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Simultaneous Electroencephalography-Functional Magnetic Resonance Imaging for Assessment of Human Brain Function Publisher



Ebrahimzadeh E1, 2 ; Saharkhiz S3 ; Rajabion L4 ; Oskouei HB5 ; Seraji M6 ; Fayaz F7 ; Saliminia S7 ; Sadjadi SM1 ; Soltanianzadeh H1, 2
Authors
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Authors Affiliations
  1. 1. School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
  2. 2. School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
  3. 3. Department of Pharmacology-Physiology, Faculty of Medicine, University of Sherbrooke, Sherbrooke, Canada
  4. 4. School of Graduate Studies, State University of New York Empire State College, Manhattan, NY, United States
  5. 5. School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Department of Psychology, University of Texas at Austin, Austin, TX, United States
  7. 7. Department of Biomedical Engineering, School of Electrical Engineering, Payame Noor University of North Tehran, Tehran, Iran

Source: Frontiers in Systems Neuroscience Published:2022


Abstract

Electroencephalography (EEG) and functional Magnetic Resonance Imaging (MRI) have long been used as tools to examine brain activity. Since both methods are very sensitive to changes of synaptic activity, simultaneous recording of EEG and fMRI can provide both high temporal and spatial resolution. Therefore, the two modalities are now integrated into a hybrid tool, EEG-fMRI, which encapsulates the useful properties of the two. Among other benefits, EEG-fMRI can contribute to a better understanding of brain connectivity and networks. This review lays its focus on the methodologies applied in performing EEG-fMRI studies, namely techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. We will investigate simultaneous resting-state and task-based EEG-fMRI studies and discuss their clinical and technological perspectives. Moreover, it is established that the brain regions affected by a task-based neural activity might not be limited to the regions in which they have been initiated. Advanced methods can help reveal the regions responsible for or affected by a developed neural network. Therefore, we have also looked into studies related to characterization of structure and dynamics of brain networks. The reviewed literature suggests that EEG-fMRI can provide valuable complementary information about brain neural networks and functions. Copyright © 2022 Ebrahimzadeh, Saharkhiz, Rajabion, Oskouei, Seraji, Fayaz, Saliminia, Sadjadi and Soltanian-Zadeh.
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