glm for fmri data analysis - dimitri van de...

Getting Started AUDIO 1st level The Batch Interface

GLM for fMRI data analysisLab Exercise 1

March 15, 2013

Medical Image Processing Lab

Medical Image Processing Lab GLM for fMRI data analysis

http://miplab.epfl.ch

http://www.epfl.ch

http://miplab.epfl.ch


Outline

1 Getting Started

2 AUDIO 1st levelPreprocessingModel Specification, Review and EstimationInference and Results

3 The Batch Interface

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Getting the Software and Data

● get the SPM software package and the two data sets fromhttp://miplab.epfl.ch/teaching/micro-513/download/ or from the the direct linksbelow

● SPM toolkit

● Dataset (single subject)

● For this practical, three files are required:spm8.zipglm data1.zip

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from http://miplab.epfl.ch/teaching/micro-513/download/

http://miplab.epfl.ch/teaching/micro-513/download/spm8.zip

http://miplab.epfl.ch/teaching/micro-513/download/glm_data1.zip


fMRI Data Set

AUDIOsingle subject auditory data, 16 blocks, TR=7s, 1st level analysis, SPM8 manualChapter 28, available at http://www.fil.ion.ucl.ac.uk/spm/data/auditory/

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http://www.fil.ion.ucl.ac.uk/spm/data/auditory/


Medical Imaging Datatypes

DICOM (Digital Imaging and Communications in Medicine)

● file name suffix .dcm

● one file per slice

● meta information stored in every file

● vendor-specific meta-information

● standard for archiving in hospital environment

● incompatible with SPM8

ANALYZE

● file name suffix header/matrix .hdr,.img

● header contains voxel-to-world mapping

● matrix contains the raw data matrix

● compatible with SPM8

NIfTI (Neuroimaging Informatics Technology Initiative)

● file name suffix .nii

● matrix and voxel-to-world mapping in one file

● standard format of SPM8

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Start SPM8

● extract glm spm8.zip into /tmp

● verify that there is a folder /tmp/spm8

● add SPM8 to the Matlab path andstart it

% add SPM8 path to Matlab path v a r i a b l eaddpath ( genpath ( '/tmp/spm8 ' ) ) ;% s t a r t SPM8 g r a p h i c a l u s e r i n t e r f a c espm

● choose fMRI

Figure : SPM8 modality selection window.

● alternatively, start fMRI mode directlyafter adding path

% s t a r t d i r e c t l y i n fMRI modespm ( ' fMRI ' ) ;

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SPM8 Interface

● access the most usedfunctions

● status messages, progressbar, selections, etc.

● view results, images, etc.

Figure : SPM8 “Menu” (top-left), “Interactive” (bottom-left) and“Graphics” (right) window.

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File Selection Window

● one click to select/deselect files

● Ed button allows manual change or enteringof path

● Done button confirms selection

● keeps history of previously visited paths

● regexp-like filtering

● works also in scripts, e.g. files=spm select;

● current Matlab path is the default path

Figure : SPM select dialog.

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Inspect the Data

AUDIOsee SPM8 manual, chapter 28, for detailed tutorialusing this data set

● Decompress glm data1.zip into /tmp.

● Verify that there is a folder/tmp/GLMLAB/AUDIO

● Browse the files, there is one folder containingthe structural image (i.e. sM00223) and onefolder for the functional volumes (i.e.fM00223).

● start the check registration tool fromcommand line

% check t h e image r e g i s t r a t i o n q u a l i t ys p m c h e c k r e g i s t r a t i o n

● or click Check Reg button

● choose one or more images, e.g. one functionaland the structural

Figure : Functional and structuralimages before co-registration.

