1st Edition

Handbook of Neuroimaging Data Analysis

    704 Pages 172 B/W Illustrations
    by Chapman & Hall

    702 Pages 172 B/W Illustrations
    by Chapman & Hall

    702 Pages 172 B/W Illustrations
    by Chapman & Hall

    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