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, | 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 | + | 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 advised as this avoids the distortion resulting from correction. |
Revision as of 16:52, 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 advised as this avoids the distortion resulting from correction.
