Neural circuits underlying context-dependent competition between defensive actions in Drosophila larva | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Neural circuits underlying context-dependent competition between defensive actions in Drosophila larva Tihana Jovanic, Maxime Lehman, Chloé Barré, Md Amit Hasan, Benjamin Flament, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3879941/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Jan, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract To ensure their survival, animals must be able to respond adaptively to threats within their environment. However, the precise neural circuit mechanisms that underlie such flexible defensive behaviors remain poorly understood. Using neuronal manipulations, machine-learning-based behavioral detection, Electron Microscopy (EM) connectomics and calcium imaging in Drosophila larva, we have mapped the second-order interneurons differentially involved in the competition between different defensive actions and the main pathways to the motor side putatively involved in inhibiting startle-type behaviors and promoting escape behaviors in a context dependent manner. We found that mechanosensory stimulation modulates the nociceptive escape sequences and inhibits C-shape bends and Rolls in favor of startle-like behaviors. This suggests a competition between mechanosensory-induced startle responses and escape behaviors. Structural and functional connectivity revealed that the second order interneurons receive their main input from projection neurons that integrate mechanosensory and nociceptive stimuli. The analysis of their postsynaptic connectivity in EM revealed that they make indirect connections to the pre-motor and motor neurons. Finally, we identify a pair of descending neurons that could modulate the escape sequence and promote startle behaviors. Altogether, these results characterize the pathways involved in the startle and escape competition, modulated by the sensory context. Biological sciences/Neuroscience/Neural circuits Biological sciences/Neuroscience/Sensorimotor processing/Decision Full Text Additional Declarations There is NO Competing Interest. Supplementary Files Supplementarytable1presynaptic.xlsx Supplementary Table 1 Supplementarytable2BasinsA08mx.xlsx Supplementary Table 2 Supplementarytable3TransitionProbabilitiesfinal.xlsx Supplementary Table 3 Supplementarytable4postsynaptic.xlsx Supplementary Table 4 Supplementarytable5SPARCsummary.xlsx Supplementary Table 5 Supplementaryvideo1.mp4 Supplementary video 1 Cite Share Download PDF Status: Published Journal Publication published 28 Jan, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3879941","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":269831341,"identity":"a3a08627-ca89-4e90-b58d-ddff7bb3acf2","order_by":0,"name":"Tihana Jovanic","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYBAC+8M8YJqfXyKxTfJHjQ1EuAKPFjZmiBZmyRnJxyUSjqVBhM/g08IA1WJwIy19RmLTYSK0sPMe/FxQA9Ry5oz5jMSG8/Lm0scfMBzcg89hfMnSM46BtZjdSGy4bbizL8eA4cAzvH4xkOZhQ2hJMDjDw8D84QBeLca/ef4BtRzv/1aR2HAOqIX9AcMB/FrMpHnbGJQNjveYWSQ2HQBqYTAgqMWat0/CTLKZx8wi4Viy4YYzPAYH8GrhP2N8m+ebjQw/UC8wKu3kgQ57+ACfFiiQQOUS1jAKRsEoGAWjAC8AALPrUA1KqkaAAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-0525-8620","institution":"Université Paris-Saclay, CNRS, Institut des neurosciences Paris-Saclay, 91400, Saclay, France.","correspondingAuthor":true,"prefix":"","firstName":"Tihana","middleName":"","lastName":"Jovanic","suffix":""},{"id":269831342,"identity":"c52e733b-a3ab-4aed-b1cd-e6ab0e16c0d0","order_by":1,"name":"Maxime Lehman","email":"","orcid":"","institution":"Université Paris-Saclay, CNRS, Institut des neurosciences Paris-Saclay, 91400, Saclay, France.","correspondingAuthor":false,"prefix":"","firstName":"Maxime","middleName":"","lastName":"Lehman","suffix":""},{"id":269831343,"identity":"10a933fc-f168-4dd7-a419-7f4deec7e6a7","order_by":2,"name":"Chloé Barré","email":"","orcid":"","institution":"Institut Pasteur, Université Paris Cité, CNRS UMR 3571, Decision and Bayesian Computation, Epiméthée, INRIA","correspondingAuthor":false,"prefix":"","firstName":"Chloé","middleName":"","lastName":"Barré","suffix":""},{"id":269831344,"identity":"1aaf56e9-a736-44b9-bdb1-fd6a28aefc63","order_by":3,"name":"Md