dc.contributor.author | Sommerlade, Linda | |
dc.contributor.author | Thiel, Marco | |
dc.contributor.author | Mader, Malenka | |
dc.contributor.author | Mader, Wolfgang | |
dc.contributor.author | Timmer, Jens | |
dc.contributor.author | Platt, Bettina | |
dc.contributor.author | Schelter, Bjoern | |
dc.date.accessioned | 2015-03-18T10:27:00Z | |
dc.date.available | 2015-03-18T10:27:00Z | |
dc.date.issued | 2015-01-15 | |
dc.identifier | 48635780 | |
dc.identifier | 262962e6-205d-492b-92fe-0f1c3a035f28 | |
dc.identifier | 000347664400006 | |
dc.identifier | 84908350937 | |
dc.identifier.citation | Sommerlade , 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.2014.09.007 | en |
dc.identifier.issn | 0165-0270 | |
dc.identifier.other | ORCID: /0000-0002-7852-0749/work/76976860 | |
dc.identifier.uri | http://hdl.handle.net/2164/4326 | |
dc.description | Acknowledgements 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.extent | 18 | |
dc.format.extent | 445824 | |
dc.language.iso | eng | |
dc.relation.ispartof | Journal of Neuroscience Methods | en |
dc.subject | Granger-causality | en |
dc.subject | Observational noise | en |
dc.subject | Statistics | en |
dc.subject | Expectation-maximisation algorithm | en |
dc.subject | Kalman filter | en |
dc.subject | Incomplete data likelihood | en |
dc.subject | Analytical covariance matrix | en |
dc.subject | Multivariate time-series | en |
dc.subject | Granger causality | en |
dc.subject | Maximum-likelihood | en |
dc.subject | Linear-dependence | en |
dc.subject | Information-flow | en |
dc.subject | Coherence | en |
dc.subject | EEG | en |
dc.subject | Feedback | en |
dc.subject | Interval | en |
dc.subject | Algorithm | en |
dc.subject | RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry | en |
dc.subject | Supplementary Data | en |
dc.subject.lcc | RC0321 | en |
dc.title | Assessing the strength of directed influences among neural signals : An approach to noisy data | en |
dc.type | Journal article | en |
dc.contributor.institution | University of Aberdeen.Physics | en |
dc.contributor.institution | University of Aberdeen.Environment and Food Security | en |
dc.contributor.institution | University of Aberdeen.Institute for Complex Systems and Mathematical Biology (ICSMB) | en |
dc.contributor.institution | University of Aberdeen.Medical Sciences | en |
dc.description.status | Peer reviewed | en |
dc.identifier.doi | 10.1016/j.jneumeth.2014.09.007 | |