Advances in Resting-State Functional MRI: Methods, Interpretation, and Applications gives readers with basic neuroimaging experience an up-to-date and in-depth understanding of the methods, opportunities, and challenges in rs-fMRI. The book covers current knowledge gaps in rs-fMRI, including "what are biologically plausible brain networks," "how to tell what part is noise," "how to perform quality assurance on the data," "what are the spatial and temporal limits of our ability to resolve FC," and "how to best identify network features related to individual differences or disease state". This book is an ideal reference for neuroscientists, computational neuroscientists, psychologists, biomedical engineers, physicists and medical physicists. Both new and more advanced researchers alike will be able to discover new information distilled from the past decade of research to become well-versed in rs-fMRI-related topics.
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Dr. Jean Chen is a Senior Scientist at the Rotman Research Institute and Tier II Canada Research Chair in Neuroimaging of Aging. She is also faculty in Medical Biophysics at the University of Toronto. She received her PhD (2009) in Biomedical Engineering from McGill University, and completed her postdoctoral work on multimodal MRI of brain aging at the Martinos Center for Biomedical Imaging, Harvard Medical School (2011). She is best known for her work on fMRI measurements of brain physiology and physiology of the aging brain.
Catie Chang received her Ph.D. in Electrical Engineering from Stanford University, in the Radiological Sciences Lab. She was then a Postdoctoral Fellow in the Intramural Research Program of the National Institutes of Health. In 2018, she joined Vanderbilt University as an Assistant Professor. Her lab seeks to advance understanding of human brain function by developing techniques for analyzing and interpreting neuroimaging data.
Advances in Resting-State Functional MRI: Methods, Interpretation, and Applications gives readers with basic neuroimaging experience an up-to-date and in-depth understanding of the methods, opportunities, and challenges in rs-fMRI. The book covers current knowledge gaps in rs-fMRI, including "what are biologically plausible brain networks," "how to tell what part is noise," "how to perform quality assurance on the data," "what are the spatial and temporal limits of our ability to resolve FC," and "how to best identify network features related to individual differences or disease state".
This book is an ideal reference for neuroscientists, computational neuroscientists, psychologists, biomedical engineers, physicists and medical physicists. Both new and more advanced researchers alike will be able to discover new information distilled from the past decade of research to become well-versed in rs-fMRI-related topics.
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