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Statistical analysis of fMRI data
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Woolrich, Mark W., Beckmann, C. F., Nichols, Thomas E. and Smith, Stephen M. (2009) Statistical analysis of fMRI data. In: Filippi, Massimo, (ed.) fMRI techniques and protocols. Neuromethods (Vol.41). New York ; London : Humana Press, Inc., pp. 179-236. ISBN 9781603279185
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Official URL: http://dx.doi.org/10.1007/978-1-60327-919-2_7
Abstract
fMRI is a powerful tool used in the study of brain function. it can non-invasively detect signal changes in areas of the brain where neuronal activity is varying. This chapter is a comprehensive description of the various steps in the statistical analysis of fMRI data. This will cover topics such as the general linear model (including orthogonality, haemodynamic variability, noise modelling, and the use of contrasts), multi-subject statistics, and statistical thresholding (including random field theory and permutation methods).
Item Type: | Book Item | ||||
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Subjects: | Q Science > QA Mathematics R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) |
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Library of Congress Subject Headings (LCSH): | Brain -- Magnetic resonance imaging -- Statistics, Linear models (Statistics), Brain -- Imaging -- Statistical methods | ||||
Series Name: | Neuromethods | ||||
Publisher: | Humana Press, Inc. | ||||
Place of Publication: | New York ; London | ||||
ISBN: | 9781603279185 | ||||
Book Title: | fMRI techniques and protocols | ||||
Editor: | Filippi, Massimo | ||||
Official Date: | 1 September 2009 | ||||
Dates: |
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Number: | Vol.41 | ||||
Number of Pages: | 843 | ||||
Page Range: | pp. 179-236 | ||||
DOI: | 10.1007/978-1-60327-919-2_7 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access |
Data sourced from Thomson Reuters' Web of Knowledge
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