Rimpilaeinen, V;
Koulouri, A;
Lucka, F;
Kaipio, JP;
Wolters, CH;
(2018)
Bayesian Modelling of Skull Conductivity Uncertainties in EEG Source Imaging.
In: Eskola, H and Vaisanen, O and Viik, J and Hyttinen, J, (eds.)
Proceedings of the European Medical and Biological Engineering Confernce Nordic-Baltic Conference on Biomedical Engineering and Medical Physics:EMBEC & NBC 2017.
(pp. pp. 892-895).
Springer: Tampere, Finland.
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Abstract
Knowing the correct skull conductivity is crucial for the accuracy of EEG source imaging, but unfortunately, its true value, which is inter- and intra-individually varying, is difficult to determine. In this paper, we propose a statistical method based on the Bayesian approximation error approach to compensate for source imaging errors related to erronous skull conductivity. We demonstrate the potential of the approach by simulating EEG data of focal source activity and using the dipole scan algorithm and a sparsity promoting prior to reconstruct the underlying sources. The results suggest that the greatest improvements with the proposed method can be achieved when the focal sources are close to the skull.
| Type: | Proceedings paper |
|---|---|
| Title: | Bayesian Modelling of Skull Conductivity Uncertainties in EEG Source Imaging |
| Event: | European Medical and Biological Engineering Confernce Nordic-Baltic Conference on Biomedical Engineering and Medical Physics:EMBEC & NBC 2017 |
| Location: | Tampere, FINLAND |
| Dates: | June 2017 - June 2017 |
| ISBN-13: | 978-981-10-5121-0 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-981-10-5122-7_223 |
| Publisher version: | https://doi.org/10.1007/978-981-10-5122-7_223 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Electroencephalography, Bayesian modelling, inverse problems, skull conductivity |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10064098 |
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