title: Real-time EEG artifact correction during fMRI using ICA.
abstract: Simultaneous acquisition of EEG and fMRI data results in EEG signal contamination by imaging (MR) and ballistocardiogram (BCG) artifacts. Artifact correction of EEG data for real-time applications, such as neurofeedback studies, is the subject of ongoing research. To date, average artifact subtraction (AAS) is the most widespread real-time method used to partially remove BCG and imaging artifacts without requiring extra hardware equipment; no alternative software-only real time methods for removing EEG artifacts are available.
  
  
  
  We introduce a novel, improved approach for real-time EEG artifact correction during fMRI (rtICA). The rtICA is based on real time independent component analysis (ICA) and it is employed following the AAS method. The rtICA was implemented and validated during EEG and fMRI experiments on healthy subjects.
  
  
  
  Our results demonstrate that the rtICA employed after the rtAAS can obtain 98.4% success in detection of eye blinks, 4.4 times larger INPS reductions compared to RecView-corrected data, and effectively reduce motion artifacts, as well as imaging and muscle artifacts, in real time on six healthy subjects.
  
  
  
  We compared our real-time artifact reduction results with the rtAAS and various offline methods using multiple evaluation metrics, including power analysis. Importantly, the rtICA does not affect brain neuronal signals as reflected in EEG bands of interest, including the alpha band.
  
  
  
  A novel real-time ICA method was proposed for improving the EEG quality signal recorded during fMRI acquisition. The results show substantial reduction of different types of artifacts using real-time ICA method.
authors.affiliation: Laureate Institute for Brain Research, Tulsa, OK, USA; Department of Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, USA.
authors.forename: Ahmad
authors.initials: A
authors.lastname: Mayeli
authors.affiliation: Laureate Institute for Brain Research, Tulsa, OK, USA.
authors.forename: Vadim
authors.initials: V
authors.lastname: Zotev
authors.affiliation: Department of Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, USA.
authors.forename: Hazem
authors.initials: H
authors.lastname: Refai
authors.affiliation: Laureate Institute for Brain Research, Tulsa, OK, USA; Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA; Biomedical Engineering Center, University of Oklahoma, Norman, OK, USA. Electronic address: jbodurka@laureateinstitute.org.
authors.forename: Jerzy
authors.initials: J
authors.lastname: Bodurka
mesh_terms: D000328:Adult; D016477:Artifacts; D001921:Brain / Q000000981:diagnostic imaging* / Q000502:physiology*; D001931:Brain Mapping; D058256:Brain Waves / Q000502:physiology*; D004569:Electroencephalography; D005133:Eye Movements; D005260:Female; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D010100:Oxygen / Q000097:blood; D025341:Principal Component Analysis; D013997:Time Factors; D055815:Young Adult
chemical_list: D010100:Oxygen
keywords: EEG; EEG-fMRI; Real-time ICA; Real-time artifact correction; fMRI