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dc.contributor.authorBosl, William J.en_US
dc.contributor.authorTager-Flusberg, Helenen_US
dc.contributor.authorNelson, Charles A.en_US
dc.date.accessioned2019-02-06T18:59:37Z
dc.date.available2019-02-06T18:59:37Z
dc.date.issued2018-05-01
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000431114200007&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=6e74115fe3da270499c3d65c9b17d654
dc.identifier.citationWilliam J Bosl, Helen Tager-Flusberg, Charles A Nelson. 2018. "EEG Analytics for Early Detection of Autism Spectrum Disorder: A data-driven approach." SCIENTIFIC REPORTS, Volume 8, pp. ? - ? (20). https://doi.org/10.1038/s41598-018-24318-x
dc.identifier.issn2045-2322
dc.identifier.urihttps://hdl.handle.net/2144/33286
dc.description.abstractAutism spectrum disorder (ASD) is a complex and heterogeneous disorder, diagnosed on the basis of behavioral symptoms during the second year of life or later. Finding scalable biomarkers for early detection is challenging because of the variability in presentation of the disorder and the need for simple measurements that could be implemented routinely during well-baby checkups. EEG is a relatively easy-to-use, low cost brain measurement tool that is being increasingly explored as a potential clinical tool for monitoring atypical brain development. EEG measurements were collected from 99 infants with an older sibling diagnosed with ASD, and 89 low risk controls, beginning at 3 months of age and continuing until 36 months of age. Nonlinear features were computed from EEG signals and used as input to statistical learning methods. Prediction of the clinical diagnostic outcome of ASD or not ASD was highly accurate when using EEG measurements from as early as 3 months of age. Specificity, sensitivity and PPV were high, exceeding 95% at some ages. Prediction of ADOS calibrated severity scores for all infants in the study using only EEG data taken as early as 3 months of age was strongly correlated with the actual measured scores. This suggests that useful digital biomarkers might be extracted from EEG measurements.en_US
dc.description.sponsorshipThis research was supported by National Institute of Mental Health (NIMH) grant R21 MH 093753 (to WJB), National Institute on Deafness and Other Communication Disorders (NIDCD) grant R21 DC08647 (to HTF), NIDCD grant R01 DC 10290 (to HTF and CAN) and a grant from the Simons Foundation (to CAN, HTF, and WJB). We are especially grateful to the staff and students who worked on the study and to the families who participated. (R21 MH 093753 - National Institute of Mental Health (NIMH); R21 DC08647 - National Institute on Deafness and Other Communication Disorders (NIDCD); R01 DC 10290 - NIDCD; Simons Foundation)en_US
dc.format.extent20 p.en_US
dc.languageEnglish
dc.language.isoen_US
dc.publisherNature Publishing Groupen_US
dc.relation.ispartofScientific Reports
dc.rightsAttribution 4.0 Internationalen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectScience & technologyen_US
dc.subjectMultidisciplinary sciencesen_US
dc.subjectInfants at-risken_US
dc.subjectLanguage impairmenten_US
dc.subjectJoint attentionen_US
dc.subjectChildrenen_US
dc.subjectBrainen_US
dc.subjectClassificationen_US
dc.subjectParentsen_US
dc.subjectLateralizationen_US
dc.subjectMechanismsen_US
dc.subjectComplexityen_US
dc.titleEEG analytics for early detection of autism spectrum disorder: a data-driven approachen_US
dc.typeArticleen_US
dc.description.versionPublished versionen_US
dc.identifier.doi10.1038/s41598-018-24318-x
pubs.elements-sourceweb-of-scienceen_US
pubs.notesEmbargo: No embargoen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Psychological & Brain Sciencesen_US
pubs.publication-statusPublisheden_US
dc.identifier.orcid0000-0002-8768-5414 (Tager-Flusberg, Helen)


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International