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Releases: RIKEN-BCIL/HCPstyle-BOLDLagMappingAndCleaning

Lag mapping & deperfusioning for HARP protocol

17 Sep 07:44
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niimath is recommended over fslmaths/fsl5
https://github.com/rordenlab/niimath

Runs on MATLAB
FSL needs to be installed in addition to SPM12 for flexible volume smoothing

Lag mapping for non-human fMRI

27 Sep 04:12
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Email me for help if you encounter any issues: aso.toshihiko@gmail.com

Usage:
drLag4Drev7_longTR_monkey( 'test', 2.0,'fMRI2mm.nii.gz',5,0,1,4)

No cerebrum masking for extracting the initial seed timeseries
Tracking resolution is set to 0.5 sec irrespective of the TR of the acquision.

Make sure you have sufficient voxel-wise SNR in the high freq component. Please do:
niimath fMRI1mm -subsamp2offc fMRI2mm
for example, because you don't want to 1) be running out of memory and 2) fail to fill the voxels with reliable lag values.

If you want highly realible lag maps with a short scanning time (say 10 min), make it low resolution!

Revision 7

12 May 15:05
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Email me for help: aso.toshihiko@gmail.com

Now the scripts use niimath if it exists. If not, you must specify the path to fslmaths/FSL5.
Updated to work without any previous subfunctions.

Example usage:

  • Modify Line 56 to capture your fMRI directories and run
    Einsteining_v05( 'Sbj0001', '0.72', '1200', '9', '0.3', '0', '8', '0')
    or Einsteining_v05( 'Sbj0001', 0.72, 1200, 9, 0.3, 0, 8, 0)

function Einsteining_v05( Sdir, TR, Nvols, MaxLag, MinR, Fixed, Sm, onlyLag)
% Sdir: Subject directory name
% TR = in seconds
% Number of volumes per run
% MaxLag = 8 -> lag mapping up to -8TR / +8TR
% MinR = 0.2 -> Cross-correlogram peak < 0.2 will not be used (leaving such voxels as NaN)
% Fixed = 0 -> Recursive (flexible) LFO instead of Fixed-sLFO algorithm
% Spatial smoothing at 8mm FWHM
% onlyLag = 0 -> Lag mapping + deperfusioning (creating clean 4D dataset without perfusion lag structure)

Revision 6

27 Feb 07:11
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Report errors / corrections to aso.toshihiko@gmail.com.

Lag mapping & deperfusioning (Einsteining) Revision 6, 2023.

Improvements based on test-retest analyses for better reproducibility including smoothing with preservation of NaN voxels and skipping variance normalization to minimize the contribution of small-amplitude runs, etc.

Use fsl5 version if you have problems with niimath. You only need fslmaths from FSL5 because newer versions doesn't support subsamp2 on 4D images.

For non-multiband data, use BOLDLagMapping