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Estimating the time structure of descending activation that generates movements at different speeds

View ORCID ProfileRachid Ramadan, Cora Hummert, View ORCID ProfileJean Stephane Jokeit, Gregor Schöner
doi: https://doi.org/10.1101/2022.03.21.485078
Rachid Ramadan
1Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
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  • For correspondence: rachid.ramadan@ini.rub.de
Cora Hummert
1Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
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Jean Stephane Jokeit
1Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
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Gregor Schöner
1Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
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Abstract

In targeted movements of the hand, descending activation patterns must not only generate muscle activation, but must also adjust spinal reflexes from stabilizing the initial to stabilizing the final postural state. We estimate descending activation patterns that change minimally while generating a targeted movement within a given movement time based on a model of the biomechanics, muscle dynamics, and the stretch reflex. The estimated descending activation patterns predict human movement trajectories quite well. Their temporal structure varies across workspace and with movement speed, from monotonic profiles for slow movements to non-monotonic profiles for fast movements. Descending activation patterns at different speeds thus do not result from a not mere rescaling of invariant templates, but reflect varying needs to compensate for interaction torques and muscle dynamics. The virtual attractor trajectories, on which active muscle torques are zero, lie within reachable workspace and are largely invariant movements when represented in end-effector coordinates. Their temporal structure along movement direction changes from linear ramps to “N-shaped” profiles with increasing movement speed.

Author summary What descending patterns of activation drive targeted movements? Based on a model that includes biomechanics, muscles dynamics and the stretch reflex we estimate the descending activation patterns by minimizing their change using optimal control, given a movement target and movement time. The resulting activation patterns predict experimentally observed human movements reasonably well. The temporal structure of the estimated descending activation patterns depends on the speed of the movement, varying from monotonic for slow to non-monotonic for fast movements. This structure reflects the need to compensate for interaction torques and muscle properties. From the model we are able to estimate the virtual attractor trajectories on which all active muscle torques are zero. These lie within reachable workspace, and are relatively uniform across workspace. Their time structure varies from linear ramps for slow movements to N-shaped temporal profiles for fast movements.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted March 22, 2022.
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Estimating the time structure of descending activation that generates movements at different speeds
Rachid Ramadan, Cora Hummert, Jean Stephane Jokeit, Gregor Schöner
bioRxiv 2022.03.21.485078; doi: https://doi.org/10.1101/2022.03.21.485078
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Estimating the time structure of descending activation that generates movements at different speeds
Rachid Ramadan, Cora Hummert, Jean Stephane Jokeit, Gregor Schöner
bioRxiv 2022.03.21.485078; doi: https://doi.org/10.1101/2022.03.21.485078

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