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Adjusting the effect of nonstationarity in cluster-based and TFCE inference

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Salimi-Khorshidi, Gholamreza, Smith, Stephen M. and Nichols, Thomas E. (2011) Adjusting the effect of nonstationarity in cluster-based and TFCE inference. NeuroImage, Vol.54 (No.3). pp. 2006-2019. doi:10.1016/j.neuroimage.2010.09.088 ISSN 1053-8119.

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Official URL: http://dx.doi.org/10.1016/j.neuroimage.2010.09.088

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Abstract

In nonstationary images, cluster inference depends on the local image smoothness, as clusters tend to be larger in smoother regions by chance alone. In order to correct the inference for such nonstationary, cluster sizes can be adjusted according to a local smoothness estimate. In this study, adjusted cluster sizes are used in a permutation-testing framework for both cluster-based and threshold-free cluster enhancement (TFCE) inference and tested on both simulated and real data. We find that TFCE inference is already fairly robust to nonstationarity in the data, while cluster-based inference requires an adjustment to ensure homogeneity. A group of possible multi-level adjustments are introduced and their results on simulated and real data are assessed using a new performance index. We also find that adjusting for local smoothness via a separate resampling procedure is more effective at removing nonstationarity than an adjustment via a random field theory based smoothness estimator.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
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): Cluster analysis, Brain -- Imaging -- Data processing
Journal or Publication Title: NeuroImage
Publisher: Elsevier
ISSN: 1053-8119
Official Date: 1 February 2011
Dates:
DateEvent
1 February 2011Published
Volume: Vol.54
Number: No.3
Number of Pages: 14
Page Range: pp. 2006-2019
DOI: 10.1016/j.neuroimage.2010.09.088
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: Research Councils UK (RCUK), GlaxoSmithKline (GSK)

Data sourced from Thomson Reuters' Web of Knowledge

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