Engineering Commons^™

Multi-Channel Analysis For Gradient Artifact Removal From Concurrent Eeg-Fmri Studies, Miguel R. Castellanos, Zhongming Liu

The Summer Undergraduate Research Fellowship (SURF) Symposium

Concurrent electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) recordings are susceptible to large amounts of noise due to the static and dynamic magnetic fields present inside the MR scanner. EEG-fMRI studies are conducted to provide better spatial and temporal resolution for each recording, respectively, but the artifacts found in the EEG render the data impossible to interpret. Past studies have focused on signal post-processing techniques which are able to effectively remove noise upon the completion of a study, but there are no techniques able to process the data in real-time without extensive calibration. This research addresses this issue by …