TY - JOUR
T1 - Estimating parametric line-source models with electroencephalography
AU - Cao, Nannan
AU - Yetik, Imam Şamil
AU - Nehorai, Arye
AU - Muravchik, Carlos H.
AU - Haueisen, Jens
N1 - Funding Information:
Manuscript received July 20, 2005; revised May 6, 2006. This work was supported by the National Science Foundation (NSF) under Grant CCR-0105334. Asterisk indicates corresponding author. *N. Cao is with the Department of Electrical and Systems Engineering, Washington University in St. Louis, MO 63130 USA. She is also with the Bryan 201, Campus Box 1127, 1 Brookings Drive, St. Louis, MO 63130 USA (e-mail: [email protected]). ˙.S¸. Yetik is with the Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616 USA. A. Nehorai is with the Department of Electrical and Systems Engineering, Washington University in St. Louis, MO 63130 USA. C. H. Muravchik is with the Departamento de Electrotecnia, Facultad de In-genieria, Universidad Nacional de La Plata, Argentina. J. Haueisen is with the Neurological University Hospital, Jena D-07743, Germany and also with the Institute of Biomedical Engineering and Informatics, TU-Ilmenau, Ilmenau, Germany. Digital Object Identifier 10.1109/TBME.2006.880885
PY - 2006/11
Y1 - 2006/11
N2 - We develop three parametric models for electroencephalography (EEG) to estimate current sources that are spatially distributed on a line. We assume a realistic head model and solve the EEG forward problem using the boundary element method (BEM). We present the models with increasing degrees of freedom, provide the forward solutions, and derive the maximum-likelihood estimates as well as Cramér-Rao bounds of the unknown source parameters. A series of experiments are conducted to evaluate the applicability of the proposed models. We use numerical examples to demonstrate the usefulness of our line-source models in estimating extended sources. We also apply our models to the real EEG data of N20 response that is known to have an extended source. We observe that the line-source models explain the N20 measurements better than the dipole model.
AB - We develop three parametric models for electroencephalography (EEG) to estimate current sources that are spatially distributed on a line. We assume a realistic head model and solve the EEG forward problem using the boundary element method (BEM). We present the models with increasing degrees of freedom, provide the forward solutions, and derive the maximum-likelihood estimates as well as Cramér-Rao bounds of the unknown source parameters. A series of experiments are conducted to evaluate the applicability of the proposed models. We use numerical examples to demonstrate the usefulness of our line-source models in estimating extended sources. We also apply our models to the real EEG data of N20 response that is known to have an extended source. We observe that the line-source models explain the N20 measurements better than the dipole model.
KW - Cramér-Rao bounds
KW - EEG
KW - Extended source modeling
UR - https://www.scopus.com/pages/publications/33750367499
U2 - 10.1109/TBME.2006.880885
DO - 10.1109/TBME.2006.880885
M3 - Article
C2 - 17073320
AN - SCOPUS:33750367499
SN - 0018-9294
VL - 53
SP - 2156
EP - 2165
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
IS - 11
ER -