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AuthorOmidvarnia, A
AuthorMesbah, M
AuthorO'Toole, J.M.
AuthorColditz, P
AuthorBoashash, B
Available date2011-09-17T09:37:45Z
Publication Date2011-05
Publication Name2011 7th International Workshop on Systems, Signal Processing and their Applications (WOSSPA)
CitationOmidvarnia, A.; Mesbah, M.; O'Toole, J.M.; Colditz, P.; Boashash, B., "Analysis of the time-varying cortical neural connectivity in the newborn EEG: A time-frequency approach," Systems, Signal Processing and their Applications (WOSSPA), 2011 7th International Workshop on , vol., no., pp.179,182, 9-11 May 2011
DescriptionThis paper aims to assess and compare the performance of two brain connectivity measures based on time-varying multivariate AR modelling for newborn EEG analysis.
AbstractRelationships between cortical neural recordings as a representation of functional connectivity between cortical brain regions were quantified using different time-frequency criteria. Among these, Partial Directed Coherence (PDC) and Directed Transfer Function (DTF) and their extensions have found wide acceptance. This paper aims to assess and compare the performance of these two connectivity measures that are based on time-varying multivariate AR modeling. The time-varying parameters of the AR model are estimated using an Adaptive AR modeling (AAR) approach and a short-time based stationary approach. The performance of these two approaches is compared using both simulated signal and a multichannel newborn EEG recording. The results show that the time-varying PDC outperforms the time-varying DTF measure. The results also point to the limitation of the AAR algorithm in tracking rapid parameter changes and the drawback of the short-time approach in providing high resolution time-frequency coherence functions. However, it can be demonstrated that time-varying MVAR representations of the cortical connectivity will potentially lead to better understanding of non-symmetric relations between EEG channels.
SubjectAdaptation model
Brain modeling
Kalman filters
Time frequency analysis
autoregressive processes
medical signal processing
time-frequency analysis
adaptive AR modeling
cortical brain region
cortical neural recording
directed transfer function
high resolution time-frequency coherence function
multichannel newborn EEG recording
multivariate autoregressive model
partial directed coherence
short-time based stationary approach
time-varying DTF
time-varying MVAR representation
time-varying PDC
time-varying cortical neural connectivity analysis
time-varying multivariate AR modeling
Brain connectivity
newborn EEG
TitleAnalysis of the time-varying cortical neural connectivity in the newborn EEG: A time-frequency approach
TypeConference Paper

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