Emergence of Chaotic Resonance Controlled by Extremely Weak Feedback Signals in Neural Systems

Emergence of Chaotic Resonance Controlled by Extremely Weak Feedback Signals in Neural Systems | 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 Emergence of Chaotic Resonance Controlled by Extremely Weak Feedback Signals in Neural Systems Anh Tu Tran, Sou Nobukawa, Nobuhiko Wagatsuma, Keiichiro Inagaki, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3852390/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 Chaotic resonance is similar to stochastic resonance, which emerges from chaos as an internal dynamical fluctuation. In the chaotic resonance, chaos-chaos intermittency (CCI), in which the chaotic orbits shift between the separated attractor regions, synchronises with a weak input signal. Chaotic resonance exhibits higher sensitivity than stochastic resonance. However, engineering applications are needed because the internal-system-parameter adjustment requirements, especially the biological systems, to induce chaotic resonance from the outside environment is challenging. Moreover, several studies reported abnormal neural activity caused by CCI. Recently, our study proposed that the double-Gaussian-filtered reduced region of orbit (RRO) method (abbreviated as DG-RRO), using external feedback signals to generate chaotic resonance, achieved controlling CCI with a lower perturbation strength than the conventional RRO method. This study applied the DG-RRO method to two typical psychiatric neural systems with CCI behaviour which reproduces the abnormal neural activity of attention deficit hyperactivity disorder and bipolar disorder. Our finding revealed that the DG-RRO feedback method can shift abnormal irregular activity to healthy ordered activity by the chaotic resonance, maintaining extremely low perturbation of the feedback signal. This outcome has the potential application of the DG-RRO approach in treatment while minimising undesired side effects. Biological sciences/Neuroscience/Computational neuroscience/Dynamical systems Physical sciences/Physics/Statistical physics thermodynamics and nonlinear dynamics/Nonlinear phenomena 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. 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-3852390","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":267841151,"identity":"e2ce2591-e45f-4a71-ba5b-cefbe068e477","order_by":0,"name":"Anh Tu Tran","email":"","orcid":"","institution":"Chiba Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Anh","middleName":"Tu","lastName":"Tran","suffix":""},{"id":267841152,"identity":"f850cc29-63e6-480c-affb-4075f8e09b09","order_by":1,"name":"Sou 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In the chaotic resonance, chaos-chaos intermittency (CCI), in which the chaotic orbits shift between the separated attractor regions, synchronises with a weak input signal. Chaotic resonance exhibits higher sensitivity than stochastic resonance. However, engineering applications are needed because the internal-system-parameter adjustment requirements, especially the biological systems, to induce chaotic resonance from the outside environment is challenging. Moreover, several studies reported abnormal neural activity caused by CCI. Recently, our study proposed that the double-Gaussian-filtered reduced region of orbit (RRO) method (abbreviated as DG-RRO), using external feedback signals to generate chaotic resonance, achieved controlling CCI with a lower perturbation strength than the conventional RRO method. 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