Independent component analysis of magnetoencephalography data

Author

Fortuna, L. ; Bucolo, M. ; Frasca, M. ; Rosa, M. La ; Shannahoff-Khalsa, D.S. ; Schult, R.L. ; Wright, Jon A.

Author_Institution

Dipt. Elettrico Elettronico e Sistemistico, Universita degli Studi di Catania, Italy

Volume

2

fYear

2001

fDate

2001

Firstpage

1981

Abstract

Independent Component Analysis (ICA) is applied to the Magnetoencephalography (MEG) data of a subject performing a yoga breathing exercise specific for the treatment of obsessive compulsive disorder. The spatio-temporal dynamics observed using a whole-head 148-channel MEG instrument are split into the fundamental modes, thus isolating separate brain activity signals. Experiments were performed on data from different brain regions. Spectral analysis of the more significant signals are presented. Moreover a new tool is developed as a Matlab toolbox to support the scientist both in the visualization and computation phases.

Keywords

magnetoencephalography; medical signal processing; spectral analysis; Matlab toolbox; brain regions; computation phase; fundamental modes; obsessive compulsive disorder treatment; separate brain activity signals isolation; spatio-temporal dynamics; visualization phase; whole-head 148-channel MEG instrument; yoga breathing exercise; Independent component analysis; Instruments; Magnetic analysis; Magnetic field measurement; Magnetic fields; Magnetic separation; Magnetoencephalography; SQUID magnetometers; Spectral analysis; Superconducting coils;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE

ISSN

1094-687X

Print_ISBN

0-7803-7211-5

Type

conf

DOI

10.1109/IEMBS.2001.1020618

Filename

1020618