rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: The
    title: Statistical Analysis of Functional MRI Data
  name:
    name part: Lazar, Nicole.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2008
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 299 p. online resource.
  abstract: One of the most intriguing questions facing modern science is the inner workings of the human brain. Functional magnetic resonance imaging (fMRI) is a powerful tool used to study the human brain in action. The data produced from mapping the active processes within the brain present many challenges to statisticians, computer scientists, engineers and other data analysts, due to their complex structure and the ever-increasing sophistication of the scientific questions being posed by researchers. This book represents the first in-depth discussion of statistical methodology, which it couples with an introduction to the scientific background needed to understand the data. Starting from the basic science - where fMRI data come from, why they are so complicated, and the role statistics can play in designing and interpreting experiments - the book gives a detailed survey of the numerous methods that have been applied in the last fifteen years. The analysis of fMRI data features many of the major issues of concern in modern statistics, such as high dimensionality, multiple testing, and visualization. The array of techniques examined in the book ranges from the simple two-sample t-test and the general linear model to hierarchical spatiotemporal models, multivariate methods such as principal components analysis, and Bayesian approaches as they have been used in fMRI. Software, including descriptions of the most popular freeware packages and their capabilities, is also discussed. This book offers researchers who are interested in the analysis of fMRI data a detailed discussion from a statistical perspective that covers the entire process from data collection to the graphical presentation of results. The book is a valuable resource for statisticians who want to learn more about this growing field, and for neuroscientists who want to learn more about how their data can be analyzed. Nicole A. Lazar is Professor of Statistics at the University of Georgia and affiliated faculty of t…
  table of contents: The Science of fMRI -- Design of fMRI Experiments -- Noise and Data Preprocessing -- Statistical Issues in fMRI Data Analysis -- Basic Statistical Analysis -- Temporal, Spatial, and Spatiotemporal Models -- Multivariate Approaches -- Basis Function Approaches -- Bayesian Methods in fMRI -- Multiple Testing in fMRI: The Problem of #x201C;Thresholding#x201D; -- Additional Statistical Issues -- Case Study: Eye Motion Data.
  note: by Nicole Lazar.
  subject:
    topic: Medicine
  subject:
    topic: Neurosciences
  subject:
    topic: Radiology
  subject:
    topic: Bioinformatics
  subject:
    topic: Statistics
  subject:
    topic: Psychology
    topic: Methodology
  subject:
    topic: Psychological measurement
  subject:
    topic: Medicine & Public Health
  subject:
    topic: Imaging / Radiology
  subject:
    topic: Neurosciences
  subject:
    topic: Statistics for Life Sciences, Medicine, Health Sciences
  subject:
    topic: Bioinformatics
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Psychological Methods/Evaluation
  classification: R895-920
  classification: 616.0757
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Statistics for Biology and Health
  identifier: 9780387781914
  identifier: http://dx.doi.org/10.1007/978-0-387-78191-4
  record info:
    record creation date: 100301
    record change date: 20151204174335.0
    record identifier: 978-0-387-78191-4