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False positives in neuroimaging genetics using voxel-based morphometry data

Matt Silver, Giovanni Montana, Thomas E. Nichols
2011 NeuroImage  
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

Tian Ge, Jianfeng Feng, Derrek P. Hibar, Paul M. Thompson, Thomas E. Nichols
2012 NeuroImage  
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]

Weikang Gong, Lin Wan, Wenlian Lu, Liang Ma, Fan Cheng, Wei Cheng, Stefan Gruenewald, Jianfeng Feng
2016 bioRxiv   pre-print
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

Donald J. Hagler, Ayse Pinar Saygin, Martin I. Sereno
2006 NeuroImage  
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

S Hayasaka
2003 NeuroImage  
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

Thomas Nichols, Satoru Hayasaka
2003 Statistical Methods in Medical Research  
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]

Samuel Joseph Davenport, Thomas E Nichols
2021 bioRxiv   pre-print
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

Faguo Yang, Zuyao Y. Shan, Frithjof Kruggel
2010 Pattern Recognition Letters  
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

Tamás Spisák, Zsófia Spisák, Matthias Zunhammer, Ulrike Bingel, Stephen Smith, Thomas Nichols, Tamás Kincses
2019 NeuroImage  
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

K. M. Petersson, T. E. Nichols, J.-B. Poline, A. P. Holmes
1999 Philosophical Transactions of the Royal Society of London. Biological Sciences  
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

David A. Raffelt, Robert E. Smith, Gerard R. Ridgway, J-Donald Tournier, David N. Vaughan, Stephen Rose, Robert Henderson, Alan Connelly
2015 NeuroImage  
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

Thomas E. Nichols, Andrew P. Holmes
2001 Human Brain Mapping  
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

Anders Eklund, Thomas E. Nichols, Hans Knutsson
2016 Proceedings of the National Academy of Sciences of the United States of America  
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

Ying Yang, Yajun Wang, Cun Zhang, Jiajia Zhu, Yongqiang Yu
2019 Quantitative Imaging in Medicine and Surgery  
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]

William R. Crum, Lewis D. Griffin, David J. Hawkes
2004 Lecture Notes in Computer Science  
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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