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Author Omidvarnia, Aen_US
Author Mesbah, Men_US
Author O'Toole, J.M.en_US
Author Colditz, Pen_US
Author Boashash, Ben_US
Available date 2011-09-17T09:37:45Zen_US
Publication Date 2011-05en_US
Publication Name 2011 7th International Workshop on Systems, Signal Processing and their Applications (WOSSPA)
Citation Omidvarnia, 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 2011en_US
ISBN 978-1-4577-0689-9en_US
URI http://hdl.handle.net/10576/10737en_US
URI http://dx.doi.org/10.1109/WOSSPA.2011.5931445
Description This paper aims to assess and compare the performance of two brain connectivity measures based on time-varying multivariate AR modelling for newborn EEG analysis.en_US
Abstract 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.en_US
Language enen_US
Publisher IEEEen_US
Subject Adaptation modelen_US
Subject Brain modelingen_US
Subject Electroencephalographyen_US
Subject Kalman filtersen_US
Subject Pediatricsen_US
Subject Time frequency analysisen_US
Subject autoregressive processesen_US
Subject electroencephalographyen_US
Subject medical signal processingen_US
Subject neurophysiologyen_US
Subject time-frequency analysisen_US
Subject adaptive AR modelingen_US
Subject cortical brain regionen_US
Subject cortical neural recordingen_US
Subject directed transfer functionen_US
Subject high resolution time-frequency coherence functionen_US
Subject multichannel newborn EEG recordingen_US
Subject multivariate autoregressive modelen_US
Subject partial directed coherenceen_US
Subject short-time based stationary approachen_US
Subject time-varying DTFen_US
Subject time-varying MVAR representationen_US
Subject time-varying PDCen_US
Subject time-varying cortical neural connectivity analysisen_US
Subject time-varying multivariate AR modelingen_US
Subject Brain connectivityen_US
Subject newborn EEGen_US
Title Analysis of the time-varying cortical neural connectivity in the newborn EEG: A time-frequency approachen_US
Type Conference Paperen_US


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