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EEG-fMRI (short for EEG-correlated fMRI or electroencephalography-correlated functional magnetic resonance imaging) is a multimodal neuroimaging technique whereby EEG and fMRI data are recorded synchronously for the study of electrical brain activity in correlation with haemodynamic changes in brain during the electrical activity, be it normal function or associated with disorders.
The EEG proved to be a useful source in recording brain activity over the ensuing decades. However, it tended to be very difficult to assess the highly specific neural process that are the focus of cognitive neuroscience because using pure EEG data made it difficult to isolate individual neurocognitive processes. Event-related potentials (ERPs ...
The world record for the spatial resolution of a whole-brain MRI image was a 100-micrometer volume (image) achieved in 2019. The sample acquisition took about 100 hours. [ 2 ] The spatial world record of a whole human brain of any method was an X-ray tomography scan performing at the ESRF (European synchrotron radiation facility), which had a ...
Functional magnetic resonance imaging data. Functional neuroimaging is the use of neuroimaging technology to measure an aspect of brain function, often with a view to understanding the relationship between activity in certain brain areas and specific mental functions.
EEG can detect abnormal electrical discharges such as sharp waves, spikes, or spike-and-wave complexes, as observable in people with epilepsy; thus, it is often used to inform medical diagnosis. EEG can detect the onset and spatio-temporal (location and time) evolution of seizures and the presence of status epilepticus.
The first MR images of a human brain were obtained in 1978 by two groups of researchers at EMI Laboratories led by Ian Robert Young and Hugh Clow. [1] In 1986, Charles L. Dumoulin and Howard R. Hart at General Electric developed MR angiography, [2] and Denis Le Bihan obtained the first images and later patented diffusion MRI. [3]
Combining EEG with fMRI is hence potentially powerful because the two have complementary strengths—EEG has high temporal resolution, and fMRI high spatial resolution. But simultaneous acquisition needs to account for the EEG signal from varying blood flow triggered by the fMRI gradient field, and the EEG signal from the static field. [70]
EEG analysis is exploiting mathematical signal analysis methods and computer technology to extract information from electroencephalography (EEG) signals. The targets of EEG analysis are to help researchers gain a better understanding of the brain ; assist physicians in diagnosis and treatment choices; and to boost brain-computer interface (BCI ...