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Preprocessing

Headers, Pre-, and Suffixes

SPM functions modify the data in different ways

● change affine world-to-voxel mapping stored in header *.hdr

● write new file, often pre- or suffixed

Prefixes

r* re-sliced and usually also realignedmean* mean imagec1* gray matterc2* white matterc3* cerebro-spinal fluidm* bias-field corrected structural imagew* warped (non-linearly transformed) image, e.g. into MNIs* spatially smoothed image

Suffixes

* seg sn.mat non-linear forward transformation from subject to MNI space* seg inv sn.mat non-linear reverse transformation from MNI to subject space

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Preprocessing

Preprocessing Overview

Preprocessing StepInputs Outputs

Realign (Estimate & Reslice)

Coregister (Estimate)

Segmentation

Normalise (Write)

Smooth

fM00223 *.{img,hdr}

meanfM00223 004.{img,hdr}sM00223.{img,hdr}

sM00223 004.{img,hdr}

sM00223 seg sn.mat

rfM00223 *.{img,hdr}

wrfM00223 *.{img,hdr}

rfM00223 *.{img,hdr}meanfM00223 004.{img,hdr}

sM00223 002.hdr

c{1,2,3}sM00223 002.{img,hdr}sM00223 002 seg sn.mat

sM00223 002 seg inv sn.mat

msM00223 002.{img,hdr}wmsM00223 002.{img,hdr}

wrfM00223 *.{img,hdr}

swrfM00223 *.{img,hdr}

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Preprocessing

Spatial Normalization

Realignment

● rigid-body transform (translation and rotation)

● within modality

● within subject

Co-registration

● affine transform (translation, rotation and scaling)

● across different modalities

● within same or across subjects

Normalize

● non-linear invertible transformation

● usually to reference space, i.e. MNI

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Preprocessing

1st Level Analysis

Dataset AUDIO /tmp/GLMLAB/AUDIO/

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Preprocessing

Realignment of functional volumes

Perform realignment of the volumes of the timeseries to the mean image.

● select Realign (Est & Res) from the

Realign pull-down menu

● highlight data, select New Session , then

highlight the newly created Session option.

● Select Specify Files and use the SPM file

selector to choose all of your functional imagesfM000*.img. There should be 96 files

● Save the job file as eg. ./jobs/realign.m.

● Press the ▶ button in the batch editor

● headers will be rewritten

● mean image meanfM00223 004.img will becreated

Figure : Rigid body realignmentparameters.

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Preprocessing

Co-registration

Co-register the structural to the mean functionalimage.

● Select Coregister (Estimate) from the

Coregister pulldown menu.

● Highlight Reference Image and then select

the mean fMRI scan from realignmentmeanfM00223 004.img.

● Highlight Source Image and then select the

structural image sM00223 002.img.

● Press the Save button (floppy disk symbol)and save the job as coreg.m.

● Then press the ▶ button.

● Verify that alignment is correct.

Figure : Image coregistration result.

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Preprocessing

Segmentation

Create tissue probability maps of gray matter(GM), white matter (WM) and cerebro-spinal fluid(CSF), and obtain normalization parameters towarp image into MNI space.

● Press the Segment button.

● Highlight the Data field and then select thesubjects registered anatomical imagesM00223 002.img.

● Highlight . Cerebro-Spinal Fluid and choose

Native Space .

● Save the job file as segment.m, and then press▶ button.

● Open the tissue probability mapsc1sM00223 002.img (GM),c2sM00223 002.img (WM),c3sM00223 002.img (CSF), andmsM00223 002.img (bias-field corrected T1).

Figure : Segmentation result.

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Preprocessing

Normalized

Normalize volumes of time series into MNI spaceand re-slice to 3mm isotropic voxel size.

● Select Normalise (Write) from the

Normalise pull-down menu.

● Highlight Data , select New Subject .

● Highlight Parameter File and select thesM00223 0020 seg sn.mat.

● Highlight images to write and select all ofthe realigned functional images rfM000*.img

and the structural image sM00223 0020.nii.

● Open Writing Options , and change

Voxel sizes from [2 2 2] to [3 3 3].

● Save the job as normalise.m and then pressthe ▶ button.

