Neural Network Wiring and Topological Stochastic Resonance

Neural Network Wiring and Topological Stochastic Resonance | 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 Research Article Neural Network Wiring and Topological Stochastic Resonance Antoine Dedieu, Konstantin Nikolic This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8679920/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The aim of this work is to determine how variability in synaptic connectivityshapes activity in balanced spiking networks and whether “topological stochasticresonance” (amplified responses due to structural disorder) can emerge withoutchanging the connection count. For that purpose we have simulated balancednetworks of excitatory and inhibitory leaky integrate-and-fire neurons driven byexternal Poisson input. Four connectivity schemes were constructed each witha progressively more unequal distribution of the number of inputs received byindividual neurons but with the same total number of conncetions. Topologicalvariability was quantified by the standard deviation (σ) of a normal distribu-tion describing the number of inputs received from each presynaptic populationto each neuron. Our results indicate that by increasing variability in connectiv-ity produces a strong effect of increased mean firing rates and rate heterogeneityacross neuron classes, despite the total number of synapses per population beingconserved. Network balance remained globally preserved, but local deviationsgrew with σ, revealing regimes of enhanced responsiveness. We demonstratehow the structural “noise” in the form of variable synaptic connection countcan strongly modulate activity in balanced networks without altering overallconnection count. These results support the novel concept of Topological Stochas-tic Resonance and suggest that controlled connectivity disorder may help tunesensitivity and stability in cortical-like circuits. Topological Stochastic resonance Spiking neural network Neural Network Balanced Neural Network Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted 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-8679920","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":587803486,"identity":"7674dae3-819b-4263-8ee7-9171169e48ca","order_by":0,"name":"Antoine Dedieu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYLCCBBBxgMHgAAODDQMDO0TQALd6ZhQtaWABwloYoFqA5GHCWvhn9x988HCHDQPf8eaNBz62nU/ccJiB8cMPhsPGuLRI3DnMbJB4Jo1B8syxgoMz226DtDBL9jAcNsPprhvJbBKJbYcZDG7kGBzmBWrZBnSbNNCFNrh0yEO0/GcwuP/G4PDftnMgLcy/8WkxgGgB+v0Gj8FhxrYDIC1sIFtwOszwRrKxQWJbMo/kmbSCgz3nko33AzVa9hik4/S+3I3Ehw9/ttnJ8R0/vPnDjzI72ZntzYdv/KiwNmzA6X8I4EFiMzbgjchRMApGwSgYBYQBAC7cXHyCBq0OAAAAAElFTkSuQmCC","orcid":"","institution":"University of West London","correspondingAuthor":true,"prefix":"","firstName":"Antoine","middleName":"","lastName":"Dedieu","suffix":""},{"id":587803487,"identity":"f89a97e5-240d-4af9-9f61-d4d6077b5cba","order_by":1,"name":"Konstantin Nikolic","email":"","orcid":"","institution":"University of West London","correspondingAuthor":false,"prefix":"","firstName":"Konstantin","middleName":"","lastName":"Nikolic","suffix":""}],"badges":[],"createdAt":"2026-01-23 13:55:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8679920/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8679920/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104782808,"identity":"ad22ad2d-8f3e-4909-aecd-2bee6471a285","added_by":"auto","created_at":"2026-03-17 07:57:49","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3921333,"visible":true,"origin":"","legend":"","description":"","filename":"TopologicalStochasticResonance.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8679920/v1_covered_44c375eb-83fe-428b-9bd5-9adc8a521cec.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Neural Network Wiring and Topological Stochastic Resonance","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Topological Stochastic resonance, Spiking neural network, Neural Network, Balanced Neural Network","lastPublishedDoi":"10.21203/rs.3.rs-8679920/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8679920/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The aim of this work is to determine how variability in synaptic connectivityshapes activity in balanced spiking networks and whether “topological stochasticresonance” (amplified responses due to structural disorder) can emerge withoutchanging the connection count. 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