Seminar Details
2012-10-23 (14.00) : Can control theory tell us anything about the brain?
At Euler building
Organized by Mathematical Engineering
Speaker :
Crevecoeur, Frédéric
Abstract :
Understanding how the brain controls movements is a major challenge as most neurological dysfunction result in sensorimotor deficits with an obvious impact on the quality of life. Control theory is a powerful tool to examine whether some components of neural processing can be mapped into computations involved in the control algorithm. In this talk, I will present recent results showing that rapid feedback responses to mechanical perturbations are associated with, and driven by, internal state estimation. We first demonstrated that when we navigate our arm in the vicinity of physical obstacles, straight movements are sometimes rerouted around obstacles following a perturbation. We used optimal control principles to estimate when the controller should switch between strategies and found similar state-dependent switch in the data as predicted from the model. Importantly, this switch was expressed in muscle activity in about 50 ms, which is much faster than voluntary reaction times and decisional processes (> 100 ms). We further examined when the central nervous system updates the estimates of the state of the limb following a perturbation, as ignoring delays as short as 50 ms can cause instability. We reasoned that if limb afferent feedback is extrapolated to estimate the present state, then changing the relationship between the initial perturbation and the current limb motion should result in inadequate motor responses. We found evidence that participants relied on a rapid update in state estimation following the perturbations. This rapid update is adaptive and influences the motor response within 50 ms of perturbation onset according to the expected perturbation profile. In all, these results show that rapid responses traditionally viewed as reflexes, are actually driven by internal state estimation. These results imply that the underlying neural pathway, including primary motor cortex and the cerebellum, implement a state-dependent feedback control policy.