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Comparing finite difference forward models using free energy based on multiple sparse priors

Gregor Strobbe, Jose Lopez, Victoria Eugenia Montes Restrepo, Pieter van Mierlo UGent, Hans Hallez and Stefaan Vandenberghe UGent (2012) 18th Annual Meeting of the Organization for Human Brain Mapping, Abstracts. p.181-181
abstract
Due to the ill-posed nature of the EEG source localization problem, the spatial resolution of the reconstructed activity is limited to several centimeters (Baillet, 2001). Advanced forward modeling of the head can contribute to improve the spatial resolution (Hallez, 2007). The boundary element method or BEM is commonly used due to its computation speed. More advanced volume modeling methods, such as finite difference methods or FDM, are computationally more intensive but allow estimating sources inside gray matter (Vanrumste, 2000). FDM also allows to incorporate tissue anisotropy and skull inhomogeneities (Hallez, 2008). Variational Bayesian approaches are getting more popular to solve the reconstruction problem (Friston, 2008 and Wipf, 2010). They allow incorporating several types of prior information in order to get a unique source distribution. Parametric empirical bayes or PEB implemented into the SPM software package allows also to compare different models, incorporating different prior information, based on their free energy (Henson, 2009). However, using PEB in SPM only BEM forward models can be compared. Based on the fact the uncertainty on the anatomy can be incorporated within the free energy (Lopez, 2012), this work extended the PEB framework to FDM models.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
in
18th Annual Meeting of the Organization for Human Brain Mapping, Abstracts
article number
700WTH
pages
181 - 181
publisher
OHBM
place of publication
online
conference name
18th Annual Meeting of the Organization for Human Brain Mapping
conference location
Beijing, China
conference start
2012-06-10
conference end
2012-06-14
project
The integrative neuroscience of behavioral control (Neuroscience)
language
English
UGent publication?
yes
classification
C3
copyright statement
I have retained and own the full copyright for this publication
id
3239519
handle
http://hdl.handle.net/1854/LU-3239519
date created
2013-06-11 14:03:57
date last changed
2017-01-02 09:53:02
@inproceedings{3239519,
  abstract     = {Due to the ill-posed nature of the EEG source localization problem, the spatial resolution of the reconstructed activity is limited to several centimeters (Baillet, 2001). Advanced forward modeling of the head can contribute to improve the spatial resolution (Hallez, 2007). The boundary element method or BEM is commonly used due to its computation speed. More advanced volume modeling methods, such as finite difference methods or FDM, are computationally more intensive but allow estimating sources inside gray matter (Vanrumste, 2000). FDM also allows to incorporate tissue anisotropy and skull inhomogeneities (Hallez, 2008). Variational Bayesian approaches are getting more popular to solve the reconstruction problem (Friston, 2008 and Wipf, 2010). They allow incorporating several types of prior information in order to get a unique source distribution. Parametric empirical bayes or PEB implemented into the SPM software package allows also to compare different models, incorporating different prior information, based on their free energy (Henson, 2009). However, using PEB in SPM only BEM forward models can be compared. Based on the fact the uncertainty on the anatomy can be incorporated within the free energy (Lopez, 2012), this work extended the PEB framework to FDM models.},
  articleno    = {700WTH},
  author       = {Strobbe, Gregor and Lopez, Jose  and Montes Restrepo, Victoria Eugenia and van Mierlo, Pieter and Hallez, Hans and Vandenberghe, Stefaan},
  booktitle    = {18th Annual Meeting of the Organization for Human Brain Mapping, Abstracts},
  language     = {eng},
  location     = {Beijing, China},
  pages        = {700WTH:181--700WTH:181},
  publisher    = {OHBM},
  title        = {Comparing finite difference forward models using free energy based on multiple sparse priors},
  year         = {2012},
}

Chicago
Strobbe, Gregor, Jose Lopez, Victoria Eugenia Montes Restrepo, Pieter van Mierlo, Hans Hallez, and Stefaan Vandenberghe. 2012. “Comparing Finite Difference Forward Models Using Free Energy Based on Multiple Sparse Priors.” In 18th Annual Meeting of the Organization for Human Brain Mapping, Abstracts, 181–181. online: OHBM.
APA
Strobbe, G., Lopez, J., Montes Restrepo, V. E., van Mierlo, P., Hallez, H., & Vandenberghe, S. (2012). Comparing finite difference forward models using free energy based on multiple sparse priors. 18th Annual Meeting of the Organization for Human Brain Mapping, Abstracts (pp. 181–181). Presented at the 18th Annual Meeting of the Organization for Human Brain Mapping, online: OHBM.
Vancouver
1.
Strobbe G, Lopez J, Montes Restrepo VE, van Mierlo P, Hallez H, Vandenberghe S. Comparing finite difference forward models using free energy based on multiple sparse priors. 18th Annual Meeting of the Organization for Human Brain Mapping, Abstracts. online: OHBM; 2012. p. 181–181.
MLA
Strobbe, Gregor, Jose Lopez, Victoria Eugenia Montes Restrepo, et al. “Comparing Finite Difference Forward Models Using Free Energy Based on Multiple Sparse Priors.” 18th Annual Meeting of the Organization for Human Brain Mapping, Abstracts. online: OHBM, 2012. 181–181. Print.