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                                                        Installation

                                                               Usage

permits the specification of additional parameters:

    'summary_measure' :     choice of summary measure (across voxels) [{'mean'},'eigenvariate','weighted mean','weighted eigenvariate','median','sum','weighted sum','count','max',min']
    
    'level' :               summarize across [{'rois'},'clusters','peaks','voxels']
    
    'scaling' :             type of scaling (for timeseries extraction) [{'none'},'global','roi']
    
    'conjunction_mask':     filename of conjunction mask volume(s)
    
    'conjunction_threshold' absolute-threshold defining voxels within conjunction_mask [0] (e.g. conjunction_threshold=0 or conjunction_threshold={'raw', 0} keeps all voxels with mask values above zero within each ROI; conjunction_threshold={'voxels', 10} keeps only the 10 voxels with the highest values in the conjunction mask within each ROI; conjunction_threshold={'percent', .10} keeps only voxels with top 10% values in the conjunction mask within each ROI  
    
    'output_type' :         choice of saving output ['none','save','savefiles',{'saverex'}]
    
    'gui' :                 starts the gui [{0},1] 
    
    'disregard_zeros'       when datatype has no NaN representation treat 0 as NaN [0,{1}]
    
    'roi_threshold'         absolute-threshold defining voxels within cluster [0]
    
    'select_clusters'       asks user to select one or more clusters if multiple clusters exists within each ROI [{0},1]
    
    'selected_clusters'     (for 'select_clusters'=0) indexes of clusters to select (by default this value is empty and all of the clusters will be selected) 
    
    'dims' :                (for 'eigenvariate' summary measure only): number of eigenvariates to extract from the data
    
    'covariates' :          (for 'eigenvariate' summary measure only): covariates to be regressed-out before computing svd
    
    'pca' :                 (for 'eigenvariate' summary measure only): PCA decomposition 1 = first extract component represents mean signal, next components represent principal component decomposition of covariance matrix); 0 = components represent SVD decomposition of the second moment (X'*X) matrix [0,{1}] 
    
    'mindist' :             (for 'peak' level only): minimum distance (mm) between peaks 
    
    'maxpeak' :             (for 'peak' level only): maximum number of peaks per cluster
    
    'fsanatomical' :        (for ROIs defined on freesurfer cortical surfaces): subject-specific freesurfer-generated mri/T1.nii structural file 
    
    'output_files':         (for output_type 'save' or 'savefiles' only): cell array of files to create {'data.txt','data.mat','roi.tal','roi.img','roi#.img'}