Figure : wmsM00223 0020.img (top)and single subject T1 template/spm8/canonical/single subj T1.nii

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Preprocessing

Smoothing

Apply spatial smoothing with isotropic Gaussianfilter with 6mm FWHM.

● Press Smooth button.

● Select Images to Smooth and then select the

spatially normalised files created in the lastsection i.e. ^wrf.*

● Highlight FWHM and change [8 8 8] to [6 66]. This will smooth the data by 6mm in eachdirection.

● Save the job as smooth.m and press the ▶button.

Figure : wrfM00223 004.img (top) andswrfM00223 004.img (bottom)

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Model Specification, Review and Estimation

Model Specification

To avoid T1 effects in the initial scans of an fMRI time series we discarding the firstcycle (12 scans, 04-15), leaving 84 scans, image files 16-99.

● Press Specify 1st-level button.

● Open the Timing parameters option.

● Highlight Units for design and select Scans .

● Highlight Inter-scan interval and enter “7”.

● Highlight Data and Design and select New Subject/Session .

● Open the newly created Subject/Session option.

● Highlight Scans and use SPM’s file selector to choose the 84 smoothed,normalised functional images ie. swrfM00223 {016..099}.img. (use ^s.*).

● Highlight Conditions and select New condition .

● Open the newly created Condition option. Highlight Name and enter “active”.

High-light Onsets and enter “6:12:84”. Highlight Durations and enter “6”.

● Create a directory named results.

● Highlight Directory and select the results directory you just created.

● Save the job as specify.m and press the ▶ button.

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Review

Y =Xβ + ε (1)

Y: observed signal, X: regressors, β: parameter estimates, ε: zero-mean Gaussiannoise

Figure : Design matrix. Figure : Orthogonality. Figure : Explore session 1.

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Estimation

● Press the Estimate button.

● Highlight the Select SPM.mat option and then choose the SPM.mat file saved inthe classical subdirectory.

● Save the job as estimate.m and press the ▶ button.

● SPM will write a number of files into the selected directory including an SPM.mat

file.

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Inference and Results

Contrast Prompt

● Press Results .

● Select the SPM.mat file created in the lastsection.

● This will invoke the contrast manager.

● Select Define new contrast . One sided maineffects for the active condition (i.e., aone-sided t-test) can be specified as “1”(active > rest) and “-1” (rest > active).

● Select the contrast name e.g., “active > rest”.

● Press Done .

Figure : Contrast prompt.

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Inference and Results

Thresholded Statistical Parametric Map

● Select “sections” from the overlays pulldownmenu.

● Choose wmsM00223 002.img as background.

Figure : Statistical parametric map ofAUDIO single subject activation(p<0.05, FWE).

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The Batch Interface

Batch interface allows to define processing pipelineslinked by dependencies.

● Press Batch .

● Choose menu “File” then “Open File ..”

● Select realign.m, coregister.m andsegment.m (in this order).

● Select the Coregister: Estimate module and

then Reference Image .

● Press Dependency , highlight

Realign: Estimate & Reslice: Mean Image ,

and then OK.

● Select the Segment module, highlight Data ,

press Dependency , highlight

Coregister: Estimate: Coregistered Images

and Press OK .

Figure : Batch editor including the firstthree steps of the preprocessingpipeline.

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Preprocessing Overview

View of the various processing steps as a single box with only few in- and outputs.Preprocessing StepInputs Outputs

PreprocessingfM00223 *.{img,hdr}

sM00223 004.{img,hdr} swrfM00223 *.{img,hdr}

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Resources

● SPM8 Documentation, http://www.fil.ion.ucl.ac.uk/spm/doc/

● Friston, K.J., 2007. Statistical parametric mapping, the analysis of functionalbrain images. Academic Press.

Acknowledgements Thanks to Ahmed Abdulkadir and Jonas Richiardi for helping inputting together this lab exercise.

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http://www.fil.ion.ucl.ac.uk/spm/doc/

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