ArticleProceedings of the National Academy of Sciences of the United States of America2014
Neural mechanism of optimal limb coordination in crustacean swimming.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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25 citing papers in PubMed, 87 citations in OpenAlex.
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- Pleobot: a modular robotic solution for metachronal swimming.Scientific reports · 2023Article
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- Universal Features in Panarthropod Inter-Limb Coordination during Forward Walking.Integrative and comparative biology · 2021Review
- Tardigrades exhibit robust interlimb coordination across walking speeds and terrains.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
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- Swimming kinematics and hydrodynamics of barnacle larvae throughout development.Proceedings. Biological sciences · 2020Article
- Neural Circuit Mechanism Underlying the Feeding Controlled by Insula-Central Amygdala Pathway.iScience · 2020Article
- Towards an Understanding of Control of Complex Rhythmical "Wavelike" Coordination in Humans.Brain sciences · 2020Review
- Hydrodynamics of metachronal paddling: effects of varying Reynolds number and phase lag.Royal Society open science · 2019Article
- Short-term synaptic dynamics control the activity phase of neurons in an oscillatory network.eLife · 2019Article
- Nitric oxide-mediated intersegmental modulation of cycle frequency in the crayfish swimmeret system.Biology open · 2018Article
- Robust phase-waves in chains of half-center oscillators.Journal of mathematical biology · 2017Article
- IB2d: a Python and MATLAB implementation of the immersed boundary method.Bioinspiration & biomimetics · 2017Article
- De novo transcriptome assembly for the lobster Homarus americanus and characterization of differential gene expression across nervous system tissues.BMC genomics · 2016Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A fundamental challenge in neuroscience is to understand how biologically salient motor behaviors emerge from properties of the underlying neural circuits. Crayfish, krill, prawns, lobsters, and other long-tailed crustaceans swim by rhythmically moving limbs called swimmerets. Over the entire biological range of animal size and paddling frequency, movements of adjacent swimmerets maintain an approximate quarter-period phase difference with the more posterior limbs leading the cycle. We use a computational fluid dynamics model to show that this frequency-invariant stroke pattern is the most effective and mechanically efficient paddling rhythm across the full range of biologically relevant Reynolds numbers in crustacean swimming. We then show that the organization of the neural circuit underlying swimmeret coordination provides a robust mechanism for generating this stroke pattern. Specifically, the wave-like limb coordination emerges robustly from a combination of the half-center structure of the local central pattern generating circuits (CPGs) that drive the movements of each limb, the asymmetric network topology of the connections between local CPGs, and the phase response properties of the local CPGs, which we measure experimentally. Thus, the crustacean swimmeret system serves as a concrete example in which the architecture of a neural circuit leads to optimal behavior in a robust manner. Furthermore, we consider all possible connection topologies between local CPGs and show that the natural connectivity pattern generates the biomechanically optimal stroke pattern most robustly. Given the high metabolic cost of crustacean swimming, our results suggest that natural selection has pushed the swimmeret neural circuit toward a connection topology that produces optimal behavior.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.