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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.
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]
This can be done noninvasively in humans by combining transcranial magnetic stimulation with one of the neuroimaging tools such as PET, fMRI, or EEG. Massimini et al. (Science, September 30, 2005) used EEG to record how activity spreads from the stimulated site.
There are technical difficulties associated with combining EEG and fMRI including the need to remove the MRI gradient artifact present during MRI acquisition. Furthermore, currents can be induced in moving EEG electrode wires due to the magnetic field of the MRI. EEG can be used simultaneously with NIRS or fUS without major technical ...
A barrier in the widespread usage of MEG is due to pricing, as MEG systems can cost millions of dollars. EEG is a much more widely used method to achieve such temporal resolution as EEG systems cost much less than MEG systems. A disadvantage of EEG and MEG is that both methods have poor spatial resolution when compared to fMRI. [33]
This process is non-invasive and typically collects brain activity data using electroencephalography (EEG). Several neurofeedback protocols exist, with potential additional benefit from use of quantitative electroencephalography (QEEG) or functional magnetic resonance imaging (fMRI) to localize and personalize treatment.
An example that identified 10 large-scale brain networks from resting state fMRI activity through independent component analysis [15]. Because brain networks can be identified at various different resolutions and with various different neurobiological properties, there is currently no universal atlas of brain networks that fits all circumstances. [16]
Up to now, EEG-fMRI has been mainly seen as an fMRI technique in which the synchronously acquired EEG is used to characterize brain activity ('brain state') across time allowing to map (through statistical parametric mapping, for example) the associated haemodynamic changes. [52]