Motor strategies and adiabatic invariants: The case of rhythmic motion in parabolic flights

TL;DR

This study investigates how human rhythmic arm movements adapt to changing gravity during parabolic flights, using adiabatic invariants to identify nearly-conserved quantities and understand motor control strategies in variable environments.

Contribution

The paper introduces a novel application of adiabatic invariant theory to analyze human motor control in variable gravity conditions, revealing how gravity influences movement dynamics.

Findings

Adiabatic invariant in vertical direction increases linearly with gravity.

Participants adapt more freely in unrestrained conditions.

Transverse plane trajectories suggest higher-derivative dynamics.

Abstract

The role of gravity in human motor control is at the same time obvious and difficult to isolate. It can be assessed by performing experiments in variable gravity. We propose that adiabatic invariant theory may be used to reveal nearly-conserved quantities in human voluntary rhythmic motion, an individual being seen as a complex time-dependent dynamical system with bounded motion in phase-space. We study an explicit realization of our proposal: An experiment in which we asked participants to perform $\infty-$ shaped motion of their right arm during a parabolic flight, either at self-selected pace or at a metronome's given pace. Gravity varied between $0$ and $1.8$ $g$ during a parabola. We compute the adiabatic invariants in participant's frontal plane assuming a separable dynamics. It appears that the adiabatic invariant in vertical direction increases linearly with $g$, in agreement with our model. Differences between the free and metronome-driven conditions show that participants' adaptation to variable gravity is maximal without constraint. Furthermore, motion in the participant's transverse plane induces trajectories that may be linked to higher-derivative dynamics. Our results show that adiabatic invariants are relevant quantities to show the changes in motor strategy in time-dependent environments.