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False positives in neuroimaging genetics using voxel-based morphometry data
2011
NeuroImage
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As VBM data exhibit spatially-varying smoothness, we used both non-stationary and stationary cluster size tests in our analysis. ...
Tests based on the size of spatially extended clusters of contiguous suprathreshold voxels are also widely used due to their typically increased statistical power. ...
Acknowledgments Matt Silver is supported by a grant from the Wellcome Trust. ...
doi:10.1016/j.neuroimage.2010.08.049
pmid:20849959
pmcid:PMC3063336
fatcat:sxmmevqkhjeotghjhlexprfmti
Increasing power for voxel-wise genome-wide association studies: The random field theory, least square kernel machines and fast permutation procedures
2012
NeuroImage
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In this paper we present a fast implementation of voxel-and cluster-wise inferences based on the random field theory to fully use the spatial information in images. ...
Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: Random field theory Voxel-wise inference Cluster size inference Nonstationarity Least ...
Based on early work on Gaussian random field theory (Adler, 1981; Aldous, 1989) , the theoretical basis for voxel-wise inferences , stationary cluster size inferences (Cao and Worsley, 2001; Friston ...
doi:10.1016/j.neuroimage.2012.07.012
pmid:22800732
pmcid:PMC3635688
fatcat:2tpy4wwuhzfdnmglfw5bvo6mcy
Statistical testing and power analysis for brain-wide association study
[article]
2016
bioRxiv
pre-print
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Therefore, we herein report the development of a rigorous statistical framework for connexel-wise significance testing based on the Gaussian random field theory. ...
It includes controlling the family-wise error rate (FWER) of multiple hypothesis testings using topological inference methods, and calculating power and sample size for a connexel-wise study. ...
60 based method [Mumford and Nichols, 2008] , and the method based on non-central random field 61 theory (ncRFT) [Hayasaka et al., 2007] . ...
doi:10.1101/089870
fatcat:fx6llunnxrfavgkqmtrcl7jx2q
Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data
2006
NeuroImage
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Cluster size limits for multiple probability thresholds were estimated using random field theory and validated with Monte Carlo simulation. ...
Operating within the framework of the FreeSurfer software package, we have implemented a surface-based version of the cluster size exclusion method used for multiple comparisons correction. ...
Random field theory estimates and Monte Carlo simulations of cluster size Cluster size limits for use with multiple comparisons correction were estimated using random field theory (Worsley et al., 1996 ...
doi:10.1016/j.neuroimage.2006.07.036
pmid:17011792
pmcid:PMC1785301
fatcat:c7fbnylbuvdffcy57l3xbrylly
Validating cluster size inference: random field and permutation methods
2003
NeuroImage
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Cluster size tests used in analyses of brain images can have more sensitivity compared to intensity based tests. ...
The random field (RF) theory has been widely used in implementation of such tests, however the behavior of such tests is not well understood, especially when the RF assumptions are in doubt. ...
The most widely used methods, however, are the ones based on the random field (RF) theory (Friston et al., 1994; Cao and Worsley, 2001) . ...
doi:10.1016/j.neuroimage.2003.08.003
pmid:14683734
fatcat:u4ynpcaagzfehelyo3ga7m2nwm
Controlling the familywise error rate in functional neuroimaging: a comparative review
2003
Statistical Methods in Medical Research
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In particular we do not consider inference on size of contiguous suprathreshold regions or clusters. ...
"Multiple comparisons" can allude to pairwise comparisons on a single model, where as in imaging a large collection of models is each subjected to a hypothesis test. 2 A FWE-corrected threshold is one ...
Acknowledgments The authors would like to thank Keith Worsley for many valuable conversations on random field theory. ...
doi:10.1191/0962280203sm341ra
pmid:14599004
fatcat:ouwkagnh3bfvfnaswr2tvqls3e
The expected behaviour of random fields in high dimensions: contradictions in the results of Bansal and Peterson (2018)
[article]
2021
bioRxiv
pre-print
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Bansal and Peterson (2018) found that in simple stationary Gaussian simulations Random Field Theory incorrectly estimates the number of clusters of a Gaussian field that lie above a threshold. ...
Using reproducible code we demonstrate that in their simulations Random Field Theory correctly predicts the expected number of clusters and therefore that many of their results are invalid. ...
Cluster size inference using Random Field Theory is based on the properties of null mean-zero homogeneous random fields thresholded at a given cluster defining threshold (CDT) to produce an excursion set ...
doi:10.1101/2021.01.21.427611
fatcat:sud3bagl4vfcrgp6tpiy7lnlxm
White matter lesion segmentation based on feature joint occurrence probability and random field theory from magnetic resonance (MR) images
2010
Pattern Recognition Letters
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The v 2 random field theory is used to determine the significance of a detected lesion and provides a strict statistical analysis to exclude small-sized false-positive lesions. ...
v 2 Random field theory a b s t r a c t Lesions of the brain's white matter are common findings in MR examinations of elderly subjects. ...
