1st Edition
Handbook of Neuroimaging Data Analysis
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.
Overview
Introduction
Imaging Modalities
Positron Emission Tomography: Some Analysis Methods
John Aston
Structural Magnetic Resonance Imaging
Wes Thompson
Diffusion Magnetic Resonance Imaging
Hongtu Zhu
A Tutorial for Multisequence Clinical Structural Brain MRI
Ciprian Crainiceanu
Principles of Functional Magnetic Resonance Imaging
Martin Lindquist
Electroencephalography (EEG): Neurophysics, Experimental Methods, and Signal Processing
Ramesh Srinivasan
Statistical Methods and Models
Image Reconstruction in Functional MRI
Daniel Rowe
Statistical Analysis on Brain Surfaces
Moo Chung
Neuroimage Preprocessing
Stephen Strother
Linear and Nonlinear Models for fMRI Time Series Analysis
Tingting Zhang
Functional Neuroimaging Group Studies
Bertrand Thirion
Corrections for Multiplicity in Functional Neuroimaging Data
Nicole Lazar
Functional Connectivity Analysis for fMRI Data
Ivor Cribben
Multivariate Decompositions in Brain Imaging
Ani Eloyan
Effective Connectivity and Causal Inference in Neuroimaging
Martin Lindquist
Network Analysis
Cedric Ginestet
Modeling Change in the Brain: Methods for Cross-Sectional and Longitudinal Data
Phil Reiss
Joint fMRI and DTI Models for Brain Connectivity
Dubois Bowman
Statistical Analysis of Electroencephalograms
Hernando Ombao
Advanced Topics for Modeling Electroencephalograms
Hernando Ombao
Biography
Hernando Ombao is Professor in the Department of Statistics at the University of California, Irvine and Fellow of the American Statistical Association. Martin Lindquist is Professor in the Department of Biostatistics at Johns Hopkins University and Fellow of the American Statistical Association. Wesley Thompson is Associate Professor in the Department of Psychiatry at the University of California, San Diego and Lead Scientist at the Institute of Biological Psychiatry, Mental Health Services, Copenhagen, Denmark. John Aston is Professor in the Statistical Laboratory at the University of Cambridge and Fellow of the American Statistical Association.
"Handbook of Neuroimaging Data Analysis is a great source to help you get started . . . If you find a particular modality that interests you, just email one of the authors in the book who also works on data analysis within that modality. They are all friendly and helpful, and they will point you to sources of publically available data."
~Timothy D. Johnson"These chapters are primarily written by statisticians, but the book is nicely balanced by contributions from biomedical engineers, psychologists, and cognitive scientists. . . I recommend this book to statisticians interested in learning about neuroimaging and contributing to its growth."
~Journal of the American Statistical Association