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.

Membrane flutter in three-dimensional inviscid flow

“…2011; Hoover et al. 2021)). In the inviscid models computational elements are distributed along surfaces rather than throughout the flow volume.…”

“…Inviscid flow models such as the vortex-lattice method are widely used to model viscous high-Reynolds-number flows for aquatic and aerodynamic propulsion (Kagemoto et al 2000;Katz & Plotkin 2001;Shukla & Eldredge 2007;Michelin & Llewellyn Smith 2009;Willis & Persson 2014;Ayancik, Mivehchi & Moored 2022) because the computational cost is generally much lower than for direct solvers (e.g. in the case of complex and deforming body geometries, immersed-boundary, lattice-Boltzmann and deforming-mesh methods (Kim & Peskin 2007;Willis et al 2007a;Zhu et al 2011;Hoover et al 2021)). In the inviscid models computational elements are distributed along surfaces rather than throughout the flow volume.…”

“…Immersed-boundary methods have also been used to study a number of 3-D swimming problems, such as the self-propulsion of flapping flexible plates (Masoud & Alexeev 2010;Tang et al 2016), the role of active muscle contraction, passive body elasticity and fluid forces in forward swimming (Mittal et al 2008;Borazjani et al 2013;Hoover, Griffith & Miller 2017;Dawoodian & Sau 2021;Hoover et al 2021) and the propulsive forces acting on flexible fish bodies (Hoover & Tytell 2020).…”

Bio-Inspired Ocean Exploration

“…First, the robotic control is currently limited to one-dimensional steering in the direction of the current jellyfish heading. Full six degree-of-freedom steering of the jellyfish will likely require more complex muscle stimulation strategies than that implemented to date (Hoover et al, 2021), such as using various asymmetric activation patterns of electrodes on the swim muscle. Asymmetric activation patterns of electrodes can be used to initiate bell pitching due to torque, such as by stimulating one electrode to initiate time-dependent muscle contractions that travel in a bidirectional wave from the point of electrode contact.…”

Hopscotching Jellyfish: combining different duty cycle kinematics can lead to enhanced swimming performance

“…Thus, the remaining time of the cycle involved either bell expansion or pauses between successive pulses. Both of these studies viewed the duty cycle as a prescribed parameter in the model, while other computational studies model contractions via an emergent process of applying tension to the bell itself [40,41,42]. However, across all of these simulations, the duty cycle and overall contraction kinematics did not vary from cycle to cycle.…”