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Manual Computational Anatomy Toolbox - CAT12 Preprocessing Data QUICK START GUIDE ......................................................................................................................... 3 INTRODUCTION AND OVERVIEW ...................................................................................................... 5 GETTING STARTED ............................................................................................................................ 5 5 Download and Installation 6 Starting the Toolbox 6 Basic VBM analysis (overview) BASIC VBM ANALYSIS (DETAILED DESCRIPTION) ............................................................................... 9 9 9 First Module: Segment Data 11 Second Module: Display one slice for all images 11 Third Module: Check sample homogeneity 13 Fourth Module: Smooth 13 Fifth Module: Estimate Total Intracranial Volume (TIV) 14 15 Two-sample T-Test 16 Full Factorial Model (for a 2x2 Anova) 17 Multiple Regression (Linear) 18 Multiple Regression (Polynomial) 19 Full Factorial Model (Interaction) 20 Full Factorial Model (Polynomial Interaction) Building the Statistical Model 1

CAT12 for longitudinal data Adapting the workflows Altered Workflows for VBM-analyses 21 Estimating the Statistical Model 21 Checking for Design Orthogonality 24 Defining Contrasts SPECIAL CASES ................................................................................................................................ 28 28 30 Change Settings for Preprocessing 30 Preprocessing of Longitudinal Data 31 Statistical Analysis of Longitudinal Data in One Group 32 Statistical Analysis of Longitudinal Data in Two Groups 36 37 37 Customized Tissue Probability Maps 38 Customized DARTEL-template OTHER VARIANTS OF COMPUTATIONAL MORPHOMETRY .............................................................. 40 40 41 44 ADDITIONAL INFORMATION ON NATIVE, NORMALIZED AND MODULATED VOLUMES .................... 46 NAMING CONVENTION OF OUTPUT FILES ....................................................................................... 48 CALLING CAT FROM THE UNIX COMMAND LINE ............................................................................. 50 TECHNICAL INFORMATION ............................................................................................................. 50 Deformation-based morphometry (DBM) Surface-based morphometry (SBM) Region of interest (ROI) analysis 2

o Use "Full factorial" for cross-sectional data o Use "Flexible factorial" for longitudinal data o Use TIV as covariate (confound) to correct for different brain sizes and select centering with overall mean Quick start guide Errors during preprocessing Please use the Report Error function if any errors during preprocessing occurred. You have to first select the "err" directory that can be found in the folder of the failed data set and finally the indicated zip-file in the mail should be attached manually. Segment data using defaults (for longitudinal data use Segment longitudinal data). Estimate total intracranial volume (TIV) in order to correct for different head size and volume. VBM data • • • Check data quality using Check sample homogeneity for VBM data. • • Smooth data (suggested starting value 8mm). Specify 2nd-level model: o Select threshold masking with an absolute value of 0.1. This threshold can be increased in the final analysis to 0.2 or even 0.25. Estimate model. • • Check design orthogonality using the Review function in the SPM GUI. If you find a considerable correlation between TIV and any other parameter of interest it is recommended to rather use global scaling with TIV. Check the section “Building the statistical model” for more details. • Optionally Transform SPM-maps to (log-scaled) p-maps or correlation maps and apply thresholds. • Optionally try Threshold-Free Cluster Enhancement (TFCE) using the SPM.mat file of the already estimated statistical design. • Optionally Overlay selected slices. If you use log-p scaled maps from Transform & Threshold SPM-maps without any threshold use the following values as lower range for the colormap for thresholding: 1.3 (P<0.05); 2 (P<0.01); 3 (P<0.001). • Optionally estimate results for ROI analysis using Analyze ROIs. Here, the SPM.mat file of an already estimated statistical design will be used. Please check the online help “Atlas creation and ROI based analysis” for more information. 3

25mm for folding measures, use the default merging of hemispheres). • Check data quality using Check Sample Homogeneity for surface data. • Specify 2nd-level model: o Use "Full factorial" for cross-sectional data o Use "Flexible factorial" for longitudinal data o Additional surface data • Segment data and additionally select "Surface and thickness estimation" in "Writing options" (for longitudinal data use Segment longitudinal data). • Optionally extract additional surface parameters (e.g. suclus depth, gyrification index, cortical complexity). • Resample & Smooth Surfaces (suggested starting value 15mm for cortical thickness and 20- It is not necessary to use TIV as covariate (confound) because cortical thickness or other surface values are usually not dependent on TIV. It is not necessary to use any threshold masking. o Estimate Surface Model for (merged) hemispheres. • • Optionally Transform SPM-maps to (log-scaled) p-maps or correlation maps and apply thresholds. Optionally try Threshold-Free Cluster Enhancement (TFCE) using the SPM.mat file of the already estimated statistical design. • Optionally Display Surface Results for both hemispheres. Select results (preferably saved as log-p maps using “Transform and threshold SPM-surfaces”) in order to show render views of your results. • Optionally Extract ROI-based Surface Values such as thickness, gyrification or fractal dimension to provide ROI analysis. • Optionally estimate results for ROI analysis using Analyze ROIs. Here, the SPM.mat file of an already estimated statistical design will be used. Please check the online help “Atlas creation and ROI based analysis” for more information. 4

