DocumentCode :
3728220
Title :
Application of Extended Multivariate Modeling for Information Flow Analysis of Event Related Responses
Author :
Imali T. Hettiarachchi;Shady Mohamed;Saeid Nahavandi;Sofia Nahavandi
Author_Institution :
Centre for Intell. Syst. Res., Deakin Univ., Geelong, VIC, Australia
fYear :
2015
Firstpage :
1845
Lastpage :
1851
Abstract :
Event related potential (ERP) analysis is one of the most widely used methods in cognitive neuroscience research to study the physiological correlates of sensory, perceptual and cognitive activity associated with processing information. To this end information flow or dynamic effective connectivity analysis is a vital technique to understand the higher cognitive processing under different events. In this paper we present a Granger causality (GC)-based connectivity estimation applied to ERP data analysis. In contrast to the generally used strictly causal multivariate autoregressive model, we use an extended multivariate autoregressive model (eMVAR) which also accounts for any instantaneous interaction among variables under consideration. The experimental data used in the paper is based on a single subject data set for erroneous button press response from a two-back with feedback continuous performance task (CPT). In order to demonstrate the feasibility of application of eMVAR models in source space connectivity studies, we use cortical source time series data estimated using blind source separation or independent component analysis (ICA) for this data set.
Keywords :
"Brain modeling","Electroencephalography","Adaptation models","Data models","Mathematical model","Analytical models","Frequency measurement"
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/SMC.2015.323
Filename :
7379455
Link To Document :
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