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http://fmri.wfubmc.edu/software/Bpm
Software toolbox that performs SPM analysis with voxel-wise imaging covariates. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in Matlab with a user-friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely used T-field, has been implemented in the correlation analysis for more accurate results. Requirements: * SPM2 or SPM5 * MATLAB version 6.5 or higher
Proper citation: WFU Biological Parametric Mapping Toolbox (RRID:SCR_002613) Copy
A toolbox for Statistical Parametric Mapping (SPM) that provides an extensible framework for voxel level non-parametric permutation/randomization tests of functional Neuroimaging experiments with independent observations. SnPM uses the General Linear Model to construct pseudo t-statistic images, which are then assessed for significance using a standard non-parametric multiple comparisons procedure based on randomization/permutation testing. It is most suitable for single subject PET/SPECT analyses, or designs with low degrees of freedom available for variance estimation. In these situations the freedom to use weighted locally pooled variance estimates, or variance smoothing, makes the non-parametric approach considerably more powerful than conventional parametric approaches, as are implemented in SPM. Further, the non-parametric approach is always valid, given only minimal assumptions. The SnPM toolbox provides an alternative to the Statistics section of SPM.
Proper citation: Statistical non-Parametric Mapping (RRID:SCR_002092) Copy
http://www.nitrc.org/projects/asltbx
Tool box for arterial spin labeled perfusion MRI data processing. It is based on SPM and Matlab. More detailed documentation can be found in asl_perf_subtract.m, the main function for calculating CBF value. It supports 3D or 4D Analyze or Nifiti format and PASL, CASL, and PCASL data. It contains the code for calculating CBF and a set of SPM batch scripts for preprocessing and statistical analysis.
Proper citation: ASL data processing tool box (RRID:SCR_005997) Copy
https://www.nitrc.org/projects/imcalc/
A collection of functions with batch functionality for SPM: * user entered expression (one set of volumes); * binarize non-zero voxels; * binarize/threshold each image; * binarize non-zero voxels, sum, rebinarize; * voxelwise calculations on pairs (add sub mult div ... etc.); * flip sign of all non-zero voxels; * x-flip image along y = 0; * mask images to a template; * T-to-Z transform; * Winsorize (cap) extreme values; * Z-score transform of image relative to its global mean and SD; * write single voxels to a .nii; * create a cluster image; * split cluster image into constituent images; * write hemisphere masks from template; * homotopic calculations; * replace zeros with __; * pad image with extra voxels;
Proper citation: imcalc: SPM batch image calculator (RRID:SCR_000868) Copy
http://web.mit.edu/evelina9/www/funcloc.html
Spm-toolbox that performs region of interest (ROI)-level and voxel-level between-subjects analyses of functional MRI data, restricting the analyses to those areas identified using subject-specific functional localizers. Methods: The toolbox implements ROI-level and voxel-level analyses, and it implements an automatic cross-validation procedure when the localizers are not orthogonal to the effects-of-interest. ROI-level analyses allow manually defined parcels of interest, as well as automatically-defined ones (GcSS procedure, Fedorenko et al. 2010). General linear model second-level analyses are implemented, including ReML and OLS estimation of population level effects. Hypothesis testing includes standard univariate tests as well as multivariate tests for mixed within- and between-subject designs (T, F, and Wilks' lambda statistics) This toolbox requires Matlab and SPM5/SPM8.
Proper citation: SPM SS - fMRI functional localizers (RRID:SCR_009644) Copy
http://marsbar.sourceforge.net/
A toolbox for SPM which provides routines for region of interest analysis. Features include region of interest definition, combination of regions of interest with simple algebra, extraction of data for regions with and without SPM preprocessing (scaling, filtering), and statistical analyses of ROI data using the SPM statistics machinery.
Proper citation: MarsBaR region of interest toolbox for SPM (RRID:SCR_009605) Copy
Simple, menu-driven software toolbox for SPM 5/8 for exploratory data analysis for functional or structural images (.img / .nii) provides the user with several options: # a histogram of all non-zero voxel values in a brain image; # a scatter plot, Q-Q plot, or Bland-Altman plots comparing two images; # a surface plot of all voxel values at a particular axial slice; # easy Region of Interst (ROI)-based extraction of voxel values. Note: the toolbox calls various SPM 5/8 functions. The Q-Q plot function requires the MATLAB stats toolbox.
Proper citation: vis: SPM Visualized Statistics toolbox (RRID:SCR_002619) Copy
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