https://doi.org/10.1140/epjb/s10051-024-00683-7
Regular Article - Statistical and Nonlinear Physics
Power consumption during forward locomotion of C. elegans: an electrical circuit simulation
1
Chair of Digital Communication Systems, Ruhr-Universität Bochum, Universitätsstraße 150, 44801, Bochum, NRW, Germany
2
Theoretical Physics and Center for Biophysics, Saarland University, Campus E2 6, 66123, Saarbrücken, Saarland, Germany
a
sebastian.jenderny@ruhr-uni-bochum.de
Received:
14
August
2023
Accepted:
22
March
2024
Published online:
9
April
2024
Biological neuronal networks are of great interest for emerging technological approaches such as neuromorphic engineering due to their capability to efficiently process information. To understand the principles governing this energy efficiency, it is useful to investigate model organisms with small and well-characterized neuronal networks. Caenorhabditis elegans (C. elegans) is such a model organism and perfectly suited for this purpose, because its neuronal network consists of only 302 neurons whose interconnections are known. In this work, we design an ideal electrical circuit modeling this neuronal network in combination with the muscles it controls. We simulate this circuit by a run-time efficient wave digital algorithm. This allows us to investigate the energy consumption of the network occurring during locomotion of C. elegans and hence deduce potential design principles from an energy efficiency point of view. Simulation results verify that a locomotion is indeed generated. We conclude from the corresponding energy consumption rates that a small number of neurons in contrast to a high number of interconnections is favorable for consuming only little energy. This underlines the importance of interneurons. Moreover, we find that gap junctions are a more energy-efficient connection type than synapses, and inhibitory synapses consume more energy than excitatory ones. However, the energetically cheapest connection types are not the most frequent ones in C. elegans’ neuronal network. Therefore, a potential design principle of the network could be a balance between low energy costs and a certain functionality.
© The Author(s) 2024
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