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Application of extended multivariate modeling for information flow analysis of event related responses

conference contribution
posted on 2015-01-01, 00:00 authored by Imali HettiarachchiImali Hettiarachchi, Shady MohamedShady Mohamed, Saeid Nahavandi, S Nahavandi
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.

History

Event

IEEE International Conference on Systems, Man, and Cybernetics (2015 : Hong Kong, China))

Series

Systems Man and Cybernetics Conference Proceedings

Pagination

1845 - 1851

Publisher

IEEE

Location

Hong Kong, China

Place of publication

Piscataway, N.J.

Start date

2015-10-09

End date

2015-10-12

ISSN

1062-922X

Language

eng

Publication classification

E Conference publication; E1 Full written paper - refereed

Copyright notice

2015, IEEE

Title of proceedings

SMC 2015 : Proceedings of 2015 IEEE International Conference on Systems, Man and Cybernetics