Neuromechanical wave resonance in jellyfish swimming

Turning kinematics of the scyphomedusaAurelia aurita

Scyphomedusae are widespread in the oceans and their swimming has provided valuable insights into the hydrodynamics of animal propulsion. Most of this research has focused on symmetrical, linear swimming. However, in nature, medusae typically swim circuitous, nonlinear paths involving frequent turns. Here we describe swimming turns by the scyphomedusaAurelia auritaduring which asymmetric bell margin motions produce rotation around a linearly translating body center. These jellyfish 'skid' through turns and the degree of asynchrony between opposite bell margins is an approximate predictor of turn magnitude during a pulsation cycle. The underlying neuromechanical organization of bell contraction contributes substantially to asynchronous bell motions and inserts a stochastic rotational component into the directionality of scyphomedusan swimming. These mechanics are important for natural populations because asynchronous bell contraction patterns are commonin situand result in frequent turns by naturally swimming medusae.

Hydrodynamic Diversity of Jets Mediated by Giant and Non-Giant Axon Systems in Brief Squid

Neural input is critical for establishing behavioral output, but understanding how neuromuscular signals give rise to behaviors remains a challenge. In squid, locomotion through jet propulsion underlies many key behaviors, and the jet is mediated by two parallel neural pathways, the giant and non-giant axon systems. Much work has been done on the impact of these two systems on jet kinematics, such as mantle muscle contraction and pressure-derived jet speed at the funnel aperture. However, little is known about any influence these neural pathways may have on the hydrodynamics of the jet after it leaves the squid and transfers momentum to the surrounding fluid for the animal to swim. To gain a more comprehensive view of squid jet propulsion, we made simultaneous measurements of neural activity, pressure inside the mantle cavity, and wake structure. By computing impulse and time-averaged forces from the wake structures of jets associated with giant or non-giant axon activity, we show that the influence of neural pathways on jet kinematics could extend to hydrodynamic impulse and force production. Specifically, the giant axon system produced jets with, on average, greater impulse magnitude than those of the non-giant system. However, non-giant impulse could exceed that of the giant system, evident by the graded range of its output in contrast to the stereotyped nature of the giant system. Our results suggest that the non-giant system offers flexibility in hydrodynamic output, while recruitment of giant axon activity can provide a reliable boost when necessary.

A physics-based model of swarming jellyfish

We propose a model for the structure formation of jellyfish swimming based on active Brownian particles. We address the phenomena of counter-current swimming, avoidance of turbulent flow regions and foraging. We motivate corresponding mechanisms from observations of jellyfish swarming reported in the literature and incorporate them into the generic modelling framework. The model characteristics is tested in three paradigmatic flow environments.

Planktos: An Agent-Based Modeling Framework for Small Organism Movement and Dispersal in a Fluid Environment with Immersed Structures

Multiscale modeling of marine and aerial plankton has traditionally been difficult to address holistically due to the challenge of resolving individual locomotion dynamics while being carried with larger-scale flows. However, such problems are of paramount importance, e.g., dispersal of marine larval plankton is critical for the health of coral reefs, and aerial plankton (tiny arthropods) can be used as effective agricultural biocontrol agents. Here we introduce the open-source, agent-based modeling software Planktos targeted at 2D and 3D fluid environments in Python. Agents in this modeling framework are relatively tiny organisms in sufficiently low densities that their effect on the surrounding fluid motion can be considered negligible. This library can be used for scientific exploration and quantification of collective and emergent behavior, including interaction with immersed structures. In this paper, we detail the implementation and functionality of the library along with some illustrative examples. Functionality includes arbitrary agent behavior obeying either ordinary differential equations, stochastic differential equations, or coded movement algorithms, all under the influence of time-dependent fluid velocity fields generated by computational fluid dynamics, experiments, or analytical models in domains with static immersed mesh structures with sliding or sticky collisions. In addition, data visualization tools provide images or animations with kernel density estimation and velocity field analysis with respect to deterministic agent behavior via the finite-time Lyapunov exponent.

Free swimming of a squid-inspired axisymmetric system through jet propulsion

An axisymmetric fluid-structure interaction model based on the immersed-boundary approach is developed to study the self-propelled locomotion of a squid-inspired swimmer in relatively low Reynolds numbers (O(102)). Through cyclic deformation, the swimmer generates intermittent jet flow, which, together with the added-mass effect associated with the body deformation, provides thrust. Through a control volume analysis we are able to determine the jet-related thrust. By adding it to the added-mass-related thrust we separate the net thrust on the body from the drag effect due to forward motion, so that the propulsion efficiency in free swimming is found. This numerical algorithm and thrust-drag decomposition method are used to study the dynamics of the bio-inspired locomotion system in different conditions, whereby the performance is characterized by the aforementioned propulsion efficiency as well as the conventionally defined cost of transport.

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

Jellyfish (Medusozoa) have been deemed the most energy-efficient animals in the world. Their bell morphology and relatively simple nervous systems make them attractive to robotocists. Although, the science community has devoted much attention to understanding their swimming performance, there is still much to be learned about the jet propulsive locomotive gait displayed by prolate jellyfish. Traditionally, computational scientists have assumed uniform duty cycle kinematics when computationally modeling jellyfish locomotion. In this study we used fluid-structure interaction modeling to determine possible enhancements in performance from shuffling different duty cycles together across multiple Reynolds numbers and contraction frequencies. Increases in speed and reductions in cost of transport were observed as high as 80% and 50%, respectively. Generally, the net effects were greater for cases involving lower contraction frequencies. Overall, robust duty cycle combinations were determined that led to enhanced or impeded performance.

Emergent metachronal waves using tension-driven, fluid-structure interaction models of tomopterid parapodia

Metachronal waves are ubiquitous in propulsive and fluid transport systems across many different scales and morphologies in the biological world. Tomopterids are a soft-bodied, holopelagic polychaete that use metachrony with their flexible, gelatinous parapodia to deftly navigate the midwater ocean column that they inhabit. In the following study, we develop a three-dimensional, fluid-structure interaction model of a tomopterid parapodium to explore the emergent metachronal waves formed from the interplay of passive body elasticity, active muscular tension, and hydrodynamic forces. After introducing our model, we examine the effects that varying material properties have on the stroke of an individual parapodium. We then explore the temporal dynamics when multiple parapodia are placed sequentially and how differences in the phase can alter the collective kinematics and resulting flow field.