Neuroimaging clinics of North America
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Neuroimaging Clin. N. Am. · Nov 2017
ReviewTen Key Observations on the Analysis of Resting-state Functional MR Imaging Data Using Independent Component Analysis.
For more than 20 years, the powerful, flexible family of independent component analysis (ICA) techniques has been used to examine spatial, temporal, and subject variation in functional magnetic resonance (fMR) imaging data. This article provides an overview of 10 key principles in the basic and advanced application of ICA to resting-state fMR imaging. ICA's core advantages include robustness to artifact; false-positives and autocorrelation; adaptability to variant study designs; agnosticism to the temporal evolution of fMR imaging signals; and ability to extract, identify, and analyze neural networks. ICA remains in the vanguard of fMRI methods development.
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Neuroimaging Clin. N. Am. · Nov 2017
ReviewGraph Theoretic Analysis of Resting State Functional MR Imaging.
Graph theoretic analyses applied to examine the brain at rest have played a critical role in clarifying the foundations of the brain's intrinsic and task-related activity. There are many opportunities for clinical scientists to describe and predict dysfunction using a network perspective. ⋯ Major practices, concepts, and findings are concisely reviewed. The theoretic and practical frontiers of resting state functional MR imaging are highlighted with observations about major avenues for conceptual advances and clinical translation.