Continuous input drives motor cortical dynamics during reaching

Continuous input drives motor cortical dynamics during reaching | 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 Continuous input drives motor cortical dynamics during reaching Andrew Schwartz, Hongwei Mao, Brady Hasse This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8585660/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract In a departure from current models of autonomous cortical activity, we examined the effect of continuous input on the dynamic activity of motor cortical neurons throughout a reaching task. We found a series of distinct state transitions in the firing rates of these recorded neural populations. We then asked whether these changes in state were due to internal processing in the motor cortex, as previous models would suggest, or to continuous external inputs. In other words, were signals coming from outside the motor cortex the main drivers of neural activity during reaching behavior? To answer this question, we used hybrid neural networks (HNNs)—consisting of a mixture of artificial connectivity and empirical firing rates—to construct realistic model systems. The HNNs faithfully produced the firing rates of the individual neurons and the state transitions of the populations we recorded, with extrinsic input consisting of episodically modulated neurons. Instead of the reported primacy of intrinsic action, we found that input from extrinsic sources was responsible for these results. Episodic external drive produced consistent changes in the statistics of pre-threshold input integration to cause the state transitions. By using HNNs with empirically constrained connectivity, we have shown that continuous input is a plausible agent for broad system functionality. Biological sciences/Neuroscience/Motor control/Motor cortex Biological sciences/Neuroscience/Computational neuroscience/Dynamical systems Full Text Additional Declarations There is NO Competing Interest. Supplementary Files supplementalfiguresNatureNeuroscience.pdf Supplemental Figures Cite Share Download PDF Status: Under Review 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. 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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-8585660","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":584278062,"identity":"8e75d732-a332-4f3b-b809-fd1aa995b123","order_by":0,"name":"Andrew Schwartz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYDACCQbGBwkVDDxgDg+RWpgNHpxh4OFhI0ELm+TDNqBqorXwz25/IJE4746MvXwD44O3bcRYcueMgUHitmcghzEbziVGC8ONHIaExG2HQVrYpHmJ0SJ/I/3BgcQ5YC3sv4nSYnAjwbAhsQFiCzNRWgzvnDFmSDgG9MuxxGbJOeeI0CJ3u/35zx81d+zZmw8f/PCmjAgtUHAAiBkbiFcP1TIKRsEoGAWjAAcAAIg2NZBLWjbQAAAAAElFTkSuQmCC","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":true,"prefix":"","firstName":"Andrew","middleName":"","lastName":"Schwartz","suffix":""},{"id":584278063,"identity":"9b107982-6ce0-4633-95a4-5bf81a2a25ec","order_by":1,"name":"Hongwei Mao","email":"","orcid":"https://orcid.org/0000-0001-7287-8291","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Hongwei","middleName":"","lastName":"Mao","suffix":""},{"id":584278064,"identity":"3155a496-f378-46a9-9f6d-025a405a8509","order_by":2,"name":"Brady Hasse","email":"","orcid":"https://orcid.org/0000-0002-5273-3092","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Brady","middleName":"","lastName":"Hasse","suffix":""}],"badges":[],"createdAt":"2026-01-12 23:15:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8585660/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8585660/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102746750,"identity":"ab2ea600-0dde-4ba7-8d3e-680cd938df42","added_by":"auto","created_at":"2026-02-16 09:01:00","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1229373,"visible":true,"origin":"","legend":"","description":"","filename":"ContinousInputNatureNeuroscience.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8585660/v1_covered_870d69a4-2216-4da9-ab46-4dde82f1631f.pdf"},{"id":102472810,"identity":"4979b879-dc11-40e8-ac22-7a2e20e88601","added_by":"auto","created_at":"2026-02-12 04:25:48","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3473041,"visible":true,"origin":"","legend":"Supplemental Figures","description":"","filename":"supplementalfiguresNatureNeuroscience.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8585660/v1/6ded54b4504ec4358aa3cb4a.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Continuous input drives motor cortical dynamics during reaching","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"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-8585660/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8585660/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"In a departure from current models of autonomous cortical activity, we examined the effect of continuous input on the dynamic activity of motor cortical neurons throughout a reaching task. 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