Quick Start Guide 2 Computational Anatomy Toolbox - …

1 ManualComputational Anatomy Toolbox - cat12 Quick Start Guide2 Version Information4 Introduction and Overview10 Getting Started10 Download and Installation10 Starting the Toolbox11 Basic VBM Analysis (Overview)11 Overview of cat12 Processing14 cat12 Major Processing Steps14 cat12 Processing Steps in Detail15 Basic VBM Analysis (detailed description)17 Preprocessing Data17 First Module: Segment Data17 Second Module: Display slices (optionally)18 Third Module: Estimate Total Intracranial Volume (TIV)19 Fourth Module: Check sample19 Fifth Module: Smooth21 Building the Statistical Model22 Two-sample T-Test23 Full Factorial Model (for a 2x2 Anova)24 Multiple Regression (Linear)25 Multiple Regression (Polynomial)26 Full Factorial Model (Interaction)27 Full Factorial Model (Polynomial Interaction)

2 28 Estimating the Statistical Model291 Checking for Design Orthogonality29 Defining Contrasts31 Special Cases36 cat12 for longitudinal data36 Optional Change of Parameters for Preprocessing39 Preprocessing of Longitudinal Data39 Longitudinal Data in One Group40 Longitudinal Data in Two Groups42 Longitudinal Data in Two Groups with interaction of covariate by group44 Adapting the cat12 workflow for populations such as children48 Customized Tissue Probability Maps48 Customized Dartel- or Shooting-template49 Other variants of Computational morphometry53 Deformation-based morphometry (DBM)53 Surface-based morphometry (SBM)54 Region of interest (ROI) analysis57 Additional information on native, normalized and modulated volumes58 Naming convention of output files60 Calling CAT from the UNIX command line62 Technical information63 cat12 Citation66 References682 Quick Start GuideVBM data Segmentdata using defaults (useSegment LongitudinalDatafor longitudinal data).

3 Theresultingsegmentationsthatcannowbeuse dforVBMaresavedinthe"mri"folderandarenam ed"mwp1"forgraymatterand"mwp2" ,thedefaultsegmentationsforgraymatterare named"mwp1r"or"mwmwp1r" if the longitudinal model for detecting larger changes was selected. Get Total Intracranial Volume(TIV) to correct fordifferent brain sizes and the xml-files that are saved in the "report" folder. CheckthedataqualitywithCheckSampleforVBM data(optionallyconsiderTIVandageasnuisan ce variables).Select the gray or white matter segmentations from the first step. Smoothdata (recommended Start value 6-8mm1).Select the gray or white matter segmentations from the first step. Specifythe2nd-levelmodelwiththesmoothedg rayorwhitemattersegmentationsandcheck for design orthogonality and sample homogeneity: Use "Full factorial" for cross-sectional data.

4 Use "Flexible factorial" for longitudinal data. UseTIVascovariate(confound)tocorrectdiff erentbrainsizesandselectcenteringwith overall mean. ,refertothe section Building the statistical model . Estimatethe model and finally callResults. Optionally,TransformSPM-mapsto(log-scale d)p-mapsorcorrelationmapsandapplythresho lds. Optionally,youcantry Threshold-FreeClusterEnhancement (TFCE) estimated statistical design. Optionally, ,usethefollowingvaluesasthelowerrange for the colormap for the thresholding: (P< ); 2 (P< ); 3 (P< ). Optionally,estimatetheresultsforROIanaly sisusing , ,seetheonlinehelp Atlas creation and ROI based analysis .Additional surface data Segmentdataandalsoselect"Surfaceandthick nessestimation"under"Writingoptions"(for longitudinal data useSegment Longitudinal Data).

5 Thesurfacesdataaresavedinthefolder"surf" andarenamed"? *" Optionally,ExtractAdditionalSurfaceParam eters( ,gyrificationindex,corticalcomplexity). Resample&SmoothSurfaces(recommendedstart value12mmforcorticalthicknessand20-25mm for folding measures1, use the default mergingof hemispheres).Selectthe" *"datainthefolder"surf".Theresampleddata arenamed" *"for12mmsmoothed,mergedhemispheresthatw ereresampled to 32k template space. Check data quality of the resampled data usingCheckSamplefor surface data. Specify2nd-levelmodelfortheresampleddata andcheckfordesignorthogonalityandsample homogeneity: Use "Full factorial" for cross-sectional data. Use "Flexible factorial" for longitudinal data.

