Connectivity estimation of three parametric methods on simulated electroencephalogram signals

Author

Velez-Perez, Hugo ; Louis-Dorr, Valerie ; Ranta, Radu ; Dufaut, Michel

Author_Institution

Research Centre for Automatic Control (CRANUMR 7039), National Center for Scientific Research (CNRS), Nancy University, 2 Avenue de la For?t de Haye, 54516, Vandoeuvre l?s Nancy, France

fYear

2008

fDate

20-25 Aug. 2008

Firstpage

2606

Lastpage

2609

Abstract

The global framework of this paper is the connectivity estimation in multichannel electroencephalogram (EEG) recordings, modeled as multidimensional autoregressive (AR) processes. The coherence, directed transfer function and partial directed coherence functions are evaluated on two simulated EEG signals for their later application on real EEG recordings. The results were evaluated computing the relative error and a second proposed performance criterion (η) based on the entropy of the estimated connectivity matrix.

Keywords

Brain modeling; Coherence; Computational modeling; Covariance matrix; Electroencephalography; Frequency domain analysis; Multidimensional signal processing; Scalp; Signal processing; Transfer functions; Analysis of Variance; Automatic Data Processing; Brain Mapping; Cerebral Cortex; Computer Simulation; Electroencephalography; Humans; Magnetic Resonance Imaging; Models, Neurological; Models, Statistical; Neural Pathways; Regression Analysis; Reproducibility of Results; Seizures; Signal Processing, Computer-Assisted;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE

Conference_Location

Vancouver, BC

ISSN

1557-170X

Print_ISBN

978-1-4244-1814-5

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2008.4649734

Filename

4649734