{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"id":[{"id":"https:\/\/ror.org\/04rjz5883","id-type":"ROR","asserted-by":"publisher"}],"name":"eLife"}],"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T15:24:49Z","timestamp":1786980289422,"version":"build-2736575974"},"posted":{"date-parts":[[2026,8,17]]},"reference-count":23,"publisher":"eLife Sciences Publications, Ltd","license":[{"start":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T00:00:00Z","timestamp":1786924800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"HHS | National Institutes of Health","award":["U01NS136507"],"award-info":[{"award-number":["U01NS136507"]}]},{"award":["U01NS136507"],"award-info":[{"award-number":["U01NS136507"]}],"id":[{"id":"https:\/\/ror.org\/01cwqze88","id-type":"ROR","asserted-by":"publisher"}]},{"name":"HHS | National Institutes of Health","award":["R01NS145438"],"award-info":[{"award-number":["R01NS145438"]}]},{"award":["R01NS145438"],"award-info":[{"award-number":["R01NS145438"]}],"id":[{"id":"https:\/\/ror.org\/01cwqze88","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Animal intelligence is not purely a product of abstract computation in the brain, but emerges from dynamic interactions between the nervous system and the body. New connectome datasets and musculoskeletal models now enable integrated, closed-loop simulations of the neural and biomechanical systems of the fruit fly Drosophila, an ideal model organism to investigate embodied intelligence. However, many biological parameters of the nervous system and the body, as well as how they interface, remain unknown. To fill such gaps, researchers are turning to deep reinforcement learning (DRL), a data-driven optimization framework, to create virtual animals that imitate the behavior of real animals. Here, we provide a cautionary tale about the interpretation of such models. We constructed a virtual chimera of two phylogenetically distant species: a connectome of the C. elegans nematode worm and a biomechanical model of the fly body. The worm connectome receives sensory information from the fly body, and an artificial neural network is trained with DRL to map worm motor neuron activations to the fly\u2019s leg actuators. The resulting digital sphinx produces highly realistic fly walking\u2014yet it is biologically meaningless. This exercise teaches us nothing about either animal and exposes a core peril of connectome-body models: behavioral fidelity is achievable without biological fidelity, making such models easy to overinterpret. Done carefully, virtual animals can be powerful partners to biological experiments, but only if their components and interfaces are grounded in biology.<\/jats:p>","DOI":"10.7554\/elife.111516.1","type":"posted-content","created":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:30:15Z","timestamp":1786977015000},"source":"Crossref","is-referenced-by-count":0,"title":["The digital sphinx: Can a worm brain control a fly body?"],"prefix":"10.7554","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4831-3466","authenticated-orcid":false,"given":"Bingni W","family":"Brunton","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00cvxb145","id-type":"ROR","asserted-by":"publisher"}],"name":"Dept of Biology, University of Washington","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"},{"role":"corresponding-author","vocabulary":"crossref"}]},{"given":"Elliott TT","family":"Abe","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00cvxb145","id-type":"ROR","asserted-by":"publisher"}],"name":"Dept of Biology, University of Washington","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lawrence Jianqiao","family":"Hu","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00cvxb145","id-type":"ROR","asserted-by":"publisher"}],"name":"Dept of Biology, University of Washington","place":["United States"]},{"id":[{"id":"https:\/\/ror.org\/00cvxb145","id-type":"ROR","asserted-by":"publisher"}],"name":"Graduate Program in Neuroscience, University of Washington","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5689-5806","authenticated-orcid":false,"given":"John C","family":"Tuthill","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00cvxb145","id-type":"ROR","asserted-by":"publisher"}],"name":"Dept of Neurobiology & Biophysics, University of Washington","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"4374","reference":[{"key":"c1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1911.09451","type":"preprint","article-title":"Deep neuroethology of a virtual rodent","volume-title":"arXiv","author":"Merel","year":"2019"},{"key":"c2","doi-asserted-by":"publisher","first-page":"594","DOI":"10.1038\/s41586-024-07633-4","type":"journal-article","article-title":"A virtual rodent predicts the structure of neural activity across behaviours","volume":"632","author":"Aldarondo","year":"2024","journal-title":"Nature"},{"key":"c3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41586-025-09029-4","type":"journal-article","article-title":"Whole-body physics simulation of fruit fly locomotion","author":"Vaxenburg","year":"2025","journal-title":"Nature"},{"issue":"12","key":"c4","doi-asserted-by":"publisher","first-page":"2353","DOI":"10.1038\/s41592-024-02497-y","type":"journal-article","article-title":"Neuromechfly v2: simulating embodied sensorimotor control in adult Drosophila","volume":"21","author":"Wang-Chen","year":"2024","journal-title":"Nature Methods"},{"issue":"12","key":"c5","doi-asserted-by":"publisher","first-page":"978","DOI":"10.1038\/s43588-024-00738-w","type":"journal-article","article-title":"An integrative data-driven model simulating C. elegans brain, body and environment interactions","volume":"4","author":"Zhao","year":"2024","journal-title":"Nature Computational Science"},{"issue":"107","key":"c6","doi-asserted-by":"publisher","first-page":"eadv4408","DOI":"10.1126\/scirobotics.adv4408","type":"journal-article","article-title":"Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors","volume":"10","author":"Liu","year":"2025","journal-title":"Science Robotics"},{"key":"c7","doi-asserted-by":"publisher","DOI":"10.1101\/2025.07.31.667571","type":"preprint","article-title":"Distributed control circuits across a brain-and-cord connectome","volume-title":"bioRxiv","author":"Bates","year":"2025"},{"key":"c8","doi-asserted-by":"publisher","DOI":"10.1101\/2025.10.09.680999","type":"preprint","article-title":"Sexual dimorphism in the complete connectome of the drosophila male central nervous system","volume-title":"bioRxiv","author":"Berg","year":"2025"},{"key":"c9","doi-asserted-by":"publisher","first-page":"620","DOI":"10.1038\/s41592-022-01466-7","type":"journal-article","article-title":"NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster","volume":"19","author":"Lobato-Rios","year":"2022","journal-title":"Nature Methods"},{"key":"c10","doi-asserted-by":"publisher","first-page":"5026","DOI":"10.1109\/iros.2012.6386109","type":"conference-paper","article-title":"Mujoco: A physics engine for model-based control","author":"Todorov","year":"2012","unstructured":"Todorov E, Erez T, Tassa Y. 2012. 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