From single neurons to behavior in the jellyfish Aurelia aurita
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...
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doaj-95c4b87590674e05a278f52b9e05ed612021-05-05T18:12:26ZengeLife Sciences Publications LtdeLife2050-084X2019-12-01810.7554/eLife.50084From single neurons to behavior in the jellyfish Aurelia auritaFabian Pallasdies0https://orcid.org/0000-0001-5359-4699Sven Goedeke1https://orcid.org/0000-0001-5314-345XWilhelm Braun2https://orcid.org/0000-0002-9419-3311Raoul-Martin Memmesheimer3Neural Network Dynamics and Computation, Institute of Genetics, University of Bonn, Bonn, GermanyNeural Network Dynamics and Computation, Institute of Genetics, University of Bonn, Bonn, GermanyNeural Network Dynamics and Computation, Institute of Genetics, University of Bonn, Bonn, GermanyNeural Network Dynamics and Computation, Institute of Genetics, University of Bonn, Bonn, GermanyJellyfish 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.https://elifesciences.org/articles/50084jellyfishscyphozoaAurelia auritacomputational neurosciencenerve netsmulti-scale modeling |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Fabian Pallasdies Sven Goedeke Wilhelm Braun Raoul-Martin Memmesheimer |
spellingShingle |
Fabian Pallasdies Sven Goedeke Wilhelm Braun Raoul-Martin Memmesheimer From single neurons to behavior in the jellyfish Aurelia aurita eLife jellyfish scyphozoa Aurelia aurita computational neuroscience nerve nets multi-scale modeling |
author_facet |
Fabian Pallasdies Sven Goedeke Wilhelm Braun Raoul-Martin Memmesheimer |
author_sort |
Fabian Pallasdies |
title |
From single neurons to behavior in the jellyfish Aurelia aurita |
title_short |
From single neurons to behavior in the jellyfish Aurelia aurita |
title_full |
From single neurons to behavior in the jellyfish Aurelia aurita |
title_fullStr |
From single neurons to behavior in the jellyfish Aurelia aurita |
title_full_unstemmed |
From single neurons to behavior in the jellyfish Aurelia aurita |
title_sort |
from single neurons to behavior in the jellyfish aurelia aurita |
publisher |
eLife Sciences Publications Ltd |
series |
eLife |
issn |
2050-084X |
publishDate |
2019-12-01 |
description |
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. |
topic |
jellyfish scyphozoa Aurelia aurita computational neuroscience nerve nets multi-scale modeling |
url |
https://elifesciences.org/articles/50084 |
work_keys_str_mv |
AT fabianpallasdies fromsingleneuronstobehaviorinthejellyfishaureliaaurita AT svengoedeke fromsingleneuronstobehaviorinthejellyfishaureliaaurita AT wilhelmbraun fromsingleneuronstobehaviorinthejellyfishaureliaaurita AT raoulmartinmemmesheimer fromsingleneuronstobehaviorinthejellyfishaureliaaurita |
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