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Séminaire impromptu - Emmanuel GuigonExperimental and theoretical study of velocity fluctuations during slow movements in humans

Abstract :

 Slow and segmented movements are frequently observed in brain disorders and are detrimental in many activities of the daily life.
The origin and nature of these movements are still poorly understood. We studied velocity fluctuations during movements in a range of slow mean travel speeds performed by healthy participants with a stylus on a graphic tablet.
These fluctuations resembled those found in pathological movements and had a robust organization based on a succession of movement segments of approximately constant duration and of amplitude varying with mean travel speed.
A model explains that the fluctuations could result from the brain tracking a staircase input corresponding to a periodic sampling along the desired spatial path. The same model indicates that fast and smooth movements would result from the brain directly tracking a spatial goal. 
These results could explain why improvements in motor control are observed in patients with different movement disorders following changes in movement guidance and task instructions.


Selected publications

Proietti T, Guigon E, Roby-Brami A, Jarrassé N., Modifying upper-limb inter-joint coordination in healthy subjects by training with a robotic exoskeleton. J Neuroeng Rehabil. 2017 Jun 12;14(1):55. doi: 10.1186/s12984-017-0254-x. PMID: 28606179 Free PMC Article

Cos I, Girard B, Guigon E. Balancing out dwelling and moving: optimal sensorimotor synchronization. Journal of Neurophysiology. 114: 146-58. PMID 25878154 DOI: 10.1152/jn.00175. 2015

Rigoux L, Guigon E. A model of reward- and effort-based optimal decision making and motor control. Plos Computational Biology. 8: e1002716. PMID 23055916 DOI: 10.1371/journal.pcbi.1002716 2012

Reinkensmeyer DJ, Guigon E, Maier MA. A computational model of use-dependent motor recovery following a stroke: optimizing corticospinal activations via reinforcement learning can explain residual capacity and other strength recovery dynamics. Neural Networks : the Official Journal of the International Neural Network Society. 29: 60-9. PMID 22391058 DOI: 10.1016/j.neunet.2012.02.002