Kalman filter-based time-varying cortical connectivity analysis of newborn EEG

Show simple item record

Author Omidvarnia, A.H. en_US
Author Mesbah, M. en_US
Author Khlif, M.S. en_US
Author O'Toole, J.M. en_US
Author Colditz, P. en_US
Author Boashash, B. en_US
Available date 2012-06-18T08:28:35Z en_US
Publication Date 2011 en_US
Citation A. H. Omidvarnia, M. Mesbah, M. S. Khlif, J. M. O'Toole, P. B. Colditz, and B. Boashash, "Kalman filter-based time-varying cortical connectivity analysis of newborn EEG," in Proc. of IEEE 2011 Annual International Conference of Engineering in Medicine and Biology Society,EMBC, 2011, pp. 1423-1426 en_US
URI http://dx.doi.org/10.1109/iembs.2011.6090335 en_US
URI http://hdl.handle.net/10576/10847 en_US
Description This paper presents a time-varying cortical connectivity analysis for to a source localization approach within the inner layers of the newborn brain. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). en_US
Abstract Multivariate Granger causality in the timefrequency domain as a representation of time-varying cortical connectivity in the brain has been investigated for the adult case. This is, however, not the case in newborns as the nature of the transient changes in the newborn EEG is different from that of adults. This paper aims to evaluate the performance of the time-varying versions of the two popular Granger causality measures, namely Partial Directed Coherence (PDC) and direct Directed Transfer Function (dDTF). The parameters of the time-varying AR, that models the inter-channel interactions, are estimated using Dual Extended Kalman Filter (DEKF) as it accounts for both non-stationarity and non-linearity behaviors of the EEG. Using simulated data, we show that fast changing cortical connectivity between channels can be measured more accurately using the time-varying PDC. The performance of the time-varying PDC is also tested on a neonatal EEG exhibiting seizure. en_US
Language en en_US
Publisher IEEE en_US
Subject DEKF en_US
Subject EEG nonlinearity behavior en_US
Subject EEG nonstationarity behavior en_US
Subject Granger causality measures en_US
Subject dDTF en_US
Subject directed transfer function en_US
Subject dual extended Kalman filter en_US
Subject fast changing cortical connectivity en_US
Subject interchannel interactions en_US
Subject neonatal EEG exhibiting seizure en_US
Subject newborn EEG en_US
Subject partial directed coherence en_US
Subject time varying AR parameters en_US
Subject time varying PDC en_US
Subject time varying cortical connectivity analysis en_US
Subject time-frequency domain multivariate Granger causality en_US
Title Kalman filter-based time-varying cortical connectivity analysis of newborn EEG en_US
Type Conference Paper en_US

Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record