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State-switching navigation strategies in Caenorhabditis elegans are beneficial for chemotaxis

Research output: Contribution to journalArticlepeer-review

Abstract

Animals employ different strategies for relating sensory input and behavioral output to navigate sensory environments, but what strategy to use, when to switch and why remain unclear. Caenorhabditis elegans navigate by combining “steering” (small heading changes) with “turn” (large reorientations). It is unknown whether transitions between these elements are driven solely by sensory input or also by persistent internal states. It is also unclear how worms sometimes appear to exit turns such that they are already oriented toward a goal, despite their presumed lack of spatial awareness during turns. We address these questions with measurements of sensory-guided navigation and a statistical model of state-dependent control. Worm navigation is well described by a sensory-driven, two-state-switching model whose states persist for seconds and produce distinct sensorimotor mixtures: one state is steer-enriched, the other turn-enriched. This hierarchical temporal organization challenges the view that gradient-climbing strategies are static and purely stimulus-locked. Instead, sensory input causally modulates transitions between persistent states, creating the appearance of “directed turns” when exiting the turn-enriched state. Measurements using genetically perturbed animals and modeling with data-constrained reinforcement-learning both show that state switching enhances gradient-climbing performance. Together, measurement, perturbation, and modeling reveal that state switching is functionally beneficial, organizing behavior across time—a principle that may generalize across species and contexts.

Original languageEnglish (US)
Article numbere2519999123
JournalProceedings of the National Academy of Sciences of the United States of America
Volume123
Issue number25
DOIs
StatePublished - Jun 2026

All Science Journal Classification (ASJC) codes

  • General

Keywords

  • C. elegans
  • navigation
  • neural circuits
  • reinforcement learning
  • state space model

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