The Neuro-Computational Origin of Disposition: Unconsciousness as Lifelong Prior Overfitting and Consciousness as Active Inference

The Neuro-Computational Origin of Disposition: Unconsciousness as Lifelong Prior Overfitting and Consciousness as Active Inference | 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 The Neuro-Computational Origin of Disposition: Unconsciousness as Lifelong Prior Overfitting and Consciousness as Active Inference Barco You This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8915211/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 A central challenge in neuroscience is to understand how an organism’s unique history of interactions with its environment shapes its behavioral dispositions and gives rise to the phenomenal experience of consciousness. Here, we propose a formal computational framework that redefines the unconscious not as a passive reservoir, but as an active, overfitted generative model of an individual’s world. We demonstrate that the lifelong process of minimizing variational free energy—analogous to empirical risk minimization in machine learning—inevitably leads to the over-specialization of internal model parameters θ to the specific statistical regularities of an individual’s sensory history. This overfitting creates a stable, low-entropy informational manifold that determines an individual’s probabilistic “destiny”, or disposition to perceive and act. Within this framework, consciousness, including social forms thereof, is characterized as the recursive, energy-consuming process of active inference, where the brain dynamically minimizes the prediction error between this overfitted prior model and real-time sensory data. By synthesizing concepts from theoretical neuroscience, artificial intelligence, and non-equilibrium thermodynamics, we derive a mathematical model for a “Consciousness Potential” and propose that the brain operates as an entropy-reducing computational system governed by a fundamental information geometry. Our framework provides a unified mathematical language for describing the interplay between experience, disposition, and conscious awareness, offering testable predictions for neuroimaging and AI research. Biological sciences/Neuroscience/Computational neuroscience/Biophysical models Biological sciences/Computational biology and bioinformatics/Machine learning Biological sciences/Psychology Biological sciences/Neuroscience/Social behaviour Biological sciences/Neuroscience/Computational neuroscience/Dynamical systems Full Text Additional Declarations There is NO Competing Interest. 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-8915211","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":594125500,"identity":"d33717db-bbf3-4734-9603-f9f779ebcb3f","order_by":0,"name":"Barco You","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBACAzDJI8HAD6ITCkjRItkA0mJAtBYQ4wAKFw8wZz/78MMHGQs54/OrEz88MGCQ5xc7gF+LZU+6seQMHgljsxtvN0sAHWY4c3YCAYcdSGNj5uGRSNx24+wGkJYEg9uEtJx/BtZSv3nG2c0/iNNyA2JLggF/7zbibLGc8YwZ5BfDGTd4t1kkGEgQ9os5fxrjh489dfL8/Wc33/xRYSPPL01ACxgw9gAJCbBKCSKUg8EPIOY/QKzqUTAKRsEoGGkAAKhjPnfuxVpPAAAAAElFTkSuQmCC","orcid":"","institution":"Heidelberg University","correspondingAuthor":true,"prefix":"","firstName":"Barco","middleName":"","lastName":"You","suffix":""}],"badges":[],"createdAt":"2026-02-19 07:56:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8915211/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8915211/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103503908,"identity":"af18b9fb-f059-40dd-86f7-bbb3f2c13036","added_by":"auto","created_at":"2026-02-26 13:04:35","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":458167,"visible":true,"origin":"","legend":"","description":"","filename":"Overfitting.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8915211/v1_covered_76461e65-aa63-4393-9e17-710b3b597a5c.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"The Neuro-Computational Origin of Disposition: Unconsciousness as Lifelong Prior Overfitting and Consciousness as Active Inference","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-8915211/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8915211/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA central challenge in neuroscience is to understand how an organism’s unique history of interactions with its environment shapes its behavioral dispositions and gives rise to the phenomenal experience of consciousness. 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