In this article we present a collection of common EEG artifacts with their characteristics and pictures to facilitate their identification, and various tools offered by BrainVision Analyzer 2 for artifact detection, rejection, and removal. Towards the end we make some suggestions for devising an overall artifact handling strategy.
Electroencephalography (EEG) concurrently acquired with fMRI provides high temporal resolution information about brain activity as well as subject head movement. We introduced an EEG-assisted retrospective motion correction (E-REMCOR) method that utilizes EEG data to correct for head movements in fMRI on a slice-by-slice basis and substantially improves the quality of the data. To further enhance the usability of E-REMCOR, especially for the large-scale EEG-fMRI studies, we developed an automatic and improved implementation of E-REMCOR, referred as aE-REMCOR.
Simultaneous EEG-fMRI acquisitions can offer valuable insights for the non-invasive study of human brain function. Concurrently, the benefits offered by high-field imaging have attracted considerable interest towards simultaneous EEG-fMRI at higher field strengths. Unfortunately, simultaneous acquisitions are subject to problematic interactions that can compromise data quality and subject safety. Reducing noise during acquisition is crucial to improve EEG data quality, especially at higher fields. In this article, we assessed the importance of EEG cable length and geometry on noise sensitivity, at 7T, at the level of transmission between the cap and amplifiers.
Removing artifacts induced by tDC, tAC, tRN stimulators from EEG signals is a tricky and challenging task. However, it is a key prerequisite for EEG signal analysis. Artifact-corrected EEG data will lead to improved scientific conclusions on the effects of the stimulation that has been applied.
The most prominent MR-related EEG artifacts are gradient artifacts and the ballistocardiogram. However, vibrations represent another problematic source of artifacts. Therefore, noise assessment and reduction is of special importance for EEG measurements within the MR scanner.
