Neural control of Caenorhabditis elegans forward locomotion: the role of sensory feedback
Abstract
This paper presents a simple yet biologically-grounded model for the neural control of Caenorhabditis elegans forward locomotion. We identify a minimal circuit within the C. elegans ventral cord that is likely to be sufficient to generate and sustain forward locomotion in vivo. This limited subcircuit appears to contain no obvious central pattern generated control. For that subcircuit, we present a model that relies on a chain of oscillators along the body which are driven by local and proximate mechano-sensory input. Computer simulations were used to study the model under a variety of conditions and to test whether it is behaviourally plausible. Within our model, we find that a minimal circuit of AVB interneurons and B-class motoneurons is sufficient to generate and sustain fictive forward locomotion patterns that are robust to significant environmental perturbations. The model predicts speed and amplitude modulation by the AVB command interneurons. An extended model including D-class motoneurons is included for comparison.
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Previous models of locomotion have typically assumed graded potential neurons, in line with available data at the time.
“Previous models of locomotion have typically assumed graded potential neurons (Niebur and Erdös, 1991; Karbowski et al., 2006; Bryden and Cohen, 2008), in line with available data at the time (Goodman et al., 1998; Nickell et al., 2002; Francis et al., 2003; O’Hagan et al., 2005).”
From Gait Modulation in C. elegans: An Integrated Neuromechanical Model (2012) · cites this paper as Bryden and Cohen, 2008
The model requires integration of proprioceptive inputs over up to half a body length.
“Previously, the necessary extent of proprioceptive receptive fields has been considered only for crawling-like motor patterns (Niebur and Erdös, 1991; Bryden and Cohen, 2008), but we find that our model requires integration of proprioceptive inputs over up to half a body length.”
From Gait Modulation in C. elegans: An Integrated Neuromechanical Model (2012) · cites this paper as Bryden and Cohen, 2008
Cites
The structure of the nervous system of the nematode <i>Caenorhabditis elegans</i>
White, J. G., Southgate, E., Thomson, J. N., & Brenner, S. (1986) · Philosophical Transactions of the Royal Society of London. B, Biological Sciences · doi:10.1098/rstb.1986.0056 · Cited by 5,589 · cited 6× · see citing works
“…receptors were located only at the tips of the neurons (specifically, at the posterior tips of forward locomotion B-class motoneurons, and at the anterior tips of the A-class backward locomotion motoneurons) (unpublished communication, L. Eberly and R. L. Russell, reported in White et al. 1986b).”
BackgroundInfluentialFunctional regeneration after laser axotomy
Yanik, M. F., Cinar, H., Cinar, H. N., Chisholm, A. D., Jin, Y., & Ben-Yakar, A. (2004) · Nature · doi:10.1038/432822a · Cited by 598 · cited 2× · see citing works
“The production of a working model of a complete animal nervous system is one of the grand challenges of computational neuroscience.”
BackgroundActive Currents Regulate Sensitivity and Dynamic Range in C. elegans Neurons
Goodman, M. B., Hall, D. H., Avery, L., & Lockery, S. R. (1998) · Neuron · doi:10.1016/s0896-6273(00)81014-4 · Cited by 370 · see citing works
A Simulation Model of the Locomotion Controllers for the Nematode Caenorhabditis elegans
Bryden, J., & Cohen, N. (2004) · From Animals to Animats 8 · doi:10.7551/mitpress/3122.003.0024 · Cited by 26 · cited 3× · see citing works
“The oscillation frequencies of both segments, the phase lag between the segments and the amplitude of both segments were then averaged for each value of AVB-unit voltage over the three simulation runs.”
BackgroundMethodSelf-citationNeural network model to generate head swing in locomotion of <i>Caenorhabditis elegans</i>
Sakata, K., & Shingai, R. (2004) · Network: Computation in Neural Systems · doi:10.1088/0954-898x_15_3_003
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Gait Modulation in C. elegans: An Integrated Neuromechanical Model
Boyle, J. H., Berri, S., & Cohen, N. (2012) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2012.00010 · Cited by 163 · see citing works
“Previously, the necessary extent of proprioceptive receptive fields has been considered only for crawling-like motor patterns (Niebur and Erdös, 1991; Bryden and Cohen, 2008), but we find that our model requires integration of proprioceptive inputs over up to half a body length.”
BackgroundMethodResultInfluentialSelf-citationSwimming at low Reynolds number: a beginners guide to undulatory locomotion
Cohen, N., & Boyle, J. H. (2010) · Contemporary Physics · doi:10.1080/00107510903268381 · Cited by 110 · see citing works
Self-citationOlivares, E. O., Izquierdo, E. J., & Beer, R. D. (2018) · Network Neuroscience · doi:10.1162/netn_a_00036 · Cited by 38 · see citing works
“…now, only the first of these two hypotheses had been demonstrated using neuroanatomically grounded computational models (Boyle et al., 2012, 2008; Bryden & Cohen, 2008; Deng et al., 2016; Karbowski et al., 2008; Kunert et al., 2017; Niebur & Erdös, 1991, 1993; Sakata & Shingai, 2004; Wen et al.,…”
BackgroundThe whole worm: brain–body–environment models of C. elegans
Izquierdo, E. J., & Beer, R. D. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2016.06.005 · Cited by 27 · see citing works
- Authors
- Bryden, J., & Cohen, N.
- Affiliations
- University of Leeds (GB)
- Corresponding author
- Cohen, Netta
- Venue
- Biological Cybernetics
- Published
- 2008-03-19
- Volume
- 98
- Issue
- 4
- Pages
- 339-351
- ISSN
- 0340-1200 (ISSN-L)
- 1432-0770
- OpenAlex
- W2097290895
- Cited by
- 71
- References
- 5
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 2 · 2022: 3 · 2021: 4 · 2020: 2 · 2018: 8 · 2017: 7 · 2016: 5 · 2015: 5 · 2014: 8 · 2013: 2 · 2012: 6
- FWCI
- 2.87
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Biological Cybernetics (publishedVersion)
- PubMed (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (submittedVersion)
- Funders
- Engineering and Physical Sciences Research Council (EP/C011961/1, EP/C513711/1, EP/C011953/1)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Robotic Locomotion and Control
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurobiology and Insect Physiology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Keywords
- Caenorhabditis elegans, forward locomotion, neural control of locomotion, sensory feedback, fictive locomotion, oscillator chains, central pattern generator
- MeSH terms
- Animals, Computer Simulation, Feedback, Locomotion, Models, Neurological, Nerve Net, Neurons, Sensation, Neural Networks, Computer, Caenorhabditis elegans
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