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

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 ...

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Publication status:
Published

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Authors


Salimi-Khorshidi, G More by this author
Nichols, TE More by this author
Journal:
NeuroImage
Volume:
54
Issue:
3
Pages:
2006-2019
Publication date:
2011-02-05
DOI:
EISSN:
1095-9572
ISSN:
1053-8119
URN:
uuid:3fd5beaf-1527-4855-b079-3e02b7c5094e
Source identifiers:
116935
Local pid:
pubs:116935

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