Back to Search
Start Over
Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI
- Source :
- Journal of Visualized Experiments.
- Publication Year :
- 2021
- Publisher :
- MyJove Corporation, 2021.
-
Abstract
- Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), EEG-fMRI, combines the complementary properties of scalp EEG (good temporal resolution) and fMRI (good spatial resolution) to measure neuronal activity during an electrographic event, through hemodynamic responses known as blood-oxygen-level-dependent (BOLD) changes. It is a non-invasive research tool that is utilized in neuroscience research and is highly beneficial to the clinical community, especially for the management of neurological diseases, provided that proper equipment and protocols are administered during data acquisition. Although recording EEG-fMRI is apparently straightforward, the correct preparation, especially in placing and securing the electrodes, is not only important for safety but is also critical in ensuring the reliability and analyzability of the EEG data obtained. This is also the most experience-demanding part of the preparation. To address these issues, a straightforward protocol that ensures data quality was developed. This article provides a step-by-step guide for acquiring reliable EEG data during EEG-fMRI using this protocol that utilizes readily available medical products. The presented protocol can be adapted to different applications of EEG-fMRI in research and clinical settings, and may be beneficial to both inexperienced and expert operators.
- Subjects :
- Protocol (science)
General Immunology and Microbiology
medicine.diagnostic_test
Event (computing)
Computer science
business.industry
General Chemical Engineering
General Neuroscience
Electroencephalography
EEG-fMRI
Machine learning
computer.software_genre
Magnetic Resonance Imaging
General Biochemistry, Genetics and Molecular Biology
Data acquisition
nervous system
Data quality
medicine
Humans
Artificial intelligence
Functional magnetic resonance imaging
business
computer
Reliability (statistics)
Subjects
Details
- ISSN :
- 1940087X
- Database :
- OpenAIRE
- Journal :
- Journal of Visualized Experiments
- Accession number :
- edsair.doi.dedup.....08ae332d8d50831468983b2492210753
- Full Text :
- https://doi.org/10.3791/62247