Document Detail


To smooth or not to smooth? Bias and efficiency in fMRI time-series analysis.
MedLine Citation:
PMID:  10913325     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
This paper concerns temporal filtering in fMRI time-series analysis. Whitening serially correlated data is the most efficient approach to parameter estimation. However, if there is a discrepancy between the assumed and the actual correlations, whitening can render the analysis exquisitely sensitive to bias when estimating the standard error of the ensuing parameter estimates. This bias, although not expressed in terms of the estimated responses, has profound effects on any statistic used for inference. The special constraints of fMRI analysis ensure that there will always be a misspecification of the assumed serial correlations. One resolution of this problem is to filter the data to minimize bias, while maintaining a reasonable degree of efficiency. In this paper we present expressions for efficiency (of parameter estimation) and bias (in estimating standard error) in terms of assumed and actual correlation structures in the context of the general linear model. We show that: (i) Whitening strategies can result in profound bias and are therefore probably precluded in parametric fMRI data analyses. (ii) Band-pass filtering, and implicitly smoothing, has an important role in protecting against inferential bias.
Authors:
K J Friston; O Josephs; E Zarahn; A P Holmes; S Rouquette; J Poline
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Review    
Journal Detail:
Title:  NeuroImage     Volume:  12     ISSN:  1053-8119     ISO Abbreviation:  Neuroimage     Publication Date:  2000 Aug 
Date Detail:
Created Date:  2000-10-11     Completed Date:  2000-10-11     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  9215515     Medline TA:  Neuroimage     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  196-208     Citation Subset:  IM    
Copyright Information:
Copyright 2000 Academic Press.
Affiliation:
The Wellcome Department of Cognitive Neurology, Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Image Processing, Computer-Assisted / statistics & numerical data*
Magnetic Resonance Imaging / statistics & numerical data*
Models, Statistical

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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