From single neurons to behavior in the jellyfish Aurelia aurita

Abstract
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Abstract

Jellyfish nerve nets provide insight into the origins of nervous systems, as both their taxonomic position and their evolutionary age imply that jellyfish resemble some of the earliest neuron-bearing, actively-swimming animals. Here we develop the first neuronal network model for the nerve nets of jellyfish. Specifically, we focus on the moon jelly Aurelia aurita and the control of its energy-efficient swimming motion. The proposed single neuron model disentangles the contributions of different currents to a spike. The network model identifies factors ensuring non-pathological activity and suggests an optimization for the transmission of signals. After modeling the jellyfish's muscle system and its bell in a hydrodynamic environment, we explore the swimming elicited by neural activity. We find that different delays between nerve net activations lead to well-controlled, differently directed movements. Our model bridges the scales from single neurons to behavior, allowing for a comprehensive understanding of jellyfish neural control of locomotion.

Data availability

No experimental data sets were generated in this study. Simulation parameters for all figures can be found in the manuscript and its supplements.Hydrodynamics simulations were performed with the IB2D package by Nicholas A. Battista (https://github.com/nickabattista/ib2d).

Article and author information

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Fabian Pallasdies

Neural Network Dynamics and Computation, Institute of Genetics, University of Bonn, Bonn, Germany

For correspondence
fabianpallasdies@gmail.com

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-5359-4699
Sven Goedeke

Neural Network Dynamics and Computation, Institute of Genetics, University of Bonn, Bonn, Germany

Competing interests
The authors declare that no competing interests exist.
Wilhelm Braun

Neural Network Dynamics and Computation, Institute of Genetics, University of Bonn, Bonn, Germany

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-9419-3311
Raoul Memmesheimer

Neural Network Dynamics and Computation, Institute of Genetics, University of Bonn, Bonn, Germany

For correspondence
rm.memmesheimer@uni-bonn.de

Competing interests
The authors declare that no competing interests exist.

Funding

The German Federal Ministry of Education and Research (01GQ1710)

Fabian Pallasdies
Sven Goedeke
Wilhelm Braun
Raoul Memmesheimer

SMARTSTART Joint Training Program of the Bernstein Network and the VolkswagenStiftung (SmartStart2)

Fabian Pallasdies

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.