Transdiagnostic latent factors dissociating depression and anxiety through reinforcement learning

Transdiagnostic latent factors dissociating depression and anxiety through reinforcement learning | 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 Transdiagnostic latent factors dissociating depression and anxiety through reinforcement learning Xinru Huang, Yinmei Ni, Yuxi Wang, Yujia Peng, Jian Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8307305/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 13 You are reading this latest preprint version Abstract Background : The comorbidity of depression and anxiety has long been recognized. While mainly characterized as mood dysregulation, depression and anxiety symptoms are also manifested in learning and decision-making deficits. However, the specific cognitive mechanisms that are common to both disorders, as well as those that distinguish them, remain poorly understood. Here, we propose reinforcement learning (RL) as a unifying computational framework to disentangle the shared and distinct cognitive processes underlying depression and anxiety. Methods : We adopted a probabilistic instrumental learning task in which subjects repeatedly chose between alternative options to earn rewards (Gain) or avoid losses (Loss) in two experiment (n=190 in experiment 1, n=361 in experiment 2). Classic psychiatric questionnaires about depression and anxiety traits were collected from participants. Results : We discovered a dissociation where depression traits correlated negatively with learning rates, while anxiety traits showed the opposite pattern in two separate experiments. Experiment 2 further identified transdiagnostic latent factors of depression and anxiety traits that drove the dissociation of depression and anxiety traits on learning rates. Specifically, somatic symptoms and anhedonia were found to be the main contributors to the negative correlation between learning and depression traits. In contrast, cognitive symptoms and negative affects showed a positive correlation with learning rates. Conclusions : The dissociation between transdoagnostic factors may reflect a trade-off wherein excessive internal focus diminishes the capacity for external information processing. Together, our findings demonstrate how the transdiagnostic approach under a unified computational framework can elucidate distinct cognitive profiles of depression and anxiety. Transdiagnostic latent factors Reinforcement learning Depression Anxiety Computational psychiatry Full Text Additional Declarations No competing interests reported. Supplementary Files Supplementary.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 05 May, 2026 Reviews received at journal 04 May, 2026 Reviews received at journal 13 Apr, 2026 Reviewers agreed at journal 07 Apr, 2026 Reviewers agreed at journal 23 Mar, 2026 Reviewers agreed at journal 15 Feb, 2026 Reviewers agreed at journal 05 Jan, 2026 Reviewers agreed at journal 28 Dec, 2025 Reviewers invited by journal 12 Dec, 2025 Editor invited by journal 11 Dec, 2025 Editor assigned by journal 10 Dec, 2025 Submission checks completed at journal 10 Dec, 2025 First submitted to journal 08 Dec, 2025 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-8307305","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":561073958,"identity":"650292a7-a205-4902-9ec9-94a7c27af501","order_by":0,"name":"Xinru Huang","email":"","orcid":"","institution":"Peking University","correspondingAuthor":false,"prefix":"","firstName":"Xinru","middleName":"","lastName":"Huang","suffix":""},{"id":561073959,"identity":"5a135b52-7b61-4cae-8cde-f91a1b77ca71","order_by":1,"name":"Yinmei Ni","email":"","orcid":"","institution":"Peking 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While mainly characterized as mood dysregulation, depression and anxiety symptoms are also manifested in learning and decision-making deficits. However, the specific cognitive mechanisms that are common to both disorders, as well as those that distinguish them, remain poorly understood. Here, we propose reinforcement learning (RL) as a unifying computational framework to disentangle the shared and distinct cognitive processes underlying depression and anxiety.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: We adopted a probabilistic instrumental learning task in which subjects repeatedly chose between alternative options to earn rewards (Gain) or avoid losses (Loss) in two experiment (n=190 in experiment 1, n=361 in experiment 2). Classic psychiatric questionnaires about depression and anxiety traits were collected from participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: We discovered a dissociation where depression traits correlated negatively with learning rates, while anxiety traits showed the opposite pattern in two separate experiments. Experiment 2 further identified transdiagnostic latent factors of depression and anxiety traits that drove the dissociation of depression and anxiety traits on learning rates. Specifically, somatic symptoms and anhedonia were found to be the main contributors to the negative correlation between learning and depression traits. In contrast, cognitive symptoms and negative affects showed a positive correlation with learning rates.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: The dissociation between transdoagnostic factors may reflect a trade-off wherein excessive internal focus diminishes the capacity for external information processing. Together, our findings demonstrate how the transdiagnostic approach under a unified computational framework can elucidate distinct cognitive profiles of depression and anxiety.\u003c/p\u003e","manuscriptTitle":"Transdiagnostic latent factors dissociating depression and anxiety through reinforcement learning","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-17 05:09:52","doi":"10.21203/rs.3.rs-8307305/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-05T05:20:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T07:18:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-13T19:01:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"316917248087925302419438915648600654232","date":"2026-04-07T08:55:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42391166158135124928530091830077260277","date":"2026-03-23T07:30:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"213999873147658922027196138719239541309","date":"2026-02-15T11:05:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"109472204848601014374005418348068437846","date":"2026-01-05T17:26:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"270810263003241894245036167605038904352","date":"2025-12-29T00:11:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-12T07:28:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-11T18:00:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-10T11:52:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-10T11:51:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2025-12-08T11:30:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5d2de94f-0f5d-4d7e-b581-8a303d1d120b","owner":[],"postedDate":"December 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T05:25:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-17 05:09:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8307305","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8307305","identity":"rs-8307305","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}