REX MANUAL
Contents
1. STEP 3 Specify additional output options By default rex will extract the average value within each ROI without scaling and without any additional masking Additional options include a Data level options ROI cluster voxel Each ROI file selected in step 1 characterizes a complete region of interest ROI Each ROI can be in turn formed by one or multiple clusters disjoint sets of voxels for example when using a wfu_pickatlas ROI containing multiple labels or when using a functionally defined ROI composed of several clusters of activation Last each cluster can be formed by one or multiple voxels Rex allows you to extact data separately for each voxel voxel level data to extract data collapsed separately across all voxels within each cluster cluster level data or to extract data collapsed across all of the voxels within the entire ROI ROI level data a Use extract data from each ROI to extract data separately from each ROI using the selected summary measure The default measure is the mean collapsed across multiple voxels A single output text file will be created for each ROI and it will contain the ROI level data for each source file in rows Using extract data from selected clusters is similar to extracting data from each ROI but if the ROI mask contains a disconnected set multiple clusters rex will allow the user to specify a subset of clusters and the ROI level summary measure will only include voxels2. format file Define a map wise functional ROI in SPM 1 2 Go to SPM Results select a contrast of interest and associated mask and thresholds Choose save to save an ROI NIFTI format file that includes all the significant voxels in the thresholded contrast 9 9
3. o G TD Declive_of_Vermis 0 03 1 80 u o TD Extea Nuclear 0 01 2 63 o o TD Fastiqium 0 01 0 53 D 0 ed Example of the rex results function used to perform SPM second level analyses on a complete set of anatomically defined regions Talairach Daemon areas Analyses are performed here on the average activation within each ROI Corrected p values represent a whole brain correction for these ROI based analyses NC BP eo Es Ke Effect sizes S S K ooo0isaenBus ouau aL beta Example of the rex results function used to perform multivariate second level analyses on one region of interest Anterior Cingulate Analyses are performed here on the first four eigenvariates characterizing the activation profiles within the selected ROI Corrected p values represent a multivariate correction of each of the individual eigenvariate results This example illustrates the application of multivariate analyses of ROI data showing between group differences that would be missed if only looking at the average activation within this ROI Last if the data sources have been defined using the SPM mat file you can click plots to further explore the effects of interest within the extracted ROIs The options here are the same as 7 9 REX manual 04 09 those encountered when using plots within the SPM results window including display contrast estimates and 90 C I and fitted and adjusted responses for both first level
4. selected TD Middle_Temporal_Gyrus ROIs Si es ies tite selected TD Superior_Temporal_Gyrus 02 Extract data from selected clusters ea o Egit Fy tia Pe te a Use conjunction mask x ptu ri we s 01 1 E i Exel me 5 10 15 20 25 30 35 40 volumes scans No scaling v t 0 04 an a 0 02 34 Y r R i o SAE ysy k 0 02 BP NC Sz Extract Results plots Effects of interest Sample output files TD Middle_Temporal_G TD Middle_Temporal_Gy _TD Superior_Temporal_Gyr TD Superior_Temporal_Gy yrus rex txt rus rex tal us rex txt rus rex tal one row per source file one row per voxel one row per source file one row per voxel 0 0630 36 2 50 0 0548 34 6 50 0 0080 34 2 50 0 0191 32 6 50 0 0220 32 2 50 0 0407 30 6 50 0 0326 32 2 50 0 0092 28 6 50 0 0145 34 2 50 0 0391 26 6 50 0 0135 36 2 50 0 0002 24 6 50 0 0114 38 2 50 0 0382 26 6 50 0 0034 36 4 50 0 0603 28 6 50 0 0641 34 4 50 0 0499 30 6 50 Example of rex data extraction and display performed on second level analysis data The source volumes are the subjects beta images with two anatomically defined ROIs The effects of interest represent three different subject groups The extracted data txt files contain the beta image values for each subject averaged across all the voxels within each ROI In addition if the data sources have been defined using the SPM mat file you can click Results to replicate the original voxel based SPM anal
