Andreas Galka, Laith Hamid, Ulrich Stephani
Time Series Analysis, Filtering, State Space Modelling,Artifact Removal, Electroencephalogram, Functional Mag-netic Resonance Imaging
We propose a novel state space modelling approach to removing scanner-related artifacts from electroencephalo- grams recorded inside MR scanners. For this purpose, dynamical templates for the actual brain activity and the ballistocardiogram are obtained from a short piece of data recorded without fMRI scanning; dynamical templates for the scanner artifacts are obtained from data recorded dur- ing fMRI scanning. Finally the two sets of dynamical tem- plates are merged. We compare our approach with Indepen- dent Component Analysis and find superior performance.
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