Iterative decomposition of visuomotor, device and cognitive variance in large scale online cognitive test data

preprint OA: gold CC-BY-4.0
📄 Open PDF Full text JSON View at publisher

Abstract

Abstract Online cognitive assessment technologies are gaining traction as scalable and cost-effective alternatives to traditional supervised testing. However, variability in peoples’ home devices, and their visual and motor abilities, confound the cognitive specificity of online task performance scores. To address these limitations, we develop IDoCT (Iterative Decomposition of Cognitive Tasks), a novel method for estimating cognitive abilities and trial-difficulty scales from task performance timecourses in a data-driven manner while accounting for device and visuomotor latencies, and speed-accuracy trade-offs. IDoCT can operate with any computerised task that manipulates cognitive difficulty across trials. Using data from 388,757 adults across 12 online cognitive tasks, we show that IDoCT successfully dissociates cognitive abilities from visuomotor response latencies. The resultant cognitive scores exhibit superior psychometric structure and associations with demographic factors while being insensitive to testing device. We propose that IDoCT can enhance the precision of online cognitive assessments for diverse clinical and research applications.
Full text 12,592 characters · extracted from preprint-html · click to expand
Iterative decomposition of visuomotor, device and cognitive variance in large scale online cognitive test data | 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 Iterative decomposition of visuomotor, device and cognitive variance in large scale online cognitive test data Valentina Giunchiglia, Dragos Gruia, Annalaura Lerede, William Trender, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2972434/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 Online cognitive assessment technologies are gaining traction as scalable and cost-effective alternatives to traditional supervised testing. However, variability in peoples’ home devices, and their visual and motor abilities, confound the cognitive specificity of online task performance scores. To address these limitations, we develop IDoCT (Iterative Decomposition of Cognitive Tasks), a novel method for estimating cognitive abilities and trial-difficulty scales from task performance timecourses in a data-driven manner while accounting for device and visuomotor latencies, and speed-accuracy trade-offs. IDoCT can operate with any computerised task that manipulates cognitive difficulty across trials. Using data from 388,757 adults across 12 online cognitive tasks, we show that IDoCT successfully dissociates cognitive abilities from visuomotor response latencies. The resultant cognitive scores exhibit superior psychometric structure and associations with demographic factors while being insensitive to testing device. We propose that IDoCT can enhance the precision of online cognitive assessments for diverse clinical and research applications. Biological sciences/Neuroscience/Cognitive neuroscience/Intelligence Biological sciences/Neuroscience/Cognitive neuroscience Biological sciences/Neuroscience/Computational neuroscience Full Text Additional Declarations Yes there is potential Competing Interest. A.H. is owner and founder of Future Cognition Ltd. and H2 Cognitive Designs Ltd., which develop custom cognitive assessment software for other university-based research groups. P.J.H. is the owner and co-founder of H2 Cognitive Designs Ltd. The authors report no other conflicts of interest. Supplementary Files SupplementaryMaterial1.pdf 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-2972434","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":203167653,"identity":"c24bf248-4a63-48d1-b930-9c16a1a450dd","order_by":0,"name":"Valentina Giunchiglia","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-2165-7840","institution":"Imperial College London","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Valentina","middleName":"","lastName":"Giunchiglia","suffix":""},{"id":203167648,"identity":"e22bac17-8e67-4816-9f3f-20de796d40f9","order_by":1,"name":"Dragos Gruia","email":"","orcid":"","institution":"Imperial College London","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dragos","middleName":"","lastName":"Gruia","suffix":""},{"id":203167649,"identity":"20d8c1ba-38cf-465b-a13f-f2604f2db183","order_by":2,"name":"Annalaura Lerede","email":"","orcid":"","institution":"Imperial College London","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Annalaura","middleName":"","lastName":"Lerede","suffix":""},{"id":203167650,"identity":"76d6be42-ea1d-416d-8631-6370a4dff25e","order_by":3,"name":"William Trender","email":"","orcid":"https://orcid.org/0000-0003-3947-5532","institution":"Imperial College London","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"William","middleName":"","lastName":"Trender","suffix":""},{"id":203167651,"identity":"d2f18aff-9a65-404d-b2e4-b111bd47cb72","order_by":4,"name":"Peter Hellyer","email":"","orcid":"","institution":"King's College London","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Hellyer","suffix":""},{"id":203167652,"identity":"6456663c-775f-4b77-ba78-a30108fcdddf","order_by":5,"name":"Adam Hampshire","email":"","orcid":"","institution":"Imperial College London","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Adam","middleName":"","lastName":"Hampshire","suffix":""}],"badges":[],"createdAt":"2023-05-23 15:52:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2972434/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2972434/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":37822030,"identity":"67810fee-0b5e-4eed-81aa-a3e8615f9c40","added_by":"auto","created_at":"2023-06-01 08:01:23","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2477790,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2972434/v1_covered_8bb870ad-1485-4021-b1ef-dfaad6c7f22b.pdf"},{"id":37412532,"identity":"13494b39-2484-4611-bcff-3e15ba53c909","added_by":"auto","created_at":"2023-05-24 03:46:49","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":526663,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementaryMaterial1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2972434/v1/eed8446477d6763850f282ee.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nA.H. is owner and founder of Future Cognition Ltd. and H2 Cognitive Designs Ltd., which develop custom cognitive assessment software for other university-based research groups. P.J.H. is the owner and co-founder of H2 Cognitive Designs Ltd. The authors report no other conflicts of interest.","formattedTitle":"Iterative decomposition of visuomotor, device and cognitive variance in large scale online cognitive test data","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-2972434/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2972434/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Online cognitive assessment technologies are gaining traction as scalable and cost-effective alternatives to traditional supervised testing. However, variability in peoples’ home devices, and their visual and motor abilities, confound the cognitive specificity of online task performance scores. To address these limitations, we develop IDoCT (Iterative Decomposition of Cognitive Tasks), a novel method for estimating cognitive abilities and trial-difficulty scales from task performance timecourses in a data-driven manner while accounting for device and visuomotor latencies, and speed-accuracy trade-offs. IDoCT can operate with any computerised task that manipulates cognitive difficulty across trials. Using data from 388,757 adults across 12 online cognitive tasks, we show that IDoCT successfully dissociates cognitive abilities from visuomotor response latencies. The resultant cognitive scores exhibit superior psychometric structure and associations with demographic factors while being insensitive to testing device. We propose that IDoCT can enhance the precision of online cognitive assessments for diverse clinical and research applications.","manuscriptTitle":"Iterative decomposition of visuomotor, device and cognitive variance in large scale online cognitive test data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-05-24 03:46:44","doi":"10.21203/rs.3.rs-2972434/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"b77bb5e5-c773-4ac0-93b2-6b20335cde6a","owner":[],"postedDate":"May 24th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":21761521,"name":"Biological sciences/Neuroscience/Cognitive neuroscience/Intelligence"},{"id":21761522,"name":"Biological sciences/Neuroscience/Cognitive neuroscience"},{"id":21761523,"name":"Biological sciences/Neuroscience/Computational neuroscience"}],"tags":[],"updatedAt":"2023-06-01T08:01:02+00:00","versionOfRecord":[],"versionCreatedAt":"2023-05-24 03:46:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2972434","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2972434","identity":"rs-2972434","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-05-21T05:10:58.409756+00:00
License: CC-BY-4.0