Petersson, K. M. and Nichols, Thomas E.. (1999) Statistical limitations in functional neuroimaging. I. Non-inferential methods and statistical models. Philosophical Transactions of the Royal Society B: Biological Sciences, Vol.354 (No.1387). pp. 1239-1260. ISSN 0962-8436

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Abstract

Functional neuroimaging (FNI) provides experimental access to the intact living brain making it possible to study higher cognitive functions in humans. In this review and in a companion paper in this issue, we discuss some common methods used to analyse FNI data. The emphasis in both papers is on assumptions and limitations of the methods reviewed. There are several methods available to analyse FNI data indicating that none is optimal for all purposes. In order to make optimal use of the methods available it is important to know the limits of applicability. For the interpretation of FNI results it is also important to take into account the assumptions, approximations and inherent limitations of the methods used. This paper gives a brief overview over some non-inferential descriptive methods and common statistical models used in FNI. Issues relating to the complex problem of model selection are discussed. In general, proper model selection is a necessary prerequisite for the validity of the subsequent statistical inference. The non-inferential section describes methods that, combined with inspection of parameter estimates and other simple measures, can aid in the process of model selection and verification of assumptions. The section on statistical models covers approaches to global normalization and some aspects of univariate, multivariate, and Bayesian models. Finally, approaches to functional connectivity and effective connectivity are discussed. In the companion paper we review issues related to signal detection and statistical inference.

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Brain -- Imaging -- Statistical methods, Brain -- Imaging -- Data processing, Brain -- Imaging -- Mathematical models, Mathematical statistics
Journal or Publication Title:	Philosophical Transactions of the Royal Society B: Biological Sciences
Publisher:	The Royal Society
ISSN:	0962-8436
Date:	1999
Volume:	Vol.354
Number:	No.1387
Page Range:	pp. 1239-1260
Identification Number:	10.1098/rstb.1999.0477
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
URI:	http://wrap.warwick.ac.uk/id/eprint/38243

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