5. within the selected clusters Use extract data from each cluster to extract data separately from each cluster within each ROI A separate output file will be created for each cluster and each ROI containing the cluster level data for each source file rows Use extract data from each voxel to extract the data separately from each voxel A separate output text file will be created for each ROI containing the voxel level data across all source files rows and voxels columns In this case the summary measure is disregarded and there is no collapsing across multiple voxels b Summary measure mean median weighted mean eigenvariates Note Summary measures only apply to ROI or cluster level extraction a Use mean or median to obtain the mean or median of the data across the selected voxels Use weighted mean to obtain a voxel weighted mean across the selected voxels not available when ROIs are defined using tal files The values of the ROI mask file at each voxel will be taken as the weights to be used when computing a weighted average across all selected voxels The mask values are normalized to sum to 1 and a weighted sum is computed Use eigenvariate with a chosen number of eigenvariates to summarize the data across voxels in terms of a singular value decomposition of the time series When choosing multiple eigenvariates the output text file for each ROJ cluster will contain each eigenvariabl
6. REX manual 04 09 REX MANUAL INTRODUCTION While exploring experimental questions based on prior anatomical hypotheses it is often useful to restrict the application of statistical models to specific brain regions In service of this goal SPM provides a wide range of methods for exporting image data values from image volumes at various stages of processing or statistical modeling The rex tool is designed to extend those capabilities to permit the efficient extraction of image values and time series from single voxels voxel clusters and cluster collections In addition to data extraction the rex tool performs ROI based analyses of functional data complementing SPM voxel based analyses While rex is part of the larger BIT toolbox it is a single MATLAB file that may be installed and used separately It provides capabilities to extract image data from either a single image file or multiple volumes such as a times series of images The extraction volume can be either a single ROI or a collection of spatially disjoint ROIs rex allows broad flexibility in the form of the extracted data as it can return the values of a single voxel a single cluster of voxels or a disjoint set of clusters Various options are provided to generate descriptive statistics from clusters of voxels including mean median voxel weighted mean and one or more eigenvariates To allow examination of experimental effects in units of percent signal change the resulting extracte
7. block designs or for second level analyses For event related responses you can also explore fitted responses and PSTHs 90 C Is adjusted data parametric responses and Volterra kernels 06 04 0 2 response mask02 Evert retsted responses N2 fitted response and PSTH fitted response and PSTH 0 2 0 5 10 15 20 25 peristimulus time secs 30 35 Example of the rex plots function used on first level analysis dataset in which the source volumes are individual scans comprising a time series extraction The data originate from an event related study using famous faces REF The event related PSTH plot results for one functionally defined ROI shown at the right Please report any bugs comments and or suggestions to Susan Whitfield Gabrieli sweg mit edu 8 9 REX manual 04 09 APPENDIX I Functional ROI Definition In situations where anatomical landmarks do not provide accurate guidance as to the boundaries of regional functional specialization so called functional localizers are sometimes used to identify brain regions specialized for a particular processing function These localizers usually take the form of an additional task whose associated neural activity modulations are believed to be orthogonal to the effects of interest related to the target tasks The patterns of activity detected by the localizer scan can then be thresholded to form a functional ROI that can be used to spatially con
