Name
Title | ||
|---|---|---|
A physiologically motivated sparse, compact, and smooth (SCS) approach to EEG source localization. |
Abstract | ||
|---|---|---|
Here, we introduce a novel approach to the EEG inverse problem based on the assumption that principal cortical sources of multi-channel EEG recordings may be assumed to be spatially sparse, compact, and smooth (SCS). To enforce these characteristics of solutions to the EEG inverse problem, we propose a correlation-variance model which factors a cortical source space covariance matrix into the multiplication of a pre-given correlation coefficient matrix and the square root of the diagonal variance matrix learned from the data under a Bayesian learning framework. We tested the SCS method using simulated EEG data with various SNR and applied it to a real ECOG data set. We compare the results of SCS to those of an established SBL algorithm. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/EMBC.2012.6346237 | EMBC |
Keywords | Field | DocType |
diagonal variance matrix learning,physiologically motivated compact approach,sbl algorithm,principal cortical sources,covariance analysis,learning (artificial intelligence),electroencephalography,pregiven correlation coefficient matrix,covariance matrices,eeg source localization,medical signal processing,inverse problems,physiologically motivated sparse approach,bayes methods,inverse problem,correlation-variance model,cortical source space covariance matrix,multichannel eeg recordings,bayesian learning framework,physiologically motivated smooth approach,correlation methods,learning artificial intelligence,signal to noise ratio,bayes theorem,magnetic resonance imaging,computer simulation | Diagonal,Bayesian inference,Pattern recognition,Matrix (mathematics),Computer science,Signal-to-noise ratio,Multiplication,Inverse problem,Artificial intelligence,Covariance matrix,Square root | Conference |
Volume | ISSN | ISBN |
2012 | 1557-170X | 978-1-4577-1787-1 |
Citations | PageRank | References |
1 | 0.37 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cheng Cao | 1 | 25 | 3.54 |
| Zeynep Akalin Acar | 2 | 91 | 8.22 |
| Kenneth Kreutz-Delgado | 3 | 872 | 88.17 |
| S Makeig | 4 | 1490 | 206.49 |