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Faster permutation inference in brain imaging
2016
NeuroImage
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Permutation tests are increasingly being used as a reliable method for inference in neuroimaging analysis. However, they are computationally intensive. ...
The methods considered are freely available in the tool PALM -Permutation Analysis of Linear Models. ...
number of tests usually performed in brain imaging. ...
doi:10.1016/j.neuroimage.2016.05.068
pmid:27288322
pmcid:PMC5035139
fatcat:n7dqq5rrk5f6bfr5jzh4becsvi
Towards a faster randomized parcellation based inference
2017
2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI)
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A method designed to tackle this problem is Randomized Parcellation-Based Inference (RPBI), which has shown good empirical performance. ...
As a main conclusion, we advocate the use of (permuted) RPBI with ReNA, as it yields very fast models, while keeping the performance of slower methods. ...
Yet, in most of the experiments RPBI and TFCE display better performance. Regarding the computation time, the use of ReNA consistently yields faster inference algorithms. ...
doi:10.1109/prni.2017.7981503
dblp:conf/prni/IdroboVT17
fatcat:vtrlujazufhzrgtwhef7nwojcq
Intro to APACE – Accelerated Permutation Inference for ACE models
2017
Figshare
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Software documentation for APACE (Accelerated Permutation Inference for ACE models) ...
ACEfit_Par.NoImg
Set to 1 to optionally only compute summary measures and
suppress image-wise inference (faster when only summaries
are of interest). ...
(REQUIRED) ACEfit_Par.Pmask Brain mask image (if omitted, the whole volume/surface is analyzed). ...
doi:10.6084/m9.figshare.5572438.v1
fatcat:shn33eg2yjhyjkzjewuqzamzre
BROCCOLI: Software for fast fMRI analysis on many-core CPUs and GPUs
2014
Frontiers in Neuroinformatics
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BROCCOLI (running on a GPU) can perform non-linear spatial normalization to a 1 mm 3 brain template in 4-6 seconds, and run a second level permutation test with 10,000 permutations in about a minute. ...
These tests show that parallel processing of fMRI data can lead to significantly faster analysis pipelines. ...
Left: Voxel-level inference, the maximum t-test value is saved in each permutation. Right: Cluster-level inference, the extent of the largest cluster is saved in each permutation. ...
doi:10.3389/fninf.2014.00024
pmid:24672471
pmcid:PMC3953750
fatcat:5pyi7wjvmzbvnm4zth64rcthmy
Fast and powerful heritability inference for family-based neuroimaging studies
2015
NeuroImage
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We illustrate our method on fractional anisotropy measures in 859 subjects from the Genetics of Brain Structure study. ...
The large number of voxel- and vertex-wise measurements in imaging genetics studies presents a challenge both in terms of computational intensity and the need to account for elevated false positive risk ...
This work was also supported in part by a Consortium grant (U54 EB020403) from the NIH Institutes contributing to the Big Data to Knowledge (BD2K) Initiative, including the NIBIB and NCI. ...
doi:10.1016/j.neuroimage.2015.03.005
pmid:25812717
pmcid:PMC4463976
fatcat:ywalheb3lbdhrgrkrpookaotwm
Causal inference in audiovisual perception
2020
Journal of Neuroscience
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This functional magnetic resonance imaging (fMRI) study shows that the lateral prefrontal cortex plays a key role in inferring the environment's causal structure. ...
An unresolved question is how the brain solves this binding or causal inference problem and determines the causal structure of the sensory signals.In this functional magnetic resonance imaging (fMRI) study ...
which brain systems are critical for solving this causal inference problem. ...
doi:10.1523/jneurosci.0051-20.2020
pmid:32669354
pmcid:PMC7486655
fatcat:7iif35viircarndlxjcb7l3lxe
Analytic estimation of statistical significance maps for support vector machine based multi-variate image analysis and classification
2013
NeuroImage
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In this paper we show that the results of SVM-permutation testing can be analytically approximated. ...
However, identifying brain regions that significantly contribute to the classification/group separation requires computationally expensive permutation testing. ...
Supplementary data
Supplementary materials and code In order to enable readers to replicate results presented in this manuscript and perform further experiments of their own we are releasing the code ...
doi:10.1016/j.neuroimage.2013.03.066
pmid:23583748
pmcid:PMC3767485
fatcat:3vb543ktejfnzh4hd4nlcndi4i
Accelerated estimation and permutation inference for ACE modeling
2019
Human Brain Mapping
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Combined with permutation, we call this approach "Accelerated Permutation Inference for the ACE Model (APACE)" where ACE refers to the additive genetic (A) effects, and common (C), and unique (E) environmental ...
There are a wealth of tools for fitting linear models at each location in the brain in neuroimaging analysis, and a wealth of genetic tools for estimating heritability for a small number of phenotypes. ...
