Purkayastha, Sumitra, Wager, Tor D. and Nichols, Thomas E. (2008) Inferring individual differences in fMRI : finding brain regions with significant within subject correlation. Statistica Sinica, Vol.18 . pp. 1483-1500.

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Abstract

Functional magnetic resonance imaging studies answer questions about activation effects in populations of subjects. To begin with, this involves appropriate modelling of the fMRI data at the within-subject level. This is followed by extending the model to multiple subjects. There have been several attempts toward this extension, all of which have focused on inference on a single effect of interest (e.g., fMRI response for one type of working memory). However, the existing literature does not seem to say much about the relevant inferential procedures when multiple effects are of interest (e.g., response for four different types of working memory). In particular, the within subject dependence of one activation effect on another is an important issue with a multivariate repeated measures model. While most standard statistical methods regard such correlation as a nuisance, to be adjusted for and then ignored, we develop two simple and intuitive tests to make inference on the existence of such correlation. We demonstrate use of these tests by application to an fMRI study of attention switching. These tests are different not only from conventional tests for sphericity but also, more importantly, from the likelihood ratio test (LRT) of the relevant hypothesis. We also discuss what prompts us to look for tests different from the LRT.

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics R Medicine > R Medicine (General) R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions:	Faculty of Science, Engineering and Medicine > Science > Statistics Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH):	Magnetic resonance imaging -- Mathematical models, Attention -- Testing
Journal or Publication Title:	Statistica Sinica
Publisher:	Academia Sinica * Institute of Statistical Science
ISSN:	1017-0405
Official Date:	October 2008
Dates:	Date Event October 2008 Published
Volume:	Vol.18
Number of Pages:	18
Page Range:	pp. 1483-1500
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access

Data sourced from Thomson Reuters' Web of Knowledge

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