SPM:
Use Sue Whitfield Gabrieli’s REX to extract the contrast values from a given region for each group, then compare in excel using a ttest (ttest) or matlab (ttest and ttest2).
FSL:
Use the inbuilt Featquery script to extract statistics (e.g., Contrast of Parameter Estimate Values [COPE, aka con values]) from your analysis. Type Featquery to bring up the GUI. You can choose from multiple structural atlases that are inbuilt, or use those you previously defined.
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FSL script to summarize the output from Featquery (run on each subject’s subject-level fixed effects model
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#!/bin/sh
#After running featquery on all participants’ single subject level output, paste the location of each group’s single subject feat dirs below (inputdirs) and then in the outputdirname past the name of the output folder written with the featquery. This will then output a text file with the MEAN output from each participant’s roi data.
#. /etc/fsl/fsl.sh
#output name for featquery (to be written to each person’s cope folder)
FQ_OUTPUTDIRNAME=”3b_crone2006_PAR-24-66_52_FSL_5mm”
OUTPUTFILE=”${FQ_OUTPUTDIRNAME}.txt” #ROI=’/net/rc-fs-nfs/ifs/data/Shares/DMC-Gaab2/data/GRAMMY_main/second_levels/roi/crone2006_8-12yearolds/2_crone2006_SMA-6_3_60_FSL_5mm.nii’
#Input directories.
INPUTDIRS='[Paths of group 1 feat directories]’
INPUTDIRS2='[Paths of group 2 feat directories]’
#COMPILE ALL OF THE COPE VALUES.
touch ${OUTPUTFILE}
for INPUTDIR in $INPUTDIRS ; do
#print file location
echo $INPUTDIR ‘\t’ >> ${OUTPUTFILE}
#print cope mean
awk ‘NF{printf(“\t%f\n”, $6)}’ ${INPUTDIR}/$FQ_OUTPUTDIRNAME/report.txt >> ${OUTPUTFILE}
done
echo “\nGroup 2\n” >> ${OUTPUTFILE}
for INPUTDIR2 in $INPUTDIRS2 ; do
#print file location
echo $INPUTDIR2 ‘\t’ >> ${OUTPUTFILE}
#print cope mean
awk ‘NF{printf(“\t%f\n”, $6)}’ ${INPUTDIR2}/$FQ_OUTPUTDIRNAME/report.txt >> ${OUTPUTFILE}
done
#Open this file in excel to run a ttest to compare the mean group percentage change.
npsy 