Amit Hasan","email":"","orcid":"","institution":"Université Paris-Saclay, CNRS, Institut des neurosciences Paris-Saclay, 91400, Saclay, France.","correspondingAuthor":false,"prefix":"","firstName":"Md","middleName":"Amit","lastName":"Hasan","suffix":""},{"id":269831345,"identity":"fd35077b-8166-4aaa-bc2f-abfb7054ad58","order_by":4,"name":"Benjamin Flament","email":"","orcid":"","institution":"Université Paris-Saclay, CNRS, Institut des neurosciences Paris-Saclay, 91400, Saclay, France.","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Flament","suffix":""},{"id":269831346,"identity":"a1bd7865-0ec8-45e3-b06d-1be68f0a3c8a","order_by":5,"name":"Sandra Autran","email":"","orcid":"","institution":"NEUROPSI","correspondingAuthor":false,"prefix":"","firstName":"Sandra","middleName":"","lastName":"Autran","suffix":""},{"id":269831347,"identity":"3b4c924c-e2e8-41d3-8b61-22cbacc24efb","order_by":6,"name":"Neena Dhiman","email":"","orcid":"https://orcid.org/0009-0002-5643-7810","institution":"Institute of Physiology and Pathophysiology, Friedrich-Alexander-Universität Erlangen- Nürnberg,LIMES Institute, Department of Molecular Brain Physiology and Behavior, University of","correspondingAuthor":false,"prefix":"","firstName":"Neena","middleName":"","lastName":"Dhiman","suffix":""},{"id":269831348,"identity":"c81bdeea-3fa1-4304-a853-306307afea5a","order_by":7,"name":"Peter Soba","email":"","orcid":"","institution":"Institute of Physiology and Pathophysiology, Friedrich-Alexander-Universität Erlangen- Nürnberg,LIMES Institute, Department of Molecular Brain Physiology and Behavior, University of","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Soba","suffix":""},{"id":269831349,"identity":"a00d6879-6e7f-4118-8243-ab0e4cae102f","order_by":8,"name":"Jean-Baptiste Masson","email":"","orcid":"https://orcid.org/0000-0002-5484-9056","institution":"Decision and Bayesian Computation, CNRS USR 3756, Department of Computational Biology and Neuroscience. Institut Pasteur, Paris, France","correspondingAuthor":false,"prefix":"","firstName":"Jean-Baptiste","middleName":"","lastName":"Masson","suffix":""}],"badges":[],"createdAt":"2024-01-19 21:45:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3879941/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3879941/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-56185-2","type":"published","date":"2025-01-28T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":74993280,"identity":"a2dedc20-afdb-446f-93a0-01de72e438b1","added_by":"auto","created_at":"2025-01-29 08:07:49","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8216472,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptFinalJanuarycompiledcompressed.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3879941/v1_covered_4485ceb0-be24-4dc4-ae11-ccaf7fb0a838.pdf"},{"id":50337323,"identity":"9a872f6c-5177-44b2-9cce-79ec8b21dbb5","added_by":"auto","created_at":"2024-01-30 02:52:27","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":54233,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 1\u003c/p\u003e","description":"","filename":"Supplementarytable1presynaptic.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3879941/v1/56f379242ec9ae16827a4cf3.xlsx"},{"id":50337698,"identity":"fe3e2b71-4a57-470c-ac58-ebe1ee976264","added_by":"auto","created_at":"2024-01-30 03:08:27","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":11046,"visible":true,"origin":"","legend":"Supplementary Table 2","description":"","filename":"Supplementarytable2BasinsA08mx.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3879941/v1/0cb58674bce8ad0410462af9.xlsx"},{"id":50337324,"identity":"3b05d885-69b4-408d-b8dd-628129a8c9c9","added_by":"auto","created_at":"2024-01-30 02:52:27","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":38074,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 3\u003c/p\u003e","description":"","filename":"Supplementarytable3TransitionProbabilitiesfinal.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3879941/v1/1b75cae7d4eaaf41e96decf3.xlsx"},{"id":50337326,"identity":"e174cfb1-d203-443a-b0ba-e33696f795ec","added_by":"auto","created_at":"2024-01-30 02:52:27","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":14236,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 4\u003c/p\u003e","description":"","filename":"Supplementarytable4postsynaptic.