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Published March 16, 2021 | Supplemental Material + Published
Journal Article Open

Neuromechanical wave resonance in jellyfish swimming

Abstract

For organisms to have robust locomotion, their neuromuscular organization must adapt to constantly changing environments. In jellyfish, swimming robustness emerges when marginal pacemakers fire action potentials throughout the bell's motor nerve net, which signals the musculature to contract. The speed of the muscle activation wave is dictated by the passage times of the action potentials. However, passive elastic material properties also influence the emergent kinematics, with time scales independent of neuromuscular organization. In this multimodal study, we examine the interplay between these two time scales during turning. A three-dimensional computational fluid–structure interaction model of a jellyfish was developed to determine the resulting emergent kinematics, using bidirectional muscular activation waves to actuate the bell rim. Activation wave speeds near the material wave speed yielded successful turns, with a 76-fold difference in turning rate between the best and worst performers. Hyperextension of the margin occurred only at activation wave speeds near the material wave speed, suggesting resonance. This hyperextension resulted in a 34-fold asymmetry in the circulation of the vortex ring between the inside and outside of the turn. Experimental recording of the activation speed confirmed that jellyfish actuate within this range, and flow visualization using particle image velocimetry validated the corresponding fluid dynamics of the numerical model. This suggests that neuromechanical wave resonance plays an important role in the robustness of an organism's locomotory system and presents an undiscovered constraint on the evolution of flexible organisms. Understanding these dynamics is essential for developing actuators in soft body robotics and bioengineered pumps.

Additional Information

© 2021 National Academy of Sciences. Published under the PNAS license. Edited by Leslie Greengard, New York University, New York, NY, and approved January 31, 2021 (received for review September 28, 2020). We thank Cabrillo Marine Aquarium for providing A. aurita for experimental muscle wave speed calculations. We also thank Boyce Griffith for assistance regarding model implementation. This research was funded by the NSF Division of Mathematical Sciences, under Faculty Early Career Development Program Grant 1151478 (to L.A.M.). Data Availability: All study data are included in the article, SI Appendix, and Movies S1–S8. Author contributions: A.P.H., N.W.X., B.J.G., S.P.C., J.H.C., J.O.D., and L.A.M. designed research; A.P.H., N.W.X., B.J.G., S.P.C., and J.H.C. performed research; A.P.H., N.W.X., B.J.G., S.P.C., J.H.C., J.O.D., and L.A.M. analyzed data; and A.P.H., N.W.X., and L.A.M. wrote the paper. The authors declare no competing interest. This article is a PNAS Direct Submission. This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2020025118/-/DCSupplemental.

Attached Files

Published - e2020025118.full.pdf

Supplemental Material - pnas.2020025118.sapp.pdf

Supplemental Material - pnas.2020025118.sm01.mov

Supplemental Material - pnas.2020025118.sm02.mov

Supplemental Material - pnas.2020025118.sm03.mov

Supplemental Material - pnas.2020025118.sm04.mov

Supplemental Material - pnas.2020025118.sm05.mov

Supplemental Material - pnas.2020025118.sm06.mov

Supplemental Material - pnas.2020025118.sm07.mov

Supplemental Material - pnas.2020025118.sm08.mov

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Additional details

Created:
August 22, 2023
Modified:
October 23, 2023