6 ItisnotnecessarytouseTIVasacovariate(con found)becausecorticalthicknessorother surface values are usually not dependent on TIV. It is not necessary to use any threshold masking. information, refer to the section Building the statistical model . Estimate the Surface Modeland finally callResults. Optionally,TransformSPM-mapsto(log-scale d)p-mapsorcorrelationmapsandapplythresho lds. Optionally,youcantry Threshold-FreeClusterEnhancement (TFCE) estimated statistical design. Optionally, SurfaceOverlay (preferablysavedaslog-pmapswith TransformandthresholdSPM-surfaces ortheTFCE_logmapswiththedifferentmethods for multiple comparison correction) to display rendering views of your results.

7 Optionally ExtractROI-basedSurfaceValues because this is now included in the segmentation pipeline. Optionally,estimatetheresultsforROIanaly sisusing , ,seetheonlinehelp Atlas creation and ROI based analysis .Errors during preprocessingPleaseusethe ReportError "err"directory,whichislocatedinthefolder ofthefailedrecord,andfinally,thespecifie d zip-file should be attached manually in the is for experienced users to filter sizes for Gaussian smoothing4 Duetothehighaccuracyofthespatialregistra tionapproachesusedinCAT12, ,forverysmallfiltersizesorevennofilterin g,youhavetoapplyanon-parametric permutation test such as the ( ). , the filter size should exceed the distance between a gyral crown and a sulcal data is not necessary if the minor version number of cat12 remains in version (1830) Changes in preprocessing pipeline (which affects your results compared to ) Volumetrictemplates,atlases, ''templates_MNI152 NLin2009cAsym'' or relocated.

8 Templates_ ->templates_MNI152 NLin2009 templates_ ->templates_MNI152 NLin2009 templates_ -> templates_MNI152 NLin2009 templates_ ->templates_MNI152 NLin2009 spm12/ Toolbox / -> templates_MNI152 NLin2009 spm12/ Toolbox / -> templates_MNI152 NLin2009 Thevolumetricatlaseshavebeenrevisedandar enowdefinedwithaspatialresolutionof1mm,e xceptfortheCobraatlas, (Cobra,LPBA40,IBSR,Hammers,Neuromorphome trics).Inaddition, (Julichbrain,Hammers) to previous versions. TheboundingboxoftheDartelandGeodesicShoo tingtemplateshasbeenchanged,resultingina slightlydifferentimagesizeofthespatially registeredimages( ).Therefore,olderpreprocesseddatashouldn ot(and cannot) be mixed with the new processed data (which is intended).

9 TransformedT1 Dartel/GSsurfacetemplatestothenewMNI152 NLin2009cAsymspace: templates_ ->templates_ templates_ ->templates_ templates_surfaces_32 ->templates_surfaces_32 templates_surfaces_32 ->templates_surfaces_32 Thesurfacepipelinehasbeenoptimizedtobett erhandledataatdifferentspatialresolution s. Olderpreprocessingpipelines( , , )wereremovedbecausetheirsupportbecame too difficult. Important new features TheMahalanobisdistanceinthequalitychecki snowreplacedbythenormalizedratiobetweeno verallweightedimagequality(IQR) (resultinginalownominalnumber/grade) after preprocessing. CAT12nowallowstheuseoftheBIDS directorystructureforstoringdata(notposs ibleforthelongitudinalpipeline).

10 (notpossible for the longitudinal pipeline). The"Basicmodels" :(1)cross-sectionaldataand(2) , (dependingonthecontrastdefined)to(1)remo vetheconfoundingeffectofstructuraldata( ,GM)onfunctionaldataor(2)examinetherelat ionship(regression) , can only be evaluated with the TFCE Toolbox . to remove non-brain areas. (ROI).Thistoolcanbeusedinordertoestimate ROIinformationforother(co-registered)mod alities( ,(rs)fMRI) ,aswellasthepossibility to define your own function. for very large samples. Addedstandalonetoolsforde-facing,DICOM import,andestimatingandsavingqualitymeas ures for large in version (1700) Changes in preprocessing pipeline (which affects your results compared to ) Geodesic shooting registration and surface estimation are now used by default.