Altered gravity highlights central pattern generator mechanisms.
In many nonprimate species, rhythmic patterns of activity such as locomotion or respiration are generated by neural networks at the spinal level. These neural networks are called central pattern generators (CPGs). Under normal gravitational conditions, the energy efficiency and the robustness of human rhythmic movements are due to the ability of CPGs to drive the system at a pace close to its resonant frequency. This property can be compared with oscillators running at resonant frequency, for which the energy is optimally exchanged with the environment. However, the ability of the CPG to adapt the frequency of rhythmic movements to new gravitational conditions has never been studied. We show here that the frequency of a rhythmic movement of the upper limb is systematically influenced by the different gravitational conditions created in parabolic flight. The period of the arm movement is shortened with increasing gravity levels. In weightlessness, however, the period is more dependent on instructions given to the participants, suggesting a decreased influence of resonant frequency. Our results are in agreement with a computational model of a CPG coupled to a simple pendulum under the control of gravity. We demonstrate that the innate modulation of rhythmic movements by CPGs is highly flexible across gravitational contexts. This further supports the involvement of CPG mechanisms in the achievement of efficient rhythmic arm movements. Our contribution is of major interest for the study of human rhythmic activities, both in a normal Earth environment and during microgravity conditions in space.
White
Olivier
O
Unite de Readaptation et de medecine physique, Brussels, Belgium.
Bleyenheuft
Yannick
Y
Ronsse
Renaud
R
Smith
Allan M
AM
Thonnard
Jean-Louis
JL
Lefèvre
Philippe
P
D002490:Central Nervous System / Q000033:anatomy & histology*; D003198:Computer Simulation; D018470:Gravity, Altered; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000166:cytology*; D009474:Neurons / Q000145:classification / Q000502:physiology*; D010507:Periodicity