this threshold, spontaneous use will increase in the months following therapy. In contrast, if function is below this threshold, spontaneous use will decrease. A previous “qualitative” neurocomputational model predicted that if the dose of therapy is sufficient to bring performance above a certain threshold, training can be stopped. Computer simulations are presented showing how changes in arm use following therapy depend on a performance threshold. This prediction was tested by reanalyzing the data from the extremity constraint-induced therapy evaluation (EXCITE) trial, phase III randomized controlled trial in which participants received constraint-induced movement therapy for 2 weeks and were tested both 1 week and 1 year after therapy. Finally, we present a “quantitative” model, with parameters fitted to longitudinal data of individual patients recovering from stroke, that allow us to estimate the effect of therapy on the time-varying interactions between arm function and use.
Biography
Dr. Nicolas Schweighofer graduated from the Ecole Nationale Supérieure de Mécanique in Nantes, France, and obtained a PhD from the University of Southern California (USC), USA. He is an Associate Professor in the Division of Biokinesiology and Physical Therapy an the University of Southern California, USA, and currently on a sabbatical at the Université de Montpelier in France. His research spams from computational neuroscience modelling to robot-assisted rehabilitation, and he founded the field of Computational Neurorehabilitation. His current projects include model-based optimisation of learning via adaptive practice schedules in healthy and stroke individuals.