A Hierarchical Bayesian M/EEG Imaging Method Correcting for Incomplete Spatio-Temporal Priors

Carsten Stahlhut; Hagai T. Attias; Kensuke Sekihara; David Wipf; Lars Kai Hansen; Srikantan S. Nagarajan

doi:10.1109/ISBI.2013.6556536

A Hierarchical Bayesian M/EEG Imaging Method Correcting for Incomplete Spatio-Temporal Priors

Carsten Stahlhut, Hagai T. Attias, Kensuke Sekihara, David Wipf, Lars Kai Hansen, Srikantan S. Nagarajan

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

In this paper we present a hierarchical Bayesian model, to tackle the highly ill-posed problem that follows with MEG and EEG source imaging. Our model promotes spatiotemporal patterns through the use of both spatial and temporal basis functions. While in contrast to most previous spatio-temporal inverse M/EEG models, the proposed model benefits of consisting of two source terms, namely, a spatiotemporal pattern term limiting the source configuration to a spatio-temporal subspace and a source correcting term to pick up source activity not covered by the spatio-temporal prior belief. Both artificial data and real EEG data is used to demonstrate the efficacy of the model.

Original language	English
Title of host publication	2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013)
Publisher	IEEE
Publication date	2013
Pages	560-563
ISBN (Print)	978-1-4673-6456-0
DOIs	https://doi.org/10.1109/ISBI.2013.6556536
Publication status	Published - 2013
Event	10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - San Francisco, United States Duration: 7 Apr 2013 → 11 Apr 2013 http://www.biomedicalimaging.org/2013/ http://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=20048

Conference

Conference	10th IEEE International Symposium on Biomedical Imaging
Country	United States
City	San Francisco
Period	07/04/2013 → 11/04/2013
Internet address	http://www.biomedicalimaging.org/2013/ http://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=20048

Series	International Symposium on Biomedical Imaging. Proceedings
ISSN	1945-7928

Keywords

EEG
MEG
Inverse problem
Spatio-temporal prior
Variational Bayes

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Stahlhut, C., Attias, H. T., Sekihara, K., Wipf, D., Hansen, L. K., & Nagarajan, S. S. (2013). A Hierarchical Bayesian M/EEG Imaging Method Correcting for Incomplete Spatio-Temporal Priors. In 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013) (pp. 560-563). IEEE. International Symposium on Biomedical Imaging. Proceedings https://doi.org/10.1109/ISBI.2013.6556536

Stahlhut, Carsten ; Attias, Hagai T. ; Sekihara, Kensuke ; Wipf, David ; Hansen, Lars Kai ; Nagarajan, Srikantan S. / A Hierarchical Bayesian M/EEG Imaging Method Correcting for Incomplete Spatio-Temporal Priors. 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013). IEEE, 2013. pp. 560-563 (International Symposium on Biomedical Imaging. Proceedings).

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abstract = "In this paper we present a hierarchical Bayesian model, to tackle the highly ill-posed problem that follows with MEG and EEG source imaging. Our model promotes spatiotemporal patterns through the use of both spatial and temporal basis functions. While in contrast to most previous spatio-temporal inverse M/EEG models, the proposed model benefits of consisting of two source terms, namely, a spatiotemporal pattern term limiting the source configuration to a spatio-temporal subspace and a source correcting term to pick up source activity not covered by the spatio-temporal prior belief. Both artificial data and real EEG data is used to demonstrate the efficacy of the model.",

keywords = "EEG, MEG, Inverse problem, Spatio-temporal prior, Variational Bayes",

author = "Carsten Stahlhut and Attias, {Hagai T.} and Kensuke Sekihara and David Wipf and Hansen, {Lars Kai} and Nagarajan, {Srikantan S.}",

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note = "10th IEEE International Symposium on Biomedical Imaging : From Nano to Macro, ISBI 2013 ; Conference date: 07-04-2013 Through 11-04-2013",

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Stahlhut, C, Attias, HT, Sekihara, K, Wipf, D, Hansen, LK & Nagarajan, SS 2013, A Hierarchical Bayesian M/EEG Imaging Method Correcting for Incomplete Spatio-Temporal Priors. in 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013). IEEE, International Symposium on Biomedical Imaging. Proceedings, pp. 560-563, 10th IEEE International Symposium on Biomedical Imaging, San Francisco, United States, 07/04/2013. https://doi.org/10.1109/ISBI.2013.6556536

A Hierarchical Bayesian M/EEG Imaging Method Correcting for Incomplete Spatio-Temporal Priors. / Stahlhut, Carsten; Attias, Hagai T.; Sekihara, Kensuke; Wipf, David; Hansen, Lars Kai; Nagarajan, Srikantan S.

2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013). IEEE, 2013. p. 560-563 (International Symposium on Biomedical Imaging. Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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