Journal Article FZJ-2020-04924

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From single neurons to behavior in the jellyfish Aurelia aurita

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2019
eLife Sciences Publications Cambridge

eLife 8, e50084 () [10.7554/eLife.50084]

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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.

Classification:

Contributing Institute(s):
  1. Computational and Systems Neuroscience (INM-6)
  2. Theoretical Neuroscience (IAS-6)
  3. Jara-Institut Brain structure-function relationships (INM-10)
Research Program(s):
  1. 574 - Theory, modelling and simulation (POF3-574) (POF3-574)

Appears in the scientific report 2021
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Medline ; Creative Commons Attribution CC BY 4.0 ; DOAJ ; OpenAccess ; Article Processing Charges ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; DOAJ Seal ; Ebsco Academic Search ; Essential Science Indicators ; Fees ; IF >= 5 ; JCR ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection ; Zoological Record
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Institute Collections > INM > INM-6
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Open Access

 Record created 2020-12-04, last modified 2024-03-13


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