NeuroImage
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This article provides a personal perspective of the adoption of path analysis (structural equation modeling) to neuroimaging. The paper covers the motivation stemming from the need to merge functional measures with neuroanatomy and early innovations in its application. The use of path analysis as a means to test directional hypotheses about networks is presented along with the development of the complementary method, partial least squares. A method is useful when it provides insights that were previously inaccessible, and reflecting this, the paper concludes with a synopsis of the theoretical developments that arose for the routine use of methods like path analysis.
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Review Historical Article
The future of acquisition speed, coverage, sensitivity, and resolution.
Two decades of technology development has continually improved the image quality, spatial-temporal resolution, and sensitivity of the fMRI acquisition. In this article, I assess our current acquisition needs, briefly examine the technological breakthroughs that have benefited fMRI in the past, and look at some promising technologies that are currently under development to try to envision what the fMRI acquisition protocol of the future might look like.
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Blood inflow from the upstream has contribution or contamination to the blood oxygen level-dependent (BOLD) functional signal both in its magnitude and time courses. During neuronal activations, regional blood flow velocity increases which results in increased fMRI signals near the macrovasculatures. The inflow effects are dependent on RF pulse history, slice geometry, flow velocity, blood relaxation times and imaging parameters. ⋯ This article reviews the basic principle of the inflow effects, its appearances in conventional GRE, fast spin-echo (FSE) and echo-planar imaging (EPI) acquisitions, methods for separating the inflow from the BOLD effect as well as the interplay between imaging parameters and other physiological factors with the inflow effects in fMRI. Based on theoretical derivation and human experiments, the inflow effects have been shown to contribute significantly in conventional GRE but negligible in FSE acquisitions. For gradient-echo EPI experiments, the blood inflow could modulate both amplitude and the temporal information of the fMRI signal, depending on the imaging parameters and settings.
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The goal of this review is to describe, from a personal perspective, the development and emergence of the resting state fMRI. In particular, various concepts derived from the resting state data are discussed in detail, including connectivity, amplitude of the fluctuations, analysis techniques, and use in clinical populations. We also briefly summarize our efforts in creating an open data sharing platform as well as both a journal and a conference dedicated to brain connectivity. All three projects are aimed at significantly increasing the impact of resting state fMRI developments and enabling large, collaborative science projects.
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T2*-weighted Blood Oxygen Level Dependent (BOLD) functional magnetic resonance imaging (fMRI) requires efficient acquisition methods in order to fully sample the brain in a several second time period. The most widely used approach is Echo Planar Imaging (EPI), which utilizes a Cartesian trajectory to cover k-space. This trajectory is subject to ghosts from off-resonance and gradient imperfections and is intrinsically sensitive to cardiac-induced pulsatile motion from substantial first- and higher order moments of the gradient waveform near the k-space origin. ⋯ Spiral methods have reduced sensitivity to motion, shorter readout times, improved signal recovery in most frontal and parietal brain regions, and exhibit blurring artifacts instead of ghosts or geometric distortion. Methods combining spiral-in and spiral-out trajectories have further advantages in terms of diminished susceptibility-induced signal dropout and increased BOLD signal. In measurements of temporal signal to noise ratio measured in 8 subjects, spiral-in/out exhibited significant increases over EPI in voxel volumes recovered in frontal and whole brain regions (18% and 10%, respectively).