Difference between revisions of "Handling Artifacts in BESA"
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| + | Artifact correction always aims at extracting unwanted signals like EOG, EKG or external noise from the data, | ||
| + | while leaving all brain activity of interest as undisturbed as possible. To achieve this, artifact and brain topographies must be separated. Depending on whether one is dealing with spontaneous or evoked activity, different approaches for artifact correction are appropriate. However, if the data contain only a few artifacts and a sufficient number of artifact-free trials are retained, using artifact rejection rather than correction is adviced as this avoids the distortion resulting from correction. | ||
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It is important to get good templates for the topographies of the artifact using pattern search and averaging. Then the topographies can be used as spatial components during source analysis to separate brain from artifactual activities (preferred method). | It is important to get good templates for the topographies of the artifact using pattern search and averaging. Then the topographies can be used as spatial components during source analysis to separate brain from artifactual activities (preferred method). | ||
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The advantage of the first, preferred method is that the source waveform of the artifact and brain signals can be compared to see the epochs of critical interference. Maps are not distorted. The artifact correction of the on-going EEG (second method) contrast the artifact against the background EEG rhythms but not against the much smaller evoked response components to be averaged. | The advantage of the first, preferred method is that the source waveform of the artifact and brain signals can be compared to see the epochs of critical interference. Maps are not distorted. The artifact correction of the on-going EEG (second method) contrast the artifact against the background EEG rhythms but not against the much smaller evoked response components to be averaged. | ||
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Revision as of 15:52, 15 February 2017
| Module information | |
| Modules | BESA Research Basic or higher |
| Version | 5.2 or higher |
Artifact correction always aims at extracting unwanted signals like EOG, EKG or external noise from the data, while leaving all brain activity of interest as undisturbed as possible. To achieve this, artifact and brain topographies must be separated. Depending on whether one is dealing with spontaneous or evoked activity, different approaches for artifact correction are appropriate. However, if the data contain only a few artifacts and a sufficient number of artifact-free trials are retained, using artifact rejection rather than correction is adviced as this avoids the distortion resulting from correction.
