Dataset Information

Evaluation of Electroencephalography Source Localization Algorithms with Multiple Cortical Sources.

ABSTRACT:

Background

Source localization algorithms often show multiple active cortical areas as the source of electroencephalography (EEG). Yet, there is little data quantifying the accuracy of these results. In this paper, the performance of current source density source localization algorithms for the detection of multiple cortical sources of EEG data has been characterized.

Methods

EEG data were generated by simulating multiple cortical sources (2-4) with the same strength or two sources with relative strength ratios of 1:1 to 4:1, and adding noise. These data were used to reconstruct the cortical sources using current source density (CSD) algorithms: sLORETA, MNLS, and LORETA using a p-norm with p equal to 1, 1.5 and 2. Precision (percentage of the reconstructed activity corresponding to simulated activity) and Recall (percentage of the simulated sources reconstructed) of each of the CSD algorithms were calculated.

Results

While sLORETA has the best performance when only one source is present, when two or more sources are present LORETA with p equal to 1.5 performs better. When the relative strength of one of the sources is decreased, all algorithms have more difficulty reconstructing that source. However, LORETA 1.5 continues to outperform other algorithms. If only the strongest source is of interest sLORETA is recommended, while LORETA with p equal to 1.5 is recommended if two or more of the cortical sources are of interest. These results provide guidance for choosing a CSD algorithm to locate multiple cortical sources of EEG and for interpreting the results of these algorithms.

SUBMITTER: Bradley A

PROVIDER: S-EPMC4725774 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Evaluation of Electroencephalography Source Localization Algorithms with Multiple Cortical Sources.

Bradley Allison A Yao Jun J Dewald Jules J Richter Claus-Peter CP

PloS one 20160125 1

<h4>Background</h4>Source localization algorithms often show multiple active cortical areas as the source of electroencephalography (EEG). Yet, there is little data quantifying the accuracy of these results. In this paper, the performance of current source density source localization algorithms for the detection of multiple cortical sources of EEG data has been characterized.<h4>Methods</h4>EEG data were generated by simulating multiple cortical sources (2-4) with the same strength or two source ...[more]

PMID: 26809000

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Project description:Magnetoencephalography (MEG) is a useful non-invasive technique for presurgical evaluation of focal cortical dysplasia patients. We aimed at clarifying the precise spatial relationship between the spiking volume determined with MEG, the seizure onset zone and the lesional volume in patients with focal cortical dysplasia. We studied the spatial relationships between the MEG spiking volume determined with a recent analysis pipeline, the seizure-onset zone location determined with a quantitative index calculated from intracranial EEG signals ('Epileptogenicity Index') and the lesional volume delineated on brain MRI in 11 patients with Focal Cortical Dysplasia explored with Stereo-electroencephalography (SEEG). A significant correlation between the MEG spiking activity and the Epileptogenicity Index was found in 8/11 patients. 7/8 patients were operated upon and had good surgical outcome. For three patients, no correlation between Epileptogenicity Index and spiking activity was observed; only one of those three patients had good surgical outcome. The lesion was at least partially overlapping with the seizure-onset zone in 8/9 patients with a lesion clearly identifiable by MRI. However, 57% of the SEEG epileptogenic contacts were located outside of the lesional volume. Lastly 44% of the highly epileptogenic SEEG contacts were located within the spiking volume and 22% of them were located exclusively in the spiking volume and not in the lesion. For 7/9 patients with a lesion, < 50% of epileptogenic SEEG contacts were included within the lesion: for 5/7 patients MEG provided an added value for targeting the epileptogenic region through intracranial electrodes, while for two of seven patients MEG detected only a few extralesional epileptogenic contacts. Our study suggests that modeling of the spiking volume with MEG is a promising tool to localize non-invasively the seizure-onset zone in patients with focal cortical dysplasia. Combined with brain MRI, MEG modeling of the spiking volume contributes to delineate the spatial extent of the seizure-onset zone.

Dataset Information

Evaluation of Electroencephalography Source Localization Algorithms with Multiple Cortical Sources.

Background

Methods

Results

Publications

Evaluation of Electroencephalography Source Localization Algorithms with Multiple Cortical Sources.

Similar Datasets

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