une

Partenaires

CNRS
Logo tutelle
Logo carnot


Rechercher

Sur ce site


Accueil > À noter > Séminaires > Séminaire du jeudi 6 décembre 2012 présenté par Nicolas SCHWEIGHOFER (University of Southern California & Université de Montpellier 1). A 14h, Salle des thèses, Faculté des Sciences du Sport, Campus de Luminy (Marseille). ’Models and neural bases of motor adaptation with applications to neuro-rehabilitation post-stroke.’

Séminaire du jeudi 6 décembre 2012 présenté par Nicolas SCHWEIGHOFER (University of Southern California & Université de Montpellier 1). A 14h, Salle des thèses, Faculté des Sciences du Sport, Campus de Luminy (Marseille). ’Models and neural bases of motor adaptation with applications to neuro-rehabilitation post-stroke.’

Mise à jour : 6 novembre 2014

Although our understanding of the mechanisms underlying motor adaptation has greatly benefited from previous computational models, the architecture of motor memory is still uncertain. We investigated the architecture of human motor memory by systematically testing possible architectures via a combination of computer simulations and of a dual visuo-motor adaptation experiment. Our result suggests that during motor adaptation fast and slow processes are updated simultaneously from the same motor learning errors (Lee and Schweighofer, Journal of Neuroscience 2009). Next, we discuss how our model can account for 1) the spacing effect, in which increasing the inter-trial interval reduces performance during training, but enhances long-term retention compared to blocked schedules, and 2) the contextual interference (CI) effect, in which intermixing the learning of different tasks via random schedules reduces performance during training, but enhances long-term retention compared to blocked schedules. In recent work (Ogawa, Kim, Imamizu and Schweighofer, SFN 2012), we conducted a model-based fMRI experiment, to study the neural substrates of motor adaptation. Using a modified version of the multiple-time-constant model of Kording et al. (2007), we identified three characteristic brain regions significantly correlated with the different time constants. The prefrontal region was correlated with regressors with the shorter time constants, the medial parietal cortex became more dominant with the intermediate time constants, and the cerebellum was activated with the longer time constants. We confirmed these results with a multivariate classification analysis, which showed that the neural activity in the cerebellum region progressively represented the two separate tasks. Finally, the model was used to investigate the effect of training schedules on long-term retention in healthy participants and participants at least 3 months post-stroke (Schweighofer et al., Journal of Neurophysiology, 2011). As predicted by our model, only post-stroke participants with good visuo-spatial working memory exhibited the CI effect. Thus, following blocked schedule training, the better the working memory, the worse the long-term retention.

Post-scriptum :

Nicolas Schweighofer, PhD is an Associate Professor in the Department of Biokinesiology and Physical Therapy, and has joint appointments in the Neuroscience and Computer Science Departments at the University of Southern California (USC) and in Montpellier 1 University.
Before joining USC, he was a researcher at ATR in Kyoto and head of R&D at Cerego, an educational software company based in Tokyo.