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KOELEWIJN AnneORCID_LOGO

  • Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
  • Biomechanics, Sensorimotor Control
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Trajectory optimization, optimal control, movement analysis, gait simulation

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25 Oct 2024
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Feedback-driven adaptation of gravity-related sensorimotor control to an upside-down posture

An inverse gravity experiment supports the theory of an internal gravity model in the central nervous system

Recommended by based on reviews by Jan Hondzinski and 3 anonymous reviewers

The study by Barbusse et al. (2024) investigated how motor control of arm movements is affected by reversed gravity. It is commonly assumed that the central nervous system contains an internal gravity model, and that this model is used to optimize movements to minimize effort under the influence of gravity (e.g., Berret et al., 2008). Previously, the effect of decreased and increased gravity was investigated, and it was shown that people were able to adapt to this novel environment in a matter of minutes or days (e.g., Gaveau et al., 2011). Therefore, the authors investigated the effect of inverse gravity on motor control of arm movements.

In this study, an experiment was performed in which participants were placed in an inversion table and asked to perform as many pointing movements with their shoulder as possible in 12 blocks. In each block, the inversion table was placed either in the head-up or head-down position, and the position was switched every 35 seconds, starting from the head-up position. After 4 blocks, a 90 second break was taken. It was found that movement duration and amplitude did not significantly differ between both orientations. An analysis of the difference in time to peak acceleration, time to peak velocity, and time to peak deceleration between upward and downward movements revealed no significant difference for the peak acceleration, while for the peak velocity, the time difference was significantly smaller in the head-down than the head-up position, and for the peak deceleration, the time difference changed in the head-down position with the number of blocks, reaching a value more similar to the head-up (baseline) position.

The time to peak acceleration did not reverse for the head-down position, which showed that the central nervous system is not able to take advantage of gravity when it is placed in a head-down position, since it does not take advantage of the “free” acceleration provided by gravity. A longer exposure to inverse gravity might allow the body to adapt and re-optimize its internal gravity model to the new situation. The time difference was significantly different for the deceleration, but not for acceleration, which indicates that the movement was adapted mainly by feedback control, but that feedforward control remained largely the same. This further supports the conclusion that the central nervous system had not yet adapted its internal gravity model, and that re-optimization starts with adapting feedback control (Izawa et al., 2008). An important limitation is the discomfort that is experienced in the head-down position, which not only changes gravity, but also created negative physiological responses.

References

Denis Barbusse, Sarah Amoura, Jérémie Gaveau, Olivier White (2024) Feedback-driven adaptation of gravity-related sensorimotor control to an upside-down posture. OSF preprints, ver.3 peer-reviewed and recommended by PCI Health & Movement Sciences. https://doi.org/10.17605/OSF.IO/D9JPF.

Berret B, Darlot C, Jean F, Pozzo T, Papaxanthis C, Gauthier JP (2008) The inactivation principle: mathematical solutions minimizing the absolute work and biological implications for the planning of arm movements. PLoS computational biology, 4, e1000194. https://doi.org/10.1371/journal.pcbi.1000194

Gaveau J, Paizis C, Berret B, Pozzo T, Papaxanthis C (2011) Sensorimotor adaptation of point-to-point arm movements after spaceflight: the role of internal representation of gravity force in trajectory planning. Journal of Neurophysiology, 106, 620–629. https://doi.org/10.1152/jn.00081.2011

Izawa J, Rane T, Donchin O, Shadmehr R (2008) Motor adaptation as a process of reoptimization. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 28, 2883–2891. https://doi.org/10.1523/JNEUROSCI.5359-07.2008

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KOELEWIJN AnneORCID_LOGO

  • Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
  • Biomechanics, Sensorimotor Control
  • recommender

Recommendation:  1

Reviews:  0

Areas of expertise
Trajectory optimization, optimal control, movement analysis, gait simulation