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Wavelet analysis as a tool for investigating movement-related cortical oscillations in EEG-fMRI coregistration.
- Source :
-
Brain topography [Brain Topogr] 2010 Mar; Vol. 23 (1), pp. 46-57. - Publication Year :
- 2010
-
Abstract
- Electroencephalography combined with functional magnetic resonance imaging (EEG-fMRI) identifies blood oxygenation level dependent (BOLD) signal changes associated with physiological and pathological EEG events. In this study we used EEG-fMRI to determine the possible correlation between topographical movement related EEG changes in brain oscillatory activity recorded from EEG electrodes over the scalp and fMRI cortical responses in motor areas during finger movement. Thirty-two channels of EEG were recorded in 12 subjects during eyes-closed condition inside a three T magnetic resonance (MR) scanner using an MR-compatible EEG recording system. Off-line MRI artifact subtraction software was applied to obtain continuous EEG data during fMRI acquisition. For EEG data analysis we used a time-frequency approach to measure time by varying the energy in a signal at a given frequency band by the convolution of the EEG signal with a wavelet family in the alpha and beta bands. The correlation between the BOLD signal associated with the EEG regressor provides that sensory motor region is a source of the EEG. We conclude that combined EEG-fMRI can be used to investigate movement-related oscillations of the human brain inside an MRI scanner and wavelet analysis adds further details on the EEG changes. The movement-related changes in the EEG signals are useful to identify the brain activation sources responsible for BOLD-signal changes.
- Subjects :
- Adult
Alpha Rhythm
Artifacts
Beta Rhythm
Brain blood supply
Brain Mapping methods
Female
Fingers
Humans
Male
Oxygen blood
Periodicity
Software
Time Factors
Young Adult
Brain physiology
Electroencephalography methods
Evoked Potentials, Motor
Magnetic Resonance Imaging methods
Motor Activity physiology
Signal Processing, Computer-Assisted
Subjects
Details
- Language :
- English
- ISSN :
- 1573-6792
- Volume :
- 23
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Brain topography
- Publication Type :
- Academic Journal
- Accession number :
- 19921416
- Full Text :
- https://doi.org/10.1007/s10548-009-0117-2