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    We analyzed the chaotic locomotion of Caenorhabditis elegans using optical fluctuations. This method quantifies movement predictability in microscopic species, revealing chaotic markers in nematode behavior.

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    Area of Science:

    • Physics, Optics, and Photonics
    • Biophysics and Quantitative Biology
    • Dynamical Systems and Chaos Theory

    Background:

    • Characterizing the complex movement patterns of microscopic organisms is crucial for understanding biological systems.
    • Dynamical systems theory offers tools to analyze unpredictable behaviors, but applying it to biological locomotion requires innovative methods.

    Purpose of the Study:

    • To develop and demonstrate a novel method for quantifying locomotory predictability in microscopic species.
    • To analyze the chaotic dynamics of live nematode (Caenorhabditis elegans) movement using optical far-field diffraction.

    Main Methods:

    • A dynamic far-field diffraction experiment was conducted using live Caenorhabditis elegans.
    • Time series data were generated from optical fluctuations at a single point in the diffraction pattern.
    • The largest Lyapunov exponent was calculated to characterize the chaotic nature of the nematode's locomotion by reconstructing its phase space.

    Main Results:

    • The time series derived from optical fluctuations exhibited clear markers of chaos in Caenorhabditis elegans locomotion.
    • The average largest Lyapunov exponent for 10 wildtype (N2) Caenorhabditis elegans was calculated as 1.27±0.03 s⁻¹.
    • This indicates a quantifiable level of chaotic dynamics in the nematode's movement patterns.

    Conclusions:

    • Far-field diffraction analysis of optical fluctuations provides a robust method for characterizing locomotory chaos in microscopic organisms.
    • The largest Lyapunov exponent serves as a reliable metric for assessing movement predictability in Caenorhabditis elegans.
    • This technique opens new avenues for studying the biomechanics and behavioral dynamics of small biological systems.