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Dimensionality and Dynamics in the Behavior of C. elegans
Open accessAbstract
A major challenge in analyzing animal behavior is to discover some underlying simplicity in complex motor actions. Here, we show that the space of shapes adopted by the nematode Caenorhabditis elegans is low dimensional, with just four dimensions accounting for 95% of the shape variance. These dimensions provide a quantitative description of worm behavior, and we partially reconstruct "equations of motion" for the dynamics in this space. These dynamics have multiple attractors, and we find that the worm visits these in a rapid and almost completely deterministic response to weak thermal stimuli. Stimulus-dependent correlations among the different modes suggest that one can generate more reliable behaviors by synchronizing stimuli to the state of the worm in shape space. We confirm this prediction, effectively "steering" the worm in real time.
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“fish larvae require only three basis functions to describe their backbone shapes, whereas worms analyzed in [18] required four.”
From The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog (2015) · cites this paper as [18]
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“A study of the invertebrate C. elegans by Stephens et al. [18] provided a powerful method to quantify worm locomotion in terms of the worm’s shapes.”
From The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog (2015) · cites this paper as [18]
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“However, fish exhibit larger behavioral complexity.”
From The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog (2015) · cites this paper as [18]
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“fish are stiffer than worms thanks to their backbone (see Fig 6D), leading to a smaller repertoire of accessible shapes of the fish backbone.”
From The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog (2015) · cites this paper as [18]
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Zareei, A., Jalali, M. A., Saadat, M., Grenfell, P., & Alam, M. (2019) · Physical Review Applied · doi:10.1103/physrevapplied.11.014065
Motion prediction enables simulated MR-imaging of freely moving model organisms
Reischl, M., Jouda, M., MacKinnon, N., Fuhrer, E., Bakhtina, N. A., Bartschat, A., Mikut, R., & Korvink, J. G. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006997 · Cited by 1
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Metadata
- Authors
- Stephens, G. J., Johnson-Kerner, B., Bialek, W., & Ryu, W. S.
- Affiliations
- Princeton University (US)
- Corresponding author
- Stephens, Greg J.
- Ryu, William S.
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2008-04-25
- Volume
- 4
- Issue
- 4
- Pages
- e1000028
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC2276863
- OpenAlex
- W2142254043
- Cited by
- 509
- References
- 45
- Citations by year
- 2026: 28 · 2025: 28 · 2024: 41 · 2023: 31 · 2022: 38 · 2021: 47 · 2020: 45 · 2019: 48 · 2018: 29 · 2017: 26 · 2016: 22 · 2015: 23 · 2014: 19 · 2013: 19 · 2012: 24
- FWCI
- 5.91
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- arXiv (Cornell University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- arXiv (Cornell University)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurobiology and Insect Physiology Research
- Physical Sciences › Engineering › Mechanical Engineering › Advanced Materials and Mechanics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Keywords
- Caenorhabditis elegans, worm locomotion, body shape, equations of motion, attractors, thermal stimuli, behavioral synchronization
- MeSH terms
- Animals, Behavior, Animal, Computer Simulation, Gait, Locomotion, Models, Biological, Caenorhabditis elegans
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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