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3879941/v1/38738511a080563759fa5826.xlsx"},{"id":50337565,"identity":"4c42192b-6c38-4f01-9b06-7af5af736a26","added_by":"auto","created_at":"2024-01-30 03:00:27","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":5834,"visible":true,"origin":"","legend":"Supplementary Table 5","description":"","filename":"Supplementarytable5SPARCsummary.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3879941/v1/2aa4e9416c1a32d1ee8b09d0.xlsx"},{"id":50337328,"identity":"e254b53e-0a1a-4d35-8f2a-8776b12e1877","added_by":"auto","created_at":"2024-01-30 02:52:27","extension":"mp4","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":1213740,"visible":true,"origin":"","legend":"Supplementary video 1","description":"","filename":"Supplementaryvideo1.mp4","url":"https://assets-eu.researchsquare.com/files/rs-3879941/v1/3842f5b7539a26aabdde0ecd.mp4"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Neural circuits underlying context-dependent competition between defensive actions in Drosophila larva","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"
[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3879941/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3879941/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo ensure their survival, animals must be able to respond adaptively to threats within their environment. However, the precise neural circuit mechanisms that underlie such flexible defensive behaviors remain poorly understood. Using neuronal manipulations, machine-learning-based behavioral detection, Electron Microscopy (EM) connectomics and calcium imaging in \u003cem\u003eDrosophila \u003c/em\u003elarva, we have mapped the second-order interneurons differentially involved in the competition between different defensive actions and the main pathways to the motor side putatively involved in inhibiting startle-type behaviors and promoting escape behaviors in a context dependent manner. We found that mechanosensory stimulation modulates the nociceptive escape sequences and inhibits C-shape bends and Rolls in favor of startle-like behaviors. This suggests a competition between mechanosensory-induced startle responses and escape behaviors. Structural and functional connectivity revealed that the second order interneurons receive their main input from projection neurons that integrate mechanosensory and nociceptive stimuli. The analysis of their postsynaptic connectivity in EM revealed that they make indirect connections to the pre-motor and motor neurons. Finally, we identify a pair of descending neurons that could modulate the escape sequence and promote startle behaviors. Altogether, these results characterize the pathways involved in the startle and escape competition, modulated by the sensory context.\u003c/p\u003e","manuscriptTitle":"Neural circuits underlying context-dependent competition between defensive actions in Drosophila larva","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-30 02:52:22","doi":"10.21203/rs.3.rs-3879941/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"
[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d90f8460-96d5-43de-99af-6921d3b99afd","owner":[],"postedDate":"January 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28420930,"name":"Biological sciences/Neuroscience/Neural circuits"},{"id":28420931,"name":"Biological sciences/Neuroscience/Sensorimotor processing/Decision"}],"tags":[],"updatedAt":"2025-01-29T08:07:17+00:00","versionOfRecord":{"articleIdentity":"rs-3879941","link":"https://doi.org/10.1038/s41467-025-56185-2","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-01-28 05:00:00","publishedOnDateReadable":"January 28th, 2025"},"versionCreatedAt":"2024-01-30 02:52:22","video":"","vorDoi":"10.1038/s41467-025-56185-2","vorDoiUrl":"https://doi.org/10.1038/s41467-025-56185-2","workflowStages":[]},"version":"v1","identity":"rs-3879941","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3879941","identity":"rs-3879941","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.