Estimating parametric line-source models with electroencephalography

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 freed...

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Detalles Bibliográficos
Autores principales: Cao, Nannan, Yetik, Samil, Nehorai, Arye, Muravchik, Carlos Horacio, Haueisen, Jens
Formato: Articulo
Lenguaje:Inglés
Publicado: 2006
Materias:
Ingeniería Electrónica
Cramér-Rao bounds
EEG
Extended source modeling
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/127106
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-127106
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ingeniería Electrónica
Cramér-Rao bounds
EEG
Extended source modeling
spellingShingle Ingeniería Electrónica
Cramér-Rao bounds
EEG
Extended source modeling
Cao, Nannan
Yetik, Samil
Nehorai, Arye
Muravchik, Carlos Horacio
Haueisen, Jens
Estimating parametric line-source models with electroencephalography
topic_facet Ingeniería Electrónica
Cramér-Rao bounds
EEG
Extended source modeling
description 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 Crameacuter-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
format Articulo
Articulo
author Cao, Nannan
Yetik, Samil
Nehorai, Arye
Muravchik, Carlos Horacio
Haueisen, Jens
author_facet Cao, Nannan
Yetik, Samil
Nehorai, Arye
Muravchik, Carlos Horacio
Haueisen, Jens
author_sort Cao, Nannan
title Estimating parametric line-source models with electroencephalography
title_short Estimating parametric line-source models with electroencephalography
title_full Estimating parametric line-source models with electroencephalography
title_fullStr Estimating parametric line-source models with electroencephalography
title_full_unstemmed Estimating parametric line-source models with electroencephalography
title_sort estimating parametric line-source models with electroencephalography
publishDate 2006
url http://sedici.unlp.edu.ar/handle/10915/127106
work_keys_str_mv AT caonannan estimatingparametriclinesourcemodelswithelectroencephalography
AT yetiksamil estimatingparametriclinesourcemodelswithelectroencephalography
AT nehoraiarye estimatingparametriclinesourcemodelswithelectroencephalography
AT muravchikcarloshoracio estimatingparametriclinesourcemodelswithelectroencephalography
AT haueisenjens estimatingparametriclinesourcemodelswithelectroencephalography
bdutipo_str Repositorios
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