Neuroimaging clinics of North America
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Neuroimaging Clin. N. Am. · Nov 2017
ReviewApplications of Resting-State Functional Connectivity to Neurodegenerative Disease.
Neurodegenerative diseases target specific large-scale neuronal networks, leading to distinct behavioral and cognitive dysfunctions. Resting-state functional magnetic resonance imaging (rsfMR imaging)-based functional connectivity method maps symptoms-associated functional network deterioration in vivo. ⋯ Understanding of disease mechanism can further guide early detection and predictions of disease progression and inform development of more effective treatment. With better clinical phenotyping and larger samples across multiple sites, we discuss several possible future directions to further develop rsfMR imaging-based functional connectivity methods into scientifically and clinically useful assays for neurodegenerative disorders.
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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
ReviewResting-state Functional Magnetic Resonance Imaging in Presurgical Functional Mapping: Sensorimotor Localization.
This article compares resting-state functional magnetic resonance (fMR) imaging with task fMR imaging for presurgical functional mapping of the sensorimotor (SM) region. Before tumor resection, 38 patients were scanned using both methods. ⋯ A paired t-test showed higher overlap between resting-state maps and anatomic references compared with task activation when using a maximal overlap criterion. Resting state-derived maps are more comprehensive than those derived from task fMR imaging.
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Neuroimaging Clin. N. Am. · Nov 2017
ReviewLimitations of Resting-State Functional MR Imaging in the Setting of Focal Brain Lesions.
Methods of image acquisition and analysis for resting-state functional MR imaging (rsfMR imaging) are still evolving. Neurovascular uncoupling and susceptibility artifact are important confounds of rsfMR imaging in the setting of focal brain lesions such as brain tumors. This article reviews the detection of these confounds using rsfMR imaging metrics in the setting of focal brain lesions. In the near future, with the wide range of ongoing research in rsfMR imaging, these issues likely will be overcome and will open new windows into brain function and connectivity.
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Neuroimaging Clin. N. Am. · Nov 2017
ReviewMachine Learning Applications to Resting-State Functional MR Imaging Analysis.
Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances.