echo "======================================================"
echo "                ICA for rs-fMRI data                  "
echo "         Author: Hanbing Lu, Ph.D., NIDA IRP          "
echo "    Referenced in: Acquistition of resting-state      "
echo " functional magnet resonance imaging data in the rat  "
echo "          Journal of Visual Experiments, 2021         "
echo "____________________________________________________  "

## This script uses AFNI formatted images as input and outputs an FSL melodic report
##
## Default settings: 
## --3dmerge: 1blur_fwhm (FWHM Gaussian blur) = 0.8
## --3dAutomask: clfrac (clip level fraction) = 0.7
## --melodic: d (dimensionality reduction into #num dimensions) = 15 independent components; 
##            Oall = output all
##            report = generate Melodic web report

echo "input AFNI dataset name (e.g. E8)"

read InDataset

## flip dimensions
3dLRflip -Y -prefix temp ${InDataset}+orig

# apply gaussian blur
rm -fr temp2*
3dmerge -doall -1blur_fwhm 0.8 -prefix temp2 temp+orig

## convert to nifti
rm -fr temp2.nii
3dAFNItoNIFTI temp2+orig

## get the mean image
rm -fr mean_image+orig*
3dTstat -mean -prefix mean_image temp2+orig

## generate mask image
rm -fr mask1+orig*
3dAutomask -prefix mask1 -clfrac 0.7 mean_image+orig

## convert mask to nifti
rm -fr mask1.nii
3dAFNItoNIFTI mask1+orig

## perform ICA
melodic --verbose -d 15 -m mask1.nii --Oall --report -i temp2.nii

mv temp2.ica  ${InDataset}.ica

## open melodic web report
firefox ${InDataset}.ica/report/00index.html

## clean up
rm -fr temp*
rm -fr mask1*
rm -fr mean_image+orig*