A marginalised Markov Chain Monte Carlo approach for model based analysis of EEG data Hettiarachchi, Imali, Mohamed, Shady and Nahavandi, Saeid 2012, A marginalised Markov Chain Monte Carlo approach for model based analysis of EEG data, in ISBI 2012 : From Nano to Macro : Proceedings of the 9th IEEE International Symposium on Biomedical Imaging, IEEE, Los Alamitos, Calif., pp. 1539-1542, doi: 10.1109/ISBI.2012.6235866. Attached Files Name Description MIMEType Size Downloads Title A marginalised Markov Chain Monte Carlo approach for model based analysis of EEG data Author(s) Hettiarachchi, Imali orcid.org/0000-0002-4220-0970 Mohamed, Shady orcid.org/0000-0002-8851-1635 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Conference name IEEE International Symposium on Biomedical Imaging (9th : 2012 : Barcelona, Spain) Conference location Barcelona, Spain Conference dates 2-5 May 2012 Title of proceedings ISBI 2012 : From Nano to Macro : Proceedings of the 9th IEEE International Symposium on Biomedical Imaging Editor(s) [Unknown] Publication date 2012 Conference series IEEE International Symposium on Biomedical Imaging Start page 1539 End page 1542 Total pages 4 Publisher IEEE Place of publication Los Alamitos, Calif. Keyword(s) Bayesian methods electroencephalography nonlinear dynamical systems parameter estimation particle filter Summary The work presented in this paper focuses on fitting of a neural mass model to EEG data. Neurophysiology inspired mathematical models were developed for simulating brain's electrical activity imaged through Electroencephalography (EEG) more than three decades ago. At the present well informative models which even describe the functional integration of cortical regions also exists. However, a very limited amount of work is reported in literature on the subject of model fitting to actual EEG data. Here, we present a Bayesian approach for parameter estimation of the EEG model via a marginalized Markov Chain Monte Carlo (MCMC) approach. ISBN 9781457718571 ISSN 1945-7928 Language eng DOI 10.1109/ISBI.2012.6235866 Field of Research 090399 Biomedical Engineering not elsewhere classified Socio Economic Objective 970109 Expanding Knowledge in Engineering HERDC Research category E1 Full written paper - refereed Copyright notice ©2012, IEEE Persistent URL http://hdl.handle.net/10536/DRO/DU:30049201 Document type: Conference Paper Collections: Institute for Intelligent Systems Research and Innovation (IISRI) GTP Research Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 01 Nov 2012, 13:09:34 EST Mon, 05 Nov 2012, 08:07:56 EST Mon, 05 Nov 2012, 08:10:32 EST Thu, 08 Nov 2012, 08:12:09 EST Wed, 14 Nov 2012, 12:56:06 EST Wed, 14 Nov 2012, 13:02:04 EST Fri, 24 May 2013, 13:05:38 EST Mon, 27 May 2013, 08:40:51 EST Fri, 06 Feb 2015, 11:03:27 EST Wed, 14 Oct 2015, 13:21:20 EST Filtered Full Citation counts:   Cited 6 times in TR Web of Science Cited 9 times in Scopus Search Google Scholar Access Statistics: 667 Abstract Views, 7 File Downloads  -  Detailed Statistics Created: Thu, 01 Nov 2012, 13:09:34 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.