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dc.contributor.authorSommerlade, Linda
dc.contributor.authorThiel, Marco
dc.contributor.authorMader, Malenka
dc.contributor.authorMader, Wolfgang
dc.contributor.authorTimmer, Jens
dc.contributor.authorPlatt, Bettina
dc.contributor.authorSchelter, Bjoern
dc.date.accessioned2015-03-18T10:27:00Z
dc.date.available2015-03-18T10:27:00Z
dc.date.issued2015-01-15
dc.identifier48635780
dc.identifier262962e6-205d-492b-92fe-0f1c3a035f28
dc.identifier000347664400006
dc.identifier84908350937
dc.identifier.citationSommerlade , L , Thiel , M , Mader , M , Mader , W , Timmer , J , Platt , B & Schelter , B 2015 , ' Assessing the strength of directed influences among neural signals : An approach to noisy data ' , Journal of Neuroscience Methods , vol. 239 , pp. 47-64 . https://doi.org/10.1016/j.jneumeth.2014.09.007en
dc.identifier.issn0165-0270
dc.identifier.otherORCID: /0000-0002-7852-0749/work/76976860
dc.identifier.urihttp://hdl.handle.net/2164/4326
dc.descriptionAcknowledgements This work was supported by the German Science Foundation (Ti315/4-2), the German Federal Ministry of Education and Research (BMBF grant 01GQ0420), and the Excellence Initiative of the German Federal and State Governments. B.S. is indebted to the Kosterlitz Centre for the financial support of this research project.en
dc.format.extent18
dc.format.extent445824
dc.language.isoeng
dc.relation.ispartofJournal of Neuroscience Methodsen
dc.subjectGranger-causalityen
dc.subjectObservational noiseen
dc.subjectStatisticsen
dc.subjectExpectation-maximisation algorithmen
dc.subjectKalman filteren
dc.subjectIncomplete data likelihooden
dc.subjectAnalytical covariance matrixen
dc.subjectMultivariate time-seriesen
dc.subjectGranger causalityen
dc.subjectMaximum-likelihooden
dc.subjectLinear-dependenceen
dc.subjectInformation-flowen
dc.subjectCoherenceen
dc.subjectEEGen
dc.subjectFeedbacken
dc.subjectIntervalen
dc.subjectAlgorithmen
dc.subjectRC0321 Neuroscience. Biological psychiatry. Neuropsychiatryen
dc.subjectSupplementary Dataen
dc.subject.lccRC0321en
dc.titleAssessing the strength of directed influences among neural signals : An approach to noisy dataen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Physicsen
dc.contributor.institutionUniversity of Aberdeen.Environment and Food Securityen
dc.contributor.institutionUniversity of Aberdeen.Institute for Complex Systems and Mathematical Biology (ICSMB)en
dc.contributor.institutionUniversity of Aberdeen.Medical Sciencesen
dc.description.statusPeer revieweden
dc.identifier.doi10.1016/j.jneumeth.2014.09.007


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