Introduction and Overview This manual is intended to help any user to perform a computational anatomy analysis using the CAT12 Toolbox. Although it will mainly focus on voxel-based morphometry (VBM) other variants of computational analysis such as deformation-based morphometry (DBM), surface-based morphometry (SBM), and region of interest (ROI) morphometric analysis will be also introduced and can be applied with a few changes. Basically the manual may be divided into four main sections: • Naturally, a quick guide of how to get started is given at the beginning. This section provides information how to download and install the software and start the Toolbox. Furthermore, a short overview on the steps of a VBM analysis is given. • A detailed description of a basic VBM analysis is subsequently given, which will guide the user step by step through the whole process – from preprocessing to the selection of contrasts. This description should provide all necessary information to analyze most studies successfully. • There are a few special cases of VBM analyses, for which the basic analysis workflow has to be adapted. These cases are longitudinal studies and studies in children or special patient populations. Relevant changes to a basic VBM analysis are described here and a description of how to apply these changes is provided. Importantly, only the changes are described – steps like for example quality control or smoothing are the same as in the basic analysis and not described a second time. • The manual closes with information on native, normalized and modulated volumes, which determines how the results may be interpreted. Furthermore an overview of the naming conventions used as well as technical information is given. Getting Started DOWNLOAD AND INSTALLATION • search path before The CAT12 Toolbox runs within SPM12. That is, SPM12 needs to be installed and added to your Matlab (see http://www.fil.ion.ucl.ac.uk/spm/ and http://en.wikibooks.org/wiki/SPM). installed Toolbox the CAT12 can be • Download (http://dbm.neuro.uni-jena.de/cat12/) and unzip the CAT12 Toolbox. You will get a folder named “cat12”, which contains various matlab files and compiled scripts. Copy the folder “cat12” into the SPM12 “toolbox” folder. 5

STARTING THE TOOLBOX • • • Start Matlab Start SPM12 (i.e., type “spm fmri”) Select “cat12” from the SPM menu (see Figure 1). You will find the drop-down menu between the “Display” and the “Help” button (you can also call the Toolbox directly by typing “cat12” on the Matlab command line). This will open the CAT12 Toolbox as additional window (Fig. 2). Figure 1: SPM menu Figure 2: CAT12 Window BASIC VBM ANALYSIS (OVERVIEW) The CAT12 Toolbox comes with different modules, which may be used for an analysis. Usually, a VBM analysis comprises the following steps (a) Preprocessing: 1. T1 images are normalized to a template space and segmented into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). The preprocessing parameters can be adjusted via the module “Segment Data”. 2. After the preprocessing is finished, a quality check is highly recommended. This can be achieved via the modules “Display one slice for all images” and “Check sample homogeneity”. 6

Both options are located in the CAT12 window under “Check Data Quality”. Furthermore, quality parameters are estimated and saved in xml-files for each data set during preprocessing. These quality parameters are also printed on the report PDF-page and can be additionally used in the module “Check sample homogeneity”. 3. Before entering the GM images into a statistical model, image data need to be smoothed. Of note, this step is not implemented into the CAT12 Toolbox but achieved via the standard SPM module “Smooth”. (b) Statistical analysis: 4. The smoothed GM images are entered into a statistical analysis. This requires building a statistical model (e.g., T-Tests, ANOVAs, multiple regressions). This is done by the standard SPM modules “Specify 2nd Level” or “Basic Models” in the CAT12 window covering the same function. 5. The statistical model is estimated. This is done by the standard SPM module “Estimate” (except for surface-based data where the function “Estimate Surface Models” should be used instead. 6. If you have used total intracranial volume (TIV) as confound in your model to correct for different brain sizes it is necessary to check whether TIV reveals a considerable correlation with any other parameter of interest and rather use global scaling as alternative approach. 7. After estimating the statistical model, contrasts will be defined to get the results of the analysis. This is done by the standard SPM module “Results”. The sequence of “preprocessing à quality check à smoothing à statistical analysis” remains the same for every VBM analysis, even when different steps are adapted (see “special cases”). A few words about the Batch Editor… − As soon as you select a module from the CAT12 Toolbox menu, a new window (the Batch Editor) will open. The Batch Editor is the environment where you will set up your analysis (see Figure 3). For example, an “<-X” indicates where you need to select files (e.g., your image files, the template, etc.). Other parameters have either default settings (which can be modified) or require input (e.g., choosing between different options, providing text or numeric values, etc.). − Once all missing parameters are set, a green arrow will appear on the top of the window (the current snapshots in Figure 3 show the arrow still in gray). Click this arrow to run the module or select “File à Run Batch”. It is very useful to save the settings before you run the batch (click on the disk symbol or select “File à Save Batch”). 7

− Of note, you can always find helpful information and parameter-specific explanations at the bottom of the Batch Editor window.1 − All settings can be saved either as .mat file or as .m script file and reloaded for later use. The .m script file has the advantage to be editable with a text editor. Figure 3: The Batch Editor is the environment where the analysis is set up. Left: For all settings marked with “<-X”, files have to be selected (“Select Files”). Right: Parameters can be edited and adapted (“Edit Value”). 1 Additional CAT12-related information can be found by selecting “VBM Website“ in the CAT12 window (Tools → Internet → VBM Website”). This will open a website. Here, look for “VBM subpages” on the right. 8

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