Description
Handbook of Neuroimaging Data Analysis
Chapman & Hall/CRC Handbooks of Modern Statistical Methods Series
Coordinators: Ombao Hernando, Lindquist Martin, Thompson Wesley, Aston John
Language: English
Subjects for Handbook of Neuroimaging Data Analysis:
Keywords
EEG Time Series; independent; Resting State Data; component; Familywise Error Rate; fmri; Multichannel EEG; false; Group ICA; discovery; Spontaneous EEG; rate; EEG Data; diffusion; EEG Signal; tensor; FWER; resting; Preprocessing Pipelines; state; Bold Signal; fMRI Data; EEG Channel; EEG Recording; ICA; GC; Canonical HRF; Effective Connectivity; HRF; Diffusion Mri; Var Model; Precision Matrix; Spectral Matrix; Partial Coherence; DTI Data
Publication date: 11-2019
· 17.8x25.4 cm · Paperback
Publication date: 11-2016
· 17.8x25.4 cm · Hardback
Description
/li>Contents
/li>Readership
/li>Biography
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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.
Overview. Imaging Modalities. Statistical Methods and Models.
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.
