TY - GEN
T1 - Analysis of the time-varying cortical neural connectivity in the newborn EEG
T2 - 7th International Workshop on Systems, Signal Processing and their Applications, WoSSPA 2011
AU - Omidvarnia, Amir
AU - Mesbah, Mostefa
AU - O'Toole, John M.
AU - Colditz, Paul
AU - Boashash, Boualem
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
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U2 - 10.1109/WOSSPA.2011.5931445
DO - 10.1109/WOSSPA.2011.5931445
M3 - Conference contribution
AN - SCOPUS:79960928407
SN - 9781457706905
T3 - 7th International Workshop on Systems, Signal Processing and their Applications, WoSSPA 2011
SP - 179
EP - 182
BT - 7th International Workshop on Systems, Signal Processing and their Applications, WoSSPA 2011
Y2 - 9 May 2011 through 11 May 2011
ER -