NDLI: The choice of the source space and the Laplacian matrix in LORETA and the spatio-temporal Kalman filter EEG inverse methods

Content Provider	IEEE Xplore Digital Library
Author	Habboush, N. Hamid, L. Japaridze, N. Wiegand, G. Heute, U. Stephani, U. Galka, A. Siniatchkin, M.
Copyright Year	2015
Description	Author affiliation: Dept. of Neuropediatrics, Christian-Albrechts-Univ., Kiel, Germany (Japaridze, N.) \|\| Christian-Albrechts-Univ. of Kiel, Kiel, Germany (Stephani, U.) \|\| Dept. of Med. Psychol. & Med. Sociology, Univ. of Kiel, Kiel, Germany (Habboush, N.; Hamid, L.; Galka, A.; Siniatchkin, M.) \|\| Dept. of Neuropediatrics, Univ. of Kiel, Kiel, Germany (Wiegand, G.) \|\| Ulrich Univ. of Kiel, Kiel, Germany (Heute, U.)
Abstract	The discretization of the brain and the definition of the Laplacian matrix influence the results of methods based on spatial and spatio-temporal smoothness, since the Laplacian operator is used to define the smoothness based on the neighborhood of each grid point. In this paper, the results of low resolution electromagnetic tomography (LORETA) and the spatiotemporal Kalman filter (STKF) are computed using, first, a greymatter source space with the standard definition of the Laplacian matrix and, second, using a whole-brain source space and a modified definition of the Laplacian matrix. Electroencephalographic (EEG) source imaging results of five inter-ictal spikes from a pre-surgical patient with epilepsy are used to validate the two aforementioned approaches. The results using the whole-brain source space and the modified definition of the Laplacian matrix were concentrated in a single source activation, stable, and concordant with the location of the focal cortical dysplasia (FCD) in the patient's brain compared with the results which use a grey-matter grid and the classical definition of the Laplacian matrix. This proof-of-concept study demonstrates a substantial improvement of source localization with both LORETA and STKF and constitutes a basis for further research in a large population of patients with epilepsy.
Starting Page	2745
Ending Page	2749
File Size	883429
Page Count	5
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7318960
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Laplace equations Electroencephalography Brain modeling Covariance matrices Magnetic resonance imaging Inverse problems Epilepsy
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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