# FreeSurfer SUBJECTS_DIR # T1 images and FreeSurfer segmentations are expected to be found here setenv SUBJECTS_DIR /home/afrancis/Imaging # Output directory where trac-all results will be saved # Default: Same as SUBJECTS_DIR # set dtroot = /home/afrancis/Imaging/109123 # Subject IDs # set subjlist = (109123) # Default: Run analysis on all subjects # set runlist = (1) set