Biology subjects

Crevecoeur, F.

Publications and source records attributed to Crevecoeur, F..

3 recordsLinked to original sources

bioRxiv2018

A sub-movement time scale of human motor adaptation

Humans and other animals adapt motor commands to predictable disturbances within tens of trials in laboratory conditions. A central question is how does the nervous system adapt to disturbances in natural conditions when exactly the same movements cannot be practiced several times. Because motor commands and sensory feedback together carry continuous information about limb dynamics, we hypothesized that the nervous system could adapt to unexpected disturbances online. We tested this hypothesis in two reaching experiments during which velocity-dependent force fields were randomly applied. We found that within-movement feedback corrections gradually improved, despite the fact that the perturbations were unexpected. Moreover, when participants were instructed to stop at a via-point, the application of a force field prior to the via-point induced mirror-image after-effects after the via-point, consistent with within-trial adaptation to the unexpected dynamics. These findings suggest a fast time-scale of motor learning, which complements feedback control and supports adaptation of an ongoing movement. Significance StatementAn important function of the nervous system is to adapt motor commands in anticipation of predictable disturbances, which supports motor learning when we move in novel environments such as force fields. Here we show that movement control when exposed to unpredictable disturbances exhibit similar traits: motor corrections become tuned to the force field, and they evoke after effects within an ongoing sequence of movements. We propose and discuss the framework of adaptive control to explain these results: a real-time learning algorithm, which complements feedback control in the presence of model errors. This candidate model potentially links movement control and trial-by-trial adaptation of motor commands.

neuroscience↗

bioRxiv2017

Simulating The Impact Of Sensorimotor Deficits On Reaching Performance

The healthy human nervous system accurately and robustly controls movements despite nonlinear dynamics, noise, and delays. After a stroke, motor ability frequently becomes impaired. To provide insight into the relative impact of specific sensorimotor deficits on motor performance, we modeled neural control of reaching with the human upper limb as a near-optimally feedback-controlled two-degree-of-freedom system with biologically based parameters. We added three sensorimotor impairments commonly associated with post-stroke hemiparesis--abnormal joint coupling, increased noise on internally modeled dynamics, and muscular weakness-- and examined the impact on reaching performance. We found that abnormal joint coupling unknown to the systems internal model caused systematic perturbations to trajectories, longer reach durations, and target overshoot. Increasing internal model noise and muscular weakness had little impact on motor performance unless model noise was increased by several orders of magnitude. Many reaches performed by our perturbed models replicate features commonly observed in reaches by hemiparetic stroke survivors. The sensitivity to unmodeled abnormal joint coupling agrees with experimental findings that abnormal coupling (possibly related to internal model errors) is the main cause of post-stroke motor impairment.

neuroscience↗

bioRxiv2017

Saccadic suppression as a perceptual consequence of efficient sensorimotor estimation

Humans perform saccadic eye movements two to three times per second. When doing so, the nervous system strongly suppresses sensory feedback for extended periods of time in comparison with the movement time. Why does the brain discard so much visual information? Here we suggest that perceptual suppression may arise from efficient sensorimotor computations, assuming that perception and control are fundamentally linked. More precisely, we show that a Bayesian estimator should reduce the weight of sensory information around the time of saccades, as a result of signal dependent noise and of sensorimotor delays. Such reduction parallels the behavioral suppression occurring prior to and during saccades, and the reduction in neural responses to visual stimuli observed across the visual hierarchy. We suggest that saccadic suppression originates from efficient sensorimotor processing, indicating that the brain shares neural resources for perception and control.

neuroscience↗