Handbook Of Functional Mri Data Analysis

Download or read book Handbook of Functional MRI Data Analysis written by Russell A. Poldrack and published by Cambridge University Press. This book was released on 2024-02-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook for Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM, and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling, and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software.

Download or read book Handbook of Functional MRI Data Analysis written by Russell A. Poldrack and published by Cambridge University Press. This book was released on 2011-08-22 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook for Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM, and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling, and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software.

Download or read book Handbook of Functional MRI Data Analysis written by Russell A. Poldrack and published by Cambridge University Press. This book was released on 2011-08-22 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook of Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software.

Download or read book Handbook of functional connectivity Magnetic Resonance Imaging methods in CONN written by Alfonso Nieto-Castanon and published by Hilbert Press. This book was released on 2020-01-31 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook describes methods for processing and analyzing functional connectivity Magnetic Resonance Imaging (fcMRI) data using the CONN toolbox, a popular freely-available functional connectivity analysis software. Content description [excerpt from introduction] The first section (fMRI minimal preprocessing pipeline) describes standard and advanced preprocessing steps in fcMRI. These steps are aimed at correcting or minimizing the influence of well-known factors affecting the quality of functional and anatomical MRI data, including effects arising from subject motion within the scanner, temporal and spatial image distortions due to the sequential nature of the scanning acquisition protocol, and inhomogeneities in the scanner magnetic field, as well as anatomical differences among subjects. Even after these conventional preprocessing steps, the measured blood-oxygen-level-dependent (BOLD) signal often still contains a considerable amount of noise from a combination of physiological effects, outliers, and residual subject-motion factors. If unaccounted for, these factors would introduce very strong and noticeable biases in all functional connectivity measures. The second section (fMRI denoising pipeline) describes standard and advanced denoising procedures in CONN that are used to characterize and remove the effect of these residual non-neural noise sources. Functional connectivity Magnetic Resonance Imaging studies attempt to quantify the level of functional integration across different brain areas. The third section (functional connectivity measures) describes a representative set of functional connectivity measures available in CONN, each focusing on different indicators of functional integration, including seed-based connectivity measures, ROI-to-ROI measures, graph theoretical approaches, network-based measures, and dynamic connectivity measures. Second-level analyses allow researchers to make inferences about properties of groups or populations, by generalizing from the observations of only a subset of subjects in a study. The fourth section (General Linear Model) describes the mathematics behind the General Linear Model (GLM), the approach used in CONN for all second-level analyses of functional connectivity measures. The description includes GLM model definition, parameter estimation, and hypothesis testing framework, as well as several practical examples and general guidelines aimed at helping researchers use this method to answer their specific research questions. The last section (cluster-level inferences) details several approaches implemented in CONN that allow researchers to make meaningful inferences from their second-level analysis results while providing appropriate family-wise error control (FWEC), whether in the context of voxel-based measures, such as when studying properties of seed-based maps across multiple subjects, or in the context of ROI-to-ROI measures, such as when studying properties of ROI-to-ROI connectivity matrices across multiple subjects.

Download or read book Handbook of Neuroimaging Data Analysis written by Hernando Ombao and published by CRC Press. This book was released on 2016-11-18 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph.D. students in statistics, biostatistics, psychology, neuroscience, and computer science.

Download or read book Introduction to Neuroimaging Analysis written by Mark Jenkinson and published by Oxford University Press. This book was released on 2018 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This accessible primer gives an introduction to the wide array of MRI-based neuroimaging methods that are used in research. It provides an overview of the fundamentals of what different MRI modalities measure, what artifacts commonly occur, the essentials of the analysis, and common 'pipelines'.

Download or read book Introduction to Functional Magnetic Resonance Imaging written by Richard B. Buxton and published by Cambridge University Press. This book was released on 2009-08-27 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: Functional Magnetic Resonance Imaging (fMRI) has become a standard tool for mapping the working brain's activation patterns, both in health and in disease. It is an interdisciplinary field and crosses the borders of neuroscience, psychology, psychiatry, radiology, mathematics, physics and engineering. Developments in techniques, procedures and our understanding of this field are expanding rapidly. In this second edition of Introduction to Functional Magnetic Resonance Imaging, Richard Buxton – a leading authority on fMRI – provides an invaluable guide to how fMRI works, from introducing the basic ideas and principles to the underlying physics and physiology. He covers the relationship between fMRI and other imaging techniques and includes a guide to the statistical analysis of fMRI data. This book will be useful both to the experienced radiographer, and the clinician or researcher with no previous knowledge of the technology.