Analysis of the time-varying cortical neural connectivity in the newborn EEG: A time-frequency approach

Omidvarnia, Amir, Mesbah, Mostefa, O’Toole, John M., Colditz, Paul and Boashash, Boualem (2011). Analysis of the time-varying cortical neural connectivity in the newborn EEG: A time-frequency approach. In: 7th International Workshop on Systems, Signal Processing and their Applications. 7th International Workshop on Systems, Signal Processing and their Applications, WoSSPA 2011, Tipaza, Algeria, (179-182). 9 - 11 May 2011. doi:10.1109/WOSSPA.2011.5931445

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Author Omidvarnia, Amir
Mesbah, Mostefa
O’Toole, John M.
Colditz, Paul
Boashash, Boualem
Title of paper Analysis of the time-varying cortical neural connectivity in the newborn EEG: A time-frequency approach
Conference name 7th International Workshop on Systems, Signal Processing and their Applications, WoSSPA 2011
Conference location Tipaza, Algeria
Conference dates 9 - 11 May 2011
Proceedings title 7th International Workshop on Systems, Signal Processing and their Applications
Journal name 7th International Workshop on Systems, Signal Processing and their Applications, WoSSPA 2011
Place of Publication Piscataway, NJ, USA
Publisher IEEE
Publication Year 2011
Sub-type Fully published paper
DOI 10.1109/WOSSPA.2011.5931445
ISBN 9781457706899
Start page 179
End page 182
Total pages 4
Language eng
Abstract/Summary Relationships 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.
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Thu, 08 Sep 2011, 21:46:32 EST by Matthew Lamb on behalf of School of Medicine