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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.

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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Title A marginalised Markov Chain Monte Carlo approach for model based analysis of EEG data
Author(s) Hettiarachchi, Imali
Mohamed, Shady
Nahavandi, Saeid
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
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2012, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30049201
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