Hello,
I am currently working on a fMRI project where we have 22 participants. We used a resampled grey matter mask of TT_N27. Then we utilized 3dFWHMx, and 3dClustSim to create thresholds and activation maps.
#foreach subj(03 04 05 06 08 09 10 11 13 14 15 16 17 19 20 22 23 24 25 27 28 29)
#3dFWHMx -detrend -mask /media/yanglab/fMRI/WLW/ROI/re_TT_N27+tlrc -detrend /media/yanglab/fMRI/WLW/betas/errts.ss$subj+tlrc >>ss$subj.blur.errts.1D
#end
#1dcat ss*.1D >> allBlurs.1D
#rm ss*.1D
Then we used the acf parameters to calculate the cluster size:
#3dClustSim -mask re_TT_N27+tlrc -acf 0.5908 3.0496 10.0044 -niml -prefix CStemp
#3drefit -atrstring AFNI_CLUSTSIM_NN1_1sided file:CStemp.NN1_1sided.niml -atrstring AFNI_CLUSTSIM_MASK file:CStemp.mask -atrstring AFNI_CLUSTSIM_NN2_1sided file:CStemp.NN2_1sided.niml -atrstring AFNI_CLUSTSIM_NN3_1sided file:CStemp.NN3_1sided.niml -atrstring AFNI_CLUSTSIM_NN1_2sided file:CStemp.NN1_2sided.niml -atrstring AFNI_CLUSTSIM_NN2_2sided file:CStemp.NN2_2sided.niml -atrstring AFNI_CLUSTSIM_NN3_2sided file:CStemp.NN3_2sided.niml -atrstring AFNI_CLUSTSIM_NN1_bisided file:CStemp.NN1_bisided.niml -atrstring AFNI_CLUSTSIM_NN2_bisided file:CStemp.NN2_bisided.niml -atrstring AFNI_CLUSTSIM_NN3_bisided file:CStemp.NN3_bisided.niml \
This was the afni output:
<3dClustSim_NN1 ni_type=“10*float” ni_dimen=“29” commandline=“3dClustSim -mask re_TT_N27+tlrc -acf 0.5908 3.0496 10.0044 -niml -prefix CStemp” thresholding=“2-sided” nxyz=“80,95,75” dxyz=“2.000,2.000,2.000” fwhmxyz=“0.00,0.00,0.00” iter=“10000”
pthr=“0.1,0.09,0.08,0.07,0.06,0.05,0.04,0.03,0.02,0.015,0.01,0.007,0.005,0.003,0.002,0.0015,0.001,0.0007,0.0005,0.0003,0.0002,0.00015,0.0001,7e-05,5e-05,3e-05,2e-05,1.5e-05,1e-05” athr=“0.1,0.09,0.08,0.07,0.06,0.05,0.04,0.03,0.02,0.01” mask_dset_idcode=“AFN_aqZjbVd9FBYc_zvKKEDu3g” mask_dset_name=“./re_TT_N27+tlrc.HEAD” mask_count=“180142” >
…
In this output, we found a cluster size of 37 in the p=0.001 and α=0.05. And we are concerned whether it is too small. Do you have any suggestions?
PS: We used 4 mm FWHM blur in the preprocessing of subject data.
Thank you very much!
Wang