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Resting state fMRI (rs-fMRI or R-fMRI), also referred to as task-independent fMRI or task-free fMRI, is a method of functional magnetic resonance imaging (fMRI) that is used in brain mapping to evaluate regional interactions that occur in a resting or task-negative state, when an explicit task is not being performed.
For example, it can be used in brain imaging to suppress cerebrospinal fluid (CSF) effects on the image, so as to bring out the periventricular hyperintense lesions, such as multiple sclerosis (MS) plaques. [1] It was invented by Graeme Bydder, Joseph Hajnal, and Ian Young in the early 1990s. [2]
The first study of the human brain at 3.0 T was published in 1994, [13] and in 1998 at 8 T. [14] Studies of the human brain have been performed at 9.4 T (2006) [15] and up to 10.5 T (2019). [16] Paul Lauterbur and Sir Peter Mansfield were awarded the 2003 Nobel Prize in Physiology or Medicine for their discoveries concerning MRI.
Functional magnetic resonance imaging or functional MRI (fMRI) measures brain activity by detecting changes associated with blood flow. [1] [2] This technique relies on the fact that cerebral blood flow and neuronal activation are coupled. When an area of the brain is in use, blood flow to that region also increases. [3]
In vivo magnetic resonance spectroscopy (MRS) is a specialized technique associated with magnetic resonance imaging (MRI). [1] [2]Magnetic resonance spectroscopy (MRS), also known as nuclear magnetic resonance (NMR) spectroscopy, is a non-invasive, ionizing-radiation-free analytical technique that has been used to study metabolic changes in brain tumors, strokes, seizure disorders, Alzheimer's ...
Averaging is necessary because of the complex spectral structures and relatively low concentrations of many brain metabolites, which result in a low signal-to-noise ratio (SNR) in MRS of a living brain. fMRS differs from MRS by acquiring not one but multiple spectra at different time points while the participant is inside the MRI scanner.
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A whole brain/voxel-wise approach can be analyzed by registering the ASL map into MNI space for group comparisons. A region of interest approach can be analyzed by registering the ASL map into a selected cluster, or an atlas , like a standard (such as the Harvard-Oxford Cortical atlas) or an individual atlas developed by software like FreeSurfer .