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Jenny Magnes

Publications and source records attributed to Jenny Magnes.

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Examining the evolution of phase-space elements for C.elegans locomotion

The Caenorhabditis Elegans (C.elegans) nematodes have long been a model organism for quantitative behavioral analysis, due to their tractable nervous system and well-characterized genetics. In particular, dynamic diffraction has been a successful method of studying said microorganisms due to its low level of noise and the ability to simultaneously study multiple degrees of freedom of their neuromuscular system through their locomotion. In this study, we estimate the Lyapunov spectrum of C.elegans locomotion, which offers an insight into how volume elements evolve in the phase space of the underlying dynamical system. For that, we used the Sano-Sawada algorithm to estimate the spectra from the trajectories reconstructed using the Takens embedding procedure. In total, two positive and one negative exponents were calculated and verified to be non-spurious through investigations of their stability for different sets of parameters. Those exponents have values of 0.860, 0.389, and -3.451 respectively. The presence of two positive exponents indicates that C.elegans locomotion is hyperchaotic, while the total sum being negative indicates that the system is dissipative and non-Hamiltonian. Those are key observations for the underlying system and will be significant for the potential creation of future mathematical or computational models.

nlin.CD

A minimal reaction-diffusion neural model generates $\textit{C. elegans}$ undulation

The small (1 mm) nematode $\textit{Caenorhabditis elegans}$ (Corsi [1], wormbook.org) has become widely used as a model organism; in particular, the $\textit{C. elegans}$ connectome has been completely mapped, and $\textit{C. elegans}$ locomotion has been widely studied. We describe a minimal reaction-diffusion model for the locomotion of $\textit{C. elegans}$, using as a framework a simplified, stylized "descending pathway" of neurons as central pattern generator (CPG) (Xu et al., Proceedings of the National Academy of Sciences 115, 2018). Finally, we realize a model of the required oscillations and coupling with a network of coupled Keener (IEEE Transactions on Systems, Man, and Cybernetics SMC-13, 1983 [3]) analog neurons. Note that Olivares et al. (BioRxiv 710566, 2020 [4]) present a likely more realistic model more distributed CPG. We use the simpler simulation to show that a small network of FitzHugh-Nagumo neurons (one of the simplest neuronal models) can generate key features of $\textit{C. elegans}$ undulation, and thus locomotion, yielding a minimal, biomimetic model as a building block for further exploring $\textit{C. elegans}$ locomotion.

physics.bio-ph