8. d values can be scaled with respect to either the global brain mean or the cluster time series mean rex can be accessed as a MATLAB command line function or through a graphical user interface Extracted data can be saved as text and matlab data files or visualized with several data analysis and plotting options that allow convenient data exploration and hypothesis testing INSTALLATION 1 If it does not already exist create a directory named rex 2 Copy the rex m file and optionally the additional TD files into the rex directory 3 Start MATLAB 4 To add the rex directory to the MATLAB search path from the File menu at the top of the MATLAB window go to File gt Set Path gt Add Folder and then select the rex directory 5 Click Save and then Close The rex program is now at the beginning of the MATLAB search path STEP BY STEP instructions using the rex GUI To start the ROI extraction process at the MATLAB prompt type gt gt rex The rex GUI should now appear on the screen 1 9 REX manual 04 09 er Jone Selects source volumes EP not retectedt Selects regions of interest Extract data from each ROI X No conjunction mask Data extraction options Extract mean v No scaling aa Extracts data from source volumes Additional analysis plots A he regions of interest as NIFTI 1 image mask files img or nii formats or text files tal format For example if the goal is
9. e as a column and source files as rows as usual Eigenvariates are extracted using a Singular Value Decomposition SVD of the time series across all the voxels within each ROI cluster Each eigenvariate can 4 9 REX manual 04 09 be interpreted as a separate weighted mean of the data where the voxel weights are chosen to sequentially capture the maximum signal variance For example the first eigenvariate represents the weighted mean of the ROI data that results in the time series with maximum possible variance any other weighted mean will result in a combined signal with smaller variance Multiple eigenvariate extraction is useful as a data reduction technique for multivariate analyses of ROI data characterizing the time series within an ROI in terms of a small number of components that best capture the variability of responses across all of the voxels within this ROI c Scaling options global scaling within ROI scaling none If extracting time series data e g you chose a first level SPM mat file as source typically you would want to scale the original data within sessions to increase the interpretability of the data units in percent signal change a Use global scaling to scale the output data based on the global intracerebral mean SPM session specific grand mean scaling of the data averaged across all source files or within sessions when a SPM mat file is selected as source Use this option for example if yo
10. m these volumes or 2 Select one SPM mat file to extract data from volumes specified in a SPM design or to repeat one SPM analysis for the selected ROIs Selecting a single SPM mat file instead of the NIFTI format files is equivalent to selecting all of the image files that have been defined as the original data in the analyses specified in the SPM mat file more specifically the volumes listed in the SPM xY structure Any valid SPM mat file can be used as a source including ones resulting from either first level or second level analyses For example if you select the first level analysis SPM mat file for a given subject the data sources will be assumed to be all of the functional data files for this subject with one volume for each time point across all sessions included in the SPM mat file In this case rex will effectively extract all of the functional time series at the specified ROIs for this subject and allow you to perform first level analyses on the resulting time series If you select instead a second level analysis SPM mat file the data sources will be assumed to be the beta or con images specified in this analysis one volume per regressor per subject e g one contrast volume per subject for a standard second level t test analysis In this case rex will effectively extract the beta contrast values at the specified ROIs for each subject and allow you to perform second level analyses on the resulting data 3 9 REX manual 04 09
11. strain the analysis of the target tasks Functional ROIs may be defined in a number of different ways Define a spatially localized functional ROI using the spm_VOI function 1 2 3 4 5 6 Copy spm_VOI m to the spm8_first directory at the beginning of your MATLAB path The spm_VOI m file replaces one that is part of the core SPM8 distribution so it needs to be in the MATLAB search path before the version that came with SPM8 Go to SPM Results select a contrast of interest and thresholds Choose small volume Choose a Search volume using a sphere box or image If you have installed the modified version of spm_VOI m an additional figure window will pop up with a new glass brain that has all of the voxels that survived the small volume correction process The descriptive statistics for these voxels are located in the SPM graphics window However SPM doesn t update the original glass brain in the Graphics window You can now save the functional ROI in a tal file an ASCH file containing the XYZ locations of the ROI in MNI space if you are working with images that have been spatially normalized to the MNI space Define a spatially localized functional ROI using xj View 1 2 3 4 5 Type gt gt xjview atthe MATLAB command prompt Navigate to the cluster of interest Change the radio button from ALL to either Only and Only optional Choose Pick Cluster Save the ROI mask as a NIFTI
