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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
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 | ||||
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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): | Cluster analysis, Brain -- Imaging -- Data processing | ||||
Journal or Publication Title: | NeuroImage | ||||
Publisher: | Elsevier | ||||
ISSN: | 1053-8119 | ||||
Official Date: | 1 February 2011 | ||||
Dates: |
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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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