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Published byJade Hardick Modified over 10 years ago
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Buttons in SPM5 Carolyn McGettigan & Alice Grogan Methods for Dummies 5 th April 2006
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Introducing the SPM5 User Interface Help in SPM5 Spatial Pre-processing in fMRI 1 st and 2 nd Level Analysis Overview
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SPM5 User Interface
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Preprocessing Analysis Inference
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SPM5 User Interface
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Current List of Jobs SPM5 User Interface
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Current List of Jobs Options available for currently highlighted object Current value of / information about highlighted object Save/Load as.mat files or XML (“load-xml”, “savexml”) Info about the meaning of current item SPM5 User Interface
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SPM5 Help
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Sample Data Set from SPM5 manual “Mother of All Experiments” (MoAE) Auditory fMRI data Single-subject Whole-brain BOLD/EPI images acquired on 2T Siemens MAGNETOM Vision system Each acquisition 64 contiguous slices (64x64x64 3mm x 3mm x 3mm voxels) 6.05s acquisition TR=7sec 96 acquisitions in total 16 blocks of 6 So each block 42 sec Functional data starts at acquisition 4 Advisable to discard initial few scans due to T1 effects Structural image also acquired Spatial Pre-Processing
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1.Realignment 2.Coregistration 3.Segmentation 4.Normalize 5.Smoothing Spatial Pre-processing
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Data are available from http://www.fil.ion.ucl.ac.uk/spm/data/ http://www.fil.ion.ucl.ac.uk/spm/data/ Create a new directory for data Create a subdirectory “jobs” Open MATLAB Get into the correct working directory Type “SPM fmri” If you’re using SPM for the first time, make sure you “Set Path”, under File in MATLAB. Enter the path to your SPM folder and select the “Add with Subfolders” option From start to finish…
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Click on “Realign” from drop-down menu Realignment
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Select “New Realign:Estimate and Reslice” Realignment Open “Realign:Estimate and Reslice” option Highlight Data and select “New Sesson” Highlight “Session” Select “Specify Files”
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Realignment Choose all of the functional images in the directory i.e. images beginning ‘fM000*.img’
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Realignment Save job file as e.g. “realign.mat” in your jobs directory Press “RUN”
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Realignment etc Mean image for use in coregistration Header files modified with orientation info
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Coregistration Click on “Coregister”
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Coregistration Click on “New Coreg:Estimate” Double-click on “Coreg:Estimate” Highlight “Reference Image” select mean fMRI scan meanfM00223_004.img from realignment Highlight “Source Image” select structural image sM00223_002.img SAVE as ‘coreg.mat’ Press “RUN”
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Effects: SPM implements a coregistration between structural and functional data that maximises mutual information SPM changes header of source file i.e. sM00223_002.hdr Coregistration
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Useful to check registration of ref and source images at this point Click “Check Reg” button Select your source and ref images as before Navigate images and inspect anatomical correspondence Coregistration
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Segmentation Click on “Segment”
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Segmentation Highlight Data field “Specify Files” select the subject’s registered structural image sM00223_002.img Optional extras: “Custom” menu For extra speed, though not optimal, you can reduce the number of Gaussians per class e.g. to [1 1 1 4]. Click on “Specify Text” to modify the values. SAVE as segment.mat RUN
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Effects: SPM creates grey and white matter images and a bias-field corrected structural image View with Check Reg Grey matter image is c1sM00223_002.img White matter image is c2sM00223_002.img Check reg against original structural sM00223_002.img Segmentation SPM also writes spatial normalisation and inverse spatial normalisation parameters to files in structural directory: sM00223_002_seg_sn.mat sM00223_002_seg_inv_sn.mat THESE CAN BE USED TO NORMALISE FUNCTIONAL DATA Grey matter image Original structural image
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Click on “Normalize” Normalize
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Select “Normalise:Write” Allows previously determined warps to be applied to a series of images Normalize Highlight “Data” Select new “Subject” Open “Subject” and highlight “Parameter File” Select sM00223_002_seg_sn.mat from Segmentation step Highlight “Images to Write” “Specify Files” Use filter to select all realigned functional images Type ^r.* in SPM file selector and click “Filt” Right-click “Select all” Done
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Open “Writing Options” Click “Voxel sizes”, then “Specifiy Values” Change values to [3 3 3] This writes images at a resolution closer to that at which they were acquired Normalize SAVE as “normalise.mat RUN
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Effects: SPM writes spatially normalised files to the functional data directory Normalised files have the prefix “w” Normalize
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Smooth Click on “Smooth”
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Open “Smooth” Smooth Select “Images to Smooth” select the spatially normalised files “wrfM00*.img” Highlight “FWHM” “Specify Values” Change [8 8 8] to [6 6 6] Data will be smoothed by 6mm in each direction SAVE as smooth.mat RUN
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Effects See right Normalised functional image above wrfM00223_004.img Smoothed image below swrf00223_004.img Note: SPM5 Manual says “smoothing step is unnecessary if you are only interested in Bayesian analysis of your functional data” Smooth
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fM00223_004.img Realign rfM00223_004.img Coregister Segment Normalise wrfM00223_004.img Smooth swrfM00223_004.img Overview Use SPM Help and the ? Button See SPM5 Manual for everything I’ve included today
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