This approach is based on random field theory. ...
doi:10.1016/j.patrec.2010.01.025
fatcat:guiwkaw6gbdjllffnnkrh6jt7i
Probabilistic TFCE: A generalized combination of cluster size and voxel intensity to increase statistical power
2019
NeuroImage
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In this paper, we provide an estimation of these distributions based on Gaussian Random Field theory. ...
The core of pTFCE is a conditional probability, calculated based on Bayes' rule, from the probability of voxel intensity and the threshold-wise likelihood function of the measured cluster size. ...
Gorgolewski and Russell A. Poldrack (Department of Psychology, Stanford University, USA) for sharing the fMRI datasets used for the validation on real data. We are also thankful to Dr. ...
doi:10.1016/j.neuroimage.2018.09.078
pmid:30296561
pmcid:PMC6834440
fatcat:dinjsbkxfzbkdbjnpz5ikd3hl4
Statistical limitations in functional neuroimaging II. Signal detection and statistical inference
1999
Philosophical Transactions of the Royal Society of London. Biological Sciences
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In turn, random ¢eld, scale space, non-parametric and Monte Carlo approaches are reviewed, representing the most common approaches to statistical inference used in FNI. ...
Also, some general aspects of hypothesis testing and statistical inference are discussed. ...
This approximate result is based on the theory for smooth stationary Gaussian RFs (cf. below; Worsley & Vandal 1994 ) . ...
doi:10.1098/rstb.1999.0478
pmid:10466150
pmcid:PMC1692643
fatcat:lapdgfwdmvdj7brs22f5oqe3y4
Connectivity-based fixel enhancement: Whole-brain statistical analysis of diffusion MRI measures in the presence of crossing fibres
2015
NeuroImage
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Unfortunately, traditional 3D methods for smoothing and cluster-based statistical inference cannot be used for voxel-based analysis of these measures, since the local neighbourhood for smoothing and cluster ...
Recent work has focused on the development of more interpretable quantitative measures that can be associated with a specific fibre population within a voxel containing crossing fibres (herein we use fixel ...
Stationary random field theory cluster-based approaches can fail to control the FWER in such cases. ...
doi:10.1016/j.neuroimage.2015.05.039
pmid:26004503
pmcid:PMC4528070
fatcat:wybz2wrzanfrjkjewzgzjneo2q
Nonparametric permutation tests for functional neuroimaging: A primer with examples
2001
Human Brain Mapping
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with multiple comparisons corrections derived from random field theory. ...
For this data, the Bonferroni and random field results are very similar, and the nonparametric methods are more powerful. ...
corrections derived from random field theory. ...
doi:10.1002/hbm.1058
pmid:11747097
fatcat:fytq6xmepje45cznb3h4yakize
Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates
2016
Proceedings of the National Academy of Sciences of the United States of America
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By comparison, the non-parametric permutation test, which is based on a small number of assumptions, is found to produce valid results for voxel as well as cluster wise inference. ...
in particular, cluster size inference with a cluster defining threshold of p = 0.01 generates familywise error rates up to 60%. ...
This study would not be possible without the recent data-sharing initiatives in the neuroimaging field. ...
doi:10.1073/pnas.1602413113
pmid:27357684
pmcid:PMC4948312
fatcat:wzyjhdnuqjhulg3ry2okeellxi
Neuroanatomical substrates underlying contrast sensitivity
2019
Quantitative Imaging in Medicine and Surgery
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A multiple regression analysis was used to investigate the relationship between CS and GMV in a voxel-wise manner within the whole gray matter. ...
CS was assessed using the Mars Contrast Sensitivity Test. ...
Then, all reported brain regions were corrected P<0.05 at the cluster-level using the random field theory and the FWE correction, following the current standard (32) . ...
doi:10.21037/qims.2019.03.03
pmid:31032196
pmcid:PMC6462580
fatcat:js5thtzjmrc6vhqsqw6k6dqo5u
Automatic Estimation of Error in Voxel-Based Registration
[chapter]
2004
Lecture Notes in Computer Science
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A partial volume correction is then applied to estimate finer and sub-voxel displacements. ...
The analysis identifies the most significant scale of voxel clusters in the residual image for a coarse estimate of error. ...
Fig. 4 . 4 The number of false positive voxel clusters detected in a Gaussian random noise field as a function of the statistical significance level
Fig. 5 .Fig. 6 . 56 The recovered mean displacement ...
doi:10.1007/978-3-540-30135-6_100
fatcat:xxsaiba2qbfjvloludf4x74rby
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