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HANDBOOK OF NEUROIMAGING DATA ANALYSIS
Título:
HANDBOOK OF NEUROIMAGING DATA ANALYSIS
Subtítulo:
Autor:
OMBAO, H
Editorial:
CRC
Año de edición:
2016
ISBN:
978-1-4822-2097-1
Páginas:
662
119,00 €

 

Sinopsis

Features

Summarizes the state of the art in the statistical analysis of neuroimaging data
Provides statisticians with an introduction to important active issues in neuroimaging research
Offers a path for statisticians to contribute to this rapidly emerging research area in theoretical and applied statistics
Serves as both a textbook for topical courses in statistics and biostatistics and a comprehensive reference for Ph.D. students and researchers in statistics, biostatistics, psychology, neuroscience, biomedical engineering, electrical engineering, and computer science
Summary

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.



Table of Contents

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