A Markovian dynamics for Caenorhabditis elegans behavior across scales

• 成果类型: Article
• 署名作者: Costa, Antonio C.; Ahamed, Tosif; Jordan, David; Stephens, Greg J.
• 署名单位: Vrije Universiteit Amsterdam; Howard Hughes Medical Institute; University of Cambridge; Okinawa Institute of Science & Technology Graduate University; Universite Paris Cite; Universite PSL; Ecole Normale Superieure (ENS); Centre National de la Recherche Scientifique (CNRS); Sorbonne Universite
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-13240
• DOI: 10.1073/pnas.2318805121
• 发表日期: 2024-08-06
• 关键词: delay embeddings; forced systems; c-elegans; flagellum; motion; genes; state

摘要

How do we capture the breadth of behavior in animal movement, from rapid body twitches to aging? Using high-resolution videos of the nematode worm Caenorhabditis elegans, we show that a single dynamics connects posture-scale fluctuations with trajectory diffusion and longer-lived behavioral states. We take short posture sequences as an instantaneous behavioral measure, fixing the sequence length for maximal prediction. Within the space of posture sequences, we construct a fine-scale, maximum entropy partition so that transitions among microstates define a high-fidelity Markov model, which we also use as a means of principled coarse-graining. We translate these dynamics into movement using resistive force theory, capturing the statistical properties of foraging trajectories. Predictive across scales, we leverage the longest-lived eigenvectors of the inferred Markov chain to perform a top-down subdivision of the worm's foraging behavior, revealing both runs-and-pirouettes as well as previously uncharacterized finer-scale behaviors. We use our model to investigate the relevance of these fine-scale behaviors for foraging success, recovering a trade-off between local and global search strategies.