Introduction to Neuroimaging Analysis

Introduction to Neuroimaging Analysis PDF

Author: Mark Jenkinson

Publisher: Oxford University Press

Published: 2018

Total Pages: 277

ISBN-13: 0198816308

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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'

Introduction to Neuroimaging Analysis

Introduction to Neuroimaging Analysis PDF

Author: Mark Jenkinson

Publisher: Oxford University Press

Published: 2018-03-15

Total Pages: 208

ISBN-13: 0192548271

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MRI has emerged as a powerful way of studying in-vivo brain structure and function in both healthy and disease states. Whilst new researchers may be able to call upon advice and support for acquisition from operators, radiologists and technicians, it is more challenging to obtain an understanding of the principles of analysing neuroimaging data. This is crucial for choosing acquisition parameters, designing and performing appropriate experiments, and correctly interpreting the results. This primer gives a general and accessible introduction to the wide array of MRI-based neuroimaging methods that are used in research. Supplemented with online datasets and examples to enable the reader to obtain hands-on experience working with real data, it provides a practical and approachable introduction for those new to the neuroimaging field. The text also covers the fundamentals of what different MRI modalities measure, what artifacts commonly occur, the essentials of the analysis, and common 'pipelines' including brain extraction, registration and segmentation. As it does not require any background knowledge beyond high-school mathematics and physics, this primer is essential reading for anyone wanting to work in neuroimaging or grasp the results coming from this rapidly expanding field. The Oxford Neuroimaging Primers are short texts aimed at new researchers or advanced undergraduates from the biological, medical or physical sciences. They are intended to provide a broad understanding of the ways in which neuroimaging data can be analyzed and how that relates to acquisition and interpretation. Each primer has been written so that it is a stand-alone introduction to a particular area of neuroimaging, and the primers also work together to provide a comprehensive foundation for this increasingly influential field.

Introduction to Resting State fMRI Functional Connectivity

Introduction to Resting State fMRI Functional Connectivity PDF

Author: Janine Bijsterbosch

Publisher: Oxford University Press

Published: 2017-06-15

Total Pages: 200

ISBN-13: 0192535757

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Spontaneous 'resting-state' fluctuations in neuronal activity offer insights into the inherent organisation of the human brain, and may provide markers for diagnosis and treatment of mental disorders. Resting state functional magnetic resonance imaging (fMRI) can be used to investigate intrinsic functional connectivity networks, which are identified based on similarities in the signal measured from different regions. From data acquisition to results interpretation, An Introduction to Resting State fMRI Functional Connectivity discusses a wide range of approaches without expecting previous knowledge of the reader, making it truly accessible to readers from a broad range of backgrounds. Supplemented with online examples to enable the reader to obtain hands-on experience working with data, the text also provides details to enhance learning for those already experienced in the field. The Oxford Neuroimaging Primers are written for new researchers or advanced undergraduates in neuroimaging to provide a thorough understanding of the ways in which neuroimaging data can be analysed and interpreted. Aimed at students without a background in mathematics or physics, this book is also important reading for those familiar with task fMRI but new to the field of resting state fMRI.

Introduction to Functional Magnetic Resonance Imaging

Introduction to Functional Magnetic Resonance Imaging PDF

Author: Richard B. Buxton

Publisher: Cambridge University Press

Published: 2009-08-27

Total Pages: 479

ISBN-13: 0521899958

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This is the second edition of a useful introductory book on a technique that has revolutionized neuroscience, specifically cognitive neuroscience. Functional magnetic resonance imaging (fMRI) has now become the standard tool for studying the brain systems involved in cognitive and emotional processing. It has also been a major factor in the consilience of the fields of neurobiology, cognitive psychology, social psychology, radiology, physics, mathematics, engineering, and even philosophy. Written and edited by a clinician-scientist in the field, this book remains an excellent user's guide to t

Handbook of Functional MRI Data Analysis

Handbook of Functional MRI Data Analysis PDF

Author: Russell A. Poldrack

Publisher: Cambridge University Press

Published: 2024-02-08

Total Pages: 0

ISBN-13: 9781009481168

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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.

Handbook of Neuroimaging Data Analysis

Handbook of Neuroimaging Data Analysis PDF

Author: Hernando Ombao

Publisher: CRC Press

Published: 2016-11-18

Total Pages: 662

ISBN-13: 1482220989

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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.

Electrical Neuroimaging

Electrical Neuroimaging PDF

Author: Christoph M. Michel

Publisher: Cambridge University Press

Published: 2009-07-23

Total Pages: 249

ISBN-13: 0521879795

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An authoritative reference giving a systematic overview of new electrical imaging methods. Provides a comprehensive and sound introduction to the basics of multichannel recording of EEG and event-related potential (ERP) data, as well as spatio-temporal analysis of the potential fields. Chapters include practical examples of illustrative studies and approaches.

Introduction to Human Neuroimaging

Introduction to Human Neuroimaging PDF

Author: Hans Op de Beeck

Publisher: Cambridge University Press

Published: 2019-05-16

Total Pages: 369

ISBN-13: 1107180309

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An accessible primer for courses on human neuroimaging methods, with example research studies, color figures, and practice questions.

Fundamentals of Brain Network Analysis

Fundamentals of Brain Network Analysis PDF

Author: Alex Fornito

Publisher: Academic Press

Published: 2016-03-04

Total Pages: 494

ISBN-13: 0124081185

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Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain

Pattern Analysis of the Human Connectome

Pattern Analysis of the Human Connectome PDF

Author: Dewen Hu

Publisher: Springer Nature

Published: 2019-11-12

Total Pages: 258

ISBN-13: 9813295236

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This book presents recent advances in pattern analysis of the human connectome. The human connectome, measured by magnetic resonance imaging at the macroscale, provides a comprehensive description of how brain regions are connected. Based on machine learning methods, multiviarate pattern analysis can directly decode psychological or cognitive states from brain connectivity patterns. Although there are a number of works with chapters on conventional human connectome encoding (brain-mapping), there are few resources on human connectome decoding (brain-reading). Focusing mainly on advances made over the past decade in the field of manifold learning, sparse coding, multi-task learning, and deep learning of the human connectome and applications, this book helps students and researchers gain an overall picture of pattern analysis of the human connectome. It also offers valuable insights for clinicians involved in the clinical diagnosis and treatment evaluation of neuropsychiatric disorders.