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DC Field | Value | Language |
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dc.contributor.author | Grech, Roberta | - |
dc.contributor.author | Camilleri, Tracey A. | - |
dc.contributor.author | Muscat, Joseph | - |
dc.contributor.author | Camilleri, Kenneth P. | - |
dc.contributor.author | Fabri, Simon G. | - |
dc.contributor.author | Zervakis, Michalis | - |
dc.contributor.author | Xanthopoulos, Petros | - |
dc.contributor.author | Sakkalis, Vangelis | - |
dc.contributor.author | Vanrumste, Bart | - |
dc.date.accessioned | 2017-05-04T08:49:56Z | - |
dc.date.available | 2017-05-04T08:49:56Z | - |
dc.date.issued | 2008 | - |
dc.identifier.citation | Grech, R., Cassar, T., Muscat, J., Camilleri, K. P., Fabri, S. G., Zervakis, M., ... & Vanrumste, B. (2008). Review on solving the inverse problem in EEG source analysis. Journal of Neuroengineering and Rehabilitation, 5(1), 25. | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/18810 | - |
dc.description.abstract | In this primer, we give a review of the inverse problem for EEG source localization. This is intended for the researchers new in the field to get insight in the state-of-the-art techniques used to find approximate solutions of the brain sources giving rise to a scalp potential recording. Furthermore, a review of the performance results of the different techniques is provided to compare these different inverse solutions. The authors also include the results of a Monte-Carlo analysis which they performed to compare four non parametric algorithms and hence contribute to what is presently recorded in the literature. An extensive list of references to the work of other researchers is also provided. This paper starts off with a mathematical description of the inverse problem and proceeds to discuss the two main categories of methods which were developed to solve the EEG inverse problem, mainly the non parametric and parametric methods. The main difference between the two is to whether a fixed number of dipoles is assumed a priori or not. Various techniques falling within these categories are described including minimum norm estimates and their generalizations, LORETA, sLORETA, VARETA, S-MAP, ST-MAP, Backus-Gilbert, LAURA, Shrinking LORETA FOCUSS (SLF), SSLOFO and ALF for non parametric methods and beamforming techniques, BESA, subspace techniques such as MUSIC and methods derived from it, FINES, simulated annealing and computational intelligence algorithms for parametric methods. From a review of the performance of these techniques as documented in the literature, one could conclude that in most cases the LORETA solution gives satisfactory results. In situations involving clusters of dipoles, higher resolution algorithms such as MUSIC or FINES are however preferred. Imposing reliable biophysical and psychological constraints, as done by LAURA has given superior results. The Monte-Carlo analysis performed, comparing WMN, LORETA, sLORETA and SLF, for different noise levels and different simulated source depths has shown that for single source localization, regularized sLORETA gives the best solution in terms of both localization error and ghost sources. Furthermore the computationally intensive solution given by SLF was not found to give any additional benefits under such simulated conditions. | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | BioMed Central Ltd. | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Electroencephalographers | en_GB |
dc.subject | Monte Carlo method | en_GB |
dc.subject | Electroencephalography -- Data processing | en_GB |
dc.title | Review on solving the inverse problem in EEG source analysis | en_GB |
dc.type | article | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
dc.identifier.doi | 10.1186/1743-0003-5-25 | - |
Appears in Collections: | Scholarly Works - FacEngSCE |
Files in This Item:
File | Description | Size | Format | |
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Review on solving the inverse problem in EEG source analysis.pdf Restricted Access | 2.7 MB | Adobe PDF | View/Open Request a copy |
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