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"(Medical Xpress)\u2014Functional neuroimaging technologies \u2013 such as functional Magnetic Resonance Imaging (fMRI), Positron emission tomography (PET), multichannel electroencephalography (EEG), magnetoencephalography (MEG), Near Infrared Spectroscopic Imaging (NIRSI), and Single Photon Emission Computed Tomography (SPECT) \u2013 are used to measure brain activity and its relationship to specific brain areas. Of these, resting state fMRI (known as rs-fMRI) is employed to evaluate regional interactions that occur when a subject is not performing an explicit task. Since these interactions represent network communication between brain regions, their study is integral to further understanding human behavior, cognitive development and neuropsychiatric disease. More specifically, this resting brain activity is observed noninvasively using fMRI, which detects changes in blood flow in the brain as Blood Oxygen Level Dependent (BOLD) MRI signals. While powerful, so-called BOLD fMRI has two drawbacks: even 1 mm or less of head movement while scanning can impact connectivity estimates, and BOLD sensitivity can be reduced by high subject motion. (This limitation means that when comparing the rs-fMRI data of adult controls versus high-movement subjects such as neuropsychiatric patients or children, false positive functional connectivity findings can become very prevalent.) Recently, however, scientists at the National Institute of Mental Health, University of Cambridge and other locations devised an integrated strategy for data acquisition, denoising, and connectivity estimation by combining data acquisition with multiecho (ME) echo planar imaging and analysis with spatial independent component analysis (ICA), called ME-ICA, which distinguishes BOLD (neuronally related) and non-BOLD (artifactual) effects. The researchers found that when compared with traditional techniques, their proposed strategy results in a fourfold signal-to-noise ratio improvement, more specific functional connectivity analysis, and valid statistical inference and error control between groups with different levels of subject motion."^^<http://www.w3.org/2001/XMLSchema#string>
<http://medicalxpress.com/news/2013-10-motion-tolerant-bold-fmri-signal-to-noise-functional.html>