ArticleProceedings of the National Academy of Sciences of the United States of America2023
Olfactory search with finite-state controllers.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Decoding behavior with minimal and interpretable agent models.PLoS computational biology · 2026Article
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- Article
- Neural dynamics for working memory and evidence integration during olfactory navigation in Drosophila.Nature communications · 2026Article
- Fly navigational responses exploit plume-specific odor motion and gradient cues.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Neural dynamics for working memory and evidence integration during olfactory navigation inbioRxiv : the preprint server for biology · 2025Article
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- Article
- Memoryless chemotaxis with discrete cues.Journal of the Royal Society, Interface · 2024Article
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Authors and funding
3 authors.
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Abstract
Long-range olfactory search is an extremely difficult task in view of the sparsity of odor signals that are available to the searcher and the complex encoding of the information about the source location. Current algorithmic approaches typically require a continuous memory space, sometimes of large dimensionality, which may hamper their optimization and often obscure their interpretation. Here, we show how finite-state controllers with a small set of discrete memory states are expressive enough to display rich, time-extended behavioral modules that resemble the ones observed in living organisms. Finite-state controllers optimized for olfactory search have an immediate interpretation in terms of approximate clocks and coarse-grained spatial maps, suggesting connections with neural models of search behavior.
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