12. to use anatomical ROIs to guide the functional data extraction process you can use wfu_pickatlas to create anatomically defined ROIs that can be saved as img mask files Note that rex permits the use of labels within mask files in order to define multiple ROIs with a single img file Alternative methods to create functionally defined ROIs are outlined in Appendix I To select one or more ROIs 1 Inthe rex GUI click ROIs 2 Select one or more ROI files The supported file types are nii img and tal files When using NIFTI 1 image files nii or img ROIs will be defined by the location of those voxels where the value of the ROI image is greater than zero In addition ROI NIFTI 1 files containing multiple labels can also be used the REX tool is provided with a sample Talairach Daemon ROI file defining 55 anatomical areas in normalized space In contrast tal files are simply text files containing the spatial coordinates in mm of the voxels comprising an ROI the x y z coordinates are in columns and each voxel is a separate row use normalized coordinates e g MNI if the source volumes are normalized or subject coordinates if the source volumes are in native space 2 9 Mark Pearrow 5 13 09 9 48 PM Formatted Font 11 pt Font color Black REX manual 04 09 STEP 2 Selecting image data sources To define the source image files 1 Click Sources 2 Select one or more NIFTI image volume files to extract data fro
13. u wish to extract a time series of functional data in units of percent signal change referenced to the SPM default intracerebral mean of 100 Use within ROI scaling to scale the output data based on the local mean within ROI of the data averaged across all source files or within sessions when a SPM mat file selected as source Use this option if you wish to extract time series functional data in units of percent signal change referenced to the mean value of each ROI d Conjunction mask Optionally you can define an additional NIFTI format conjunction mask file Data will only be extracted from voxels contained in this global conjunction mask For example the Mask img file generated in SPM after estimating a model can be used to restrict all ROI data extraction to voxels within the analysis mask 5 9 REX manual 04 09 STEP 4 Extract and explore the data Click Extract to extract the data from the source image files at the voxels inside the specified regions of interest A text message box will be displayed containing the paths to the newly created data files and a results window will display the extracted data In addition to the output data files rex txt files containing the extracted data one file per ROI cluster rex will create mask files rex tal files indicating the locations in mm of the voxels corresponding to the ROI cluster associated with each data file Sample GUI Sources 41 tiles
14. yses for the extracted ROIJ cluster voxel data As in SPM results you will be prompted to select or define a contrast and rex will re estimate the model and display the statistical analysis results for all of the extracted data For each ROI cluster voxel selected rex will display the effect size for the chosen contrast T statistic uncorrected p value and FDR corrected p values multiple comparison corrections are applied to correct for multiple ROIs 6 9 REX manual 04 09 connectivity result 0 6 0 4 Effect sizes o N N T a E Jgdggg dgdggdgdgg 4 JHJ dddde 3 go 3 B o8ccc 9 godo 3 Soded soos og gt PO OO bopnnyss55 E Za o Duvu bono z EAFA REEE 3 S5e 3 82933 55555 2 sso 5 Sho sFssSecocF Boor E s5 io Cee sae F lt 3 Ion 3 lo 9 ae 2d g 82 5 S Sipcgss 80 2 ga 55 Sov S 45 c aac E Sl ges 5 Be os gt cpoegro E gezo 5 boa c o S83 9 g a a Oo arc o li S pase Baa ope 8 25 R 5 OBE 235 ecg 2 205 FHR 553 3 20s Bes 5 5 Bee g 5a POI beta T prunc TD Angular_ yrus 0 10 7 10 0 000000 D gt TD Anterior Cingulate 0 22 25 12 0 000000 oO TD Caudate aog 6 97 o oanooo o Z TD Cerebellar_Lingual 0 00 0 35 0 729391 0 7 l TD Cerahellar_Tonsil 000 0 23 o 871556 n TD Cingulate_Gyrus 0 04 5 26 0 000006 0 TD Claustrum aol 1 48 0 147857 o TD Culmen 0 01 1 34 0 188453 oO TD Culmen_of_Vermis 0 01 0 66 0 510599 T TD Cuneus 0 02 2 00 o 307 D TD Declive 0 05 5 38
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