This project aims at experimentally determining, and then modelling, the influence of individual somatosensory systems on the activation of human muscles. The experimental results will be used to integrate excitatory and inhibitory contributions in a motor unit pool recruitment model, to better understand the relationship between afferent input and motor output. The individual sensory channels are experimentally targeted by means of specific perturbation paradigms to evaluate how each of them (and their combinations) contribute in tuning the descending drive to the muscle (PN2-3A). Experiments will start from fully controlled contractions (i.e., isometric, on individual muscles) to complex movements (multi-muscle coordination). Sensor dynamics will be predicted on the basis of an enhanced muscle spindle model and included into a biophysical system model of a human limb (PN2-3B). This model will sharpen our understanding of how the muscular activity is modulated by the somatosensory feedback and in response to external stimuli. Ultimately, the project strives for answering the question as to whether it becomes possible in the future to decode motion such that sensory feedback can be predicted without having the actual sensor data at hand.
Publications of PN 2-3A
- K. Gubaev, V. Zaverkin, P. Srinivasan, A. I. Duff, J. Kästner, and B. Grabowski, “Performance of two complementary machine-learned potentials in modelling chemically complex systems,” Npj Comput. Mater., vol. 9, p. 129, 2023, doi: 10.1038/s41524-023-01073-w.
|Project Number||PN 2-3A|
|Project Name||Investigating sensorimotor interaction through selective sensory perturbations|
|Project Duration||October 2019 - June 2023|
|Project Leader||Leonardo Gizzi|
|Project Members||Franziska Domeier, PhD Researcher|
|Project Partners||Syn Schmitt|