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Accueil > À noter > Séminaires > October 24, 2014. Sandro MUSSA-IVALDI (Northwestern Univ. & Rehabilitation Institute of Chicago). A 14h, Salle des thèses, Faculté des Sciences du Sport, Campus de Luminy (Marseille). ’The engineering of motor learning : From basic neuroscience to clinical applications.’

October 24, 2014. Sandro MUSSA-IVALDI (Northwestern Univ. & Rehabilitation Institute of Chicago). A 14h, Salle des thèses, Faculté des Sciences du Sport, Campus de Luminy (Marseille). ’The engineering of motor learning : From basic neuroscience to clinical applications.’

Mise à jour : 6 novembre 2014

The ability to learn is perhaps the most important feature of biological intelligence. It allows us to act in a multitude of environments and to combine sensory information with knowledge that we have acquired from previous experiences. When we practice a new task we are not only getting better at it. Our brains change and acquire knowledge on the physics of the environment and of our bodies. As the motor system is exposed to a deterministic environment, it forms internal representations that allow us to generate effective motor commands and to predict the sensory consequences of our actions. Learning is also our first line of defense after suffering an injury that changes our body. It gives us the ability to adapting to the new condition and to recover functionality and independence. Understanding learning is of critical importance for developing effective approaches to the recovery of motor functions following stroke, spinal cord injury and other neurological disorders. I will present and discuss recent studies that link the understanding of the mechanisms of motor learning to the development of new strategies for neurorehabilitation and of new approaches to the design of human-machine interfaces.

Bibliography

Shadmehr, R., & Mussa-Ivaldi, F. A. (1994). Adaptive Representation of Dynamics During Learning of a Motor Task. Journal of Neuroscience, 14, 3208-3224.
Conditt, M. A., Gandolfo, F., & Mussa-Ivaldi, F. A. (1997). The motor system does not learn the dynamics of the arm by rote memorization of past experience. Journal of Neurophysiology, 78(1), 554-560.
Mosier, K. M., Scheidt, R. A., Acosta, S., & Mussa-Ivaldi, F. A. (2005). Remapping Hand Movements in a Novel Geometrical Environment. Journal of Neurophysiology, 94, 4362-4372.
Casadio, M., Pressman, A., Fishbach, A., Danziger, Z., Acosta, S., Chen, D., . . . Mussa-Ivaldi, F. A. (2010). Functional reorganization of upper-body movement after spinal cord injury. Experimental Brain Research, 207, 233-247.
Shadmehr, R., & Mussa-Ivaldi, F. A. (2012). Biological Learning and Control. How the Brain Builds Representations, Predicts Events and Makes Decisions. Cambridge, MA : MIT Press.
Danziger, Z., & Mussa-Ivaldi, F. A. (2012). The influence of visual motion on motor learning. Journal of Neuroscience, 32(29), 9859 –9869.
Ranganathan, R., Adewuyi, A., & Mussa-Ivaldi, F. A. (2013). Learning to be Lazy : Exploiting redundancy in a novel task to minimize movement-related effort. Journal of Neuroscience, 33(7), 2754-2760.
Wang, X., Casadio, M., Weber, K. A., Mussa-Ivaldi, F. A., & Parrish, T. (2014). White Matter Microstructure Changes Induced by Motor Skill Learning utilizing a Body Machine Interface. Neuroimage, 88, 32-40.

Post-scriptum :

Ferdinando A. (Sandro) Mussa-Ivaldi was born in Torino (Italy). He as a
degree (Laurea) in physics from the University of Torino (1978) and a PhD
in biomedical engineering from the Politecnico of Milano (187).
He is Professor of Physiology, Physical medicine and Rehabilitation and
Biomedical Engineering at Northwestern University. He is director of the
Robotics Laboratory of the Rehabilitation Institute of Chicago. His areas of
interest and expertise include robotics, neurobiology of the sensory-motor
system and computational neuroscience. Among Dr. Mussa-Ivaldi’s
achievements are :
• The first measurement of human arm multi-joint impedance,
• The development of a technique for investigating the mechanisms of motor learning through the application of deterministic force fields,
• The discovery of a family of integrable generalized inverses for redundant kinematic chains,
• The discovery of functional modules within the spinal cord that generate a discrete family of forcefields,
• The development of a theoretical framework for the representation, generation and learning of arm movements
• The development of the first neurorobotic system in which a neural preparation in-vitro - the brainstem of a lamprey - controls the behavior of a mobile-robot through a closed-loop interaction.
• The development of techniques to promote reorganization of upper body motion for the control of assistive devices