DATA ACCESSIBILITY We have developed a Matlab-based tool "Accelerated Permutation Inference for the ACE Model (APACE)", which provides different analysis approaches specialized for heritability inference ...
doi:10.1002/hbm.24611
pmid:31037793
pmcid:PMC6680147
fatcat:dyyqidmvk5dkfgxbl5weqnzwuu
Exact Topological Inference For Paired Brain Networks Via Persistent Homology
[article]
2017
bioRxiv
pre-print
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We present a novel framework for characterizing paired brain networks using techniques in hyper-networks, sparse learning and persistent homology. ...
The exact nonparametric statistical inference procedure is derived on testing monotonic graph theory features that do not rely on time consuming permutation tests. ...
We thank Yoonsuck Choe of Texas A&M University and and Daniel Rowe of Marquette University for valuable discussions on permutation tests. ...
doi:10.1101/140533
fatcat:i55uzwtrsvbxpbqn5oy7eooue4
Exact Topological Inference for Paired Brain Networks via Persistent Homology
[chapter]
2017
Lecture Notes in Computer Science
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We present a novel framework for characterizing paired brain networks using techniques in hyper-networks, sparse learning and persistent homology. ...
The exact nonparametric statistical inference procedure is derived on testing monotonic graph theory features that do not rely on time consuming permutation tests. ...
We thank Yoonsuck Choe of Texas A&M University and and Daniel Rowe of Marquette University for valuable discussions on permutation tests. ...
doi:10.1007/978-3-319-59050-9_24
pmid:29075089
pmcid:PMC5654491
fatcat:hzfj37axmnhozaks4demojhwei
Faster family-wise error control for neuroimaging with a parametric bootstrap
2017
Biostatistics
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2017 pre-print arXiv:1708.05037v1 fatcat:7qpttrsjyvfz3hyhmo4tvck3b4Other Versions
In neuroimaging, hundreds to hundreds of thousands of tests are performed across a set of brain regions or all locations in an image. ...
To our knowledge, only permutation joint testing procedures have been shown to reliably control the FWER at the nominal level. ...
Support for developing statistical analyses (RTS, TDS) was provided by a seed grant by the Center for Biomedical Computing and Image Analysis (CBICA) at Penn. ...
doi:10.1093/biostatistics/kxx051
pmid:29059370
fatcat:5zazib2s6ncbxash4xj7bzuhju
Power in Voxel-based Lesion-Symptom Mapping
2007
Journal of Cognitive Neuroscience
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Voxelbased approaches to mapping lesion-behavior correlations in brain-injured populations are increasingly popular, and have the potential to leverage image analysis methods drawn from functional magnetic ...
Voxelbased approaches to mapping lesion-behavior correlations in brain-injured populations are increasingly popular, and have the potential to leverage image analysis methods drawn from functional magnetic ...
Acknowledgments This work was supported by the Human Brain Project via R01MH073529 and R01DA014418, by the Neuro-cognitive Rehabilitation Research Network (ncrrn.org) via R24HD050836, P30NS045839, and ...
doi:10.1162/jocn.2007.19.7.1067
pmid:17583984
fatcat:ibygeguaxbcmfcuufo7g5jtrou
Brain surface contraction mapped in first-episode schizophrenia: a longitudinal magnetic resonance imaging study
2008
Molecular Psychiatry
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While these threshold-based permutation tests allow inferences about group differences within the defined regions, they do not control for multiple inference at the level of individual surface points. ...
In the halfway space, brain-cerebrospinal fluid boundary voxels for both baseline and follow-up brain images were determined by finding the edge voxels of tissue-classified brain images. ...
doi:10.1038/mp.2008.34
pmid:18607377
pmcid:PMC2773126
fatcat:awbtjwcgkfbo3ahtcvnbn2nmn4
Rapid Acceleration of the Permutation Test via Slow Random Walks in the Permutation Group
[article]
2019
arXiv
pre-print
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Other Versions
The permutation test is an often used test procedure in brain imaging. ...
Unfortunately, generating every possible permutation for large-scale brain image datasets such as HCP and ADNI with hundreds images is not practical. ...
In various brain imaging applications, computing statistic f for each permutation has been the main computational bottleneck [12, 16, 4] . ...
arXiv:1812.06696v2
fatcat:az57ja6kw5aaliqbmdsqequibu
Activation likelihood estimation meta-analysis revisited
2012
NeuroImage
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In summary, we thus replaced the previous permutation algorithm with a faster and more rigorous analytical solution for the null-distribution and comprehensively address the issue of multiple-comparison ...
In this report, we outline how this previous approach may be replaced by a faster and more precise analytical method. ...
Acknowledgments We acknowledge funding by the Human Brain Project (R01-MH074457-01A1; PTF, ARL, SBE), the DFG (IRTG 1328; SBE, DB) and the Helmholtz Initiative on Systems-Biology "The Human Brain Model ...
doi:10.1016/j.neuroimage.2011.09.017
pmid:21963913
pmcid:PMC3254820
fatcat:ivq7q7cbdze7rkxqo55ffhbuci
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