Two Paths to Bias: Distinct influences of stimulus probability and previous choice on drift diffusion parameters

Two Paths to Bias: Distinct influences of stimulus probability and previous choice on drift diffusion parameters | 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 Two Paths to Bias: Distinct influences of stimulus probability and previous choice on drift diffusion parameters Carina Forster, Sebastian Hellmann This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9492170/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Perceptual decisions are shaped by prior information and choice history, yet their distinct computational implementations remain unclear. Here, we jointly model these sources of bias using hierarchical drift diffusion models fitted to behavioral and electroencephalography data from two near-threshold somatosensory detection-confidence experiments with stable (N = 43) and volatile (N = 39) probability environments. Across both datasets, we find that stimulus probability biases the starting point of evidence accumulation, whereas previous choices modulate the drift rate, consistent with a history-dependent accumulation bias. Bayesian model comparison provides decisive evidence for this dissociation across environments. Models with stimulus-dependent accumulation noise are strongly preferred, indicating increased variability in signal trials. Integrating single-trial pre-stimulus beta-band power into the model, we further show that baseline fluctuations mediate the effect of previous choice on drift rate in the stable environment, but not in the volatile environment, while no mediation is observed for probability-induced starting point biases. Together, these results establish a mechanistic dissociation between explicit and implicit biases in perceptual decision-making and demonstrate how environmental volatility shapes their neural and computational signatures. Computational Modelling History Biases Response times Drift Diffusion Model Pre-Stimulus Beta Power Probability Cue Paradigm Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 06 May, 2026 Reviewers agreed at journal 04 May, 2026 Reviewers invited by journal 03 May, 2026 Editor assigned by journal 27 Apr, 2026 Submission checks completed at journal 27 Apr, 2026 First submitted to journal 22 Apr, 2026 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-9492170","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":635662568,"identity":"8bf86c2f-fb04-46ee-8731-d1b71485c60e","order_by":0,"name":"Carina Forster","email":"","orcid":"","institution":"QIMR Berghofer Medical Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Carina","middleName":"","lastName":"Forster","suffix":""},{"id":635662569,"identity":"722a9a97-49cd-4240-a35a-fe11ab656f6b","order_by":1,"name":"Sebastian Hellmann","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIiWNgGAWjYFACHhAhAWE8KABxmA+ASMYGvFoSoFoSDEAibIkNRGhhQNbCY4hXi3x778GPP39YyJsz8B58kGCwTd5cuuf7Y94cBtl+HFoMzpxLluZJkDDc2cCXbJBgcNtw55yzG5t5tzEYz8RhjYFEjoE00C+MGw7wmEkAtTBuuJEL1pK44QAOh81/Y/zzR4KEPVCL+Q+gFvsNN3IegrXsx6GF4QbQcKDDEkG2AL1/OxGohRFiC06/5KVZ86RJJG84zGMMcljyhhtphjPnbpMwnoHLYe1nD9/8YVNnu+F4j+GHDxW3bTfcSH7w4e02G9l+HN5HAGZUrgQh9aNgFIyCUTAK8AAAExFgoaMDcWcAAAAASUVORK5CYII=","orcid":"","institution":"Technical University of Munich","correspondingAuthor":true,"prefix":"","firstName":"Sebastian","middleName":"","lastName":"Hellmann","suffix":""}],"badges":[],"createdAt":"2026-04-22 07:09:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9492170/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9492170/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109067634,"identity":"945e1784-2ba9-4a9b-ae04-d7e3069ed819","added_by":"auto","created_at":"2026-05-12 09:58:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2346691,"visible":true,"origin":"","legend":"","description":"","filename":"BetaBiasDDM.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9492170/v1_covered_b8fbd356-4284-4cce-a846-8fb765432553.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Two Paths to Bias: Distinct influences of stimulus probability and previous choice on drift diffusion parameters","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"computational-brain-and-behavior","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cobb","sideBox":"Learn more about [Computational Brain \u0026 Behavior](https://link.springer.com/journal/42113)","snPcode":"42113","submissionUrl":"https://submission.nature.com/new-submission/42113/3","title":"Computational Brain \u0026 Behavior","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Computational Modelling, History Biases, Response times, Drift Diffusion Model, Pre-Stimulus Beta Power, Probability Cue Paradigm","lastPublishedDoi":"10.21203/rs.3.rs-9492170/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9492170/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePerceptual decisions are shaped by prior information and choice history, yet their distinct computational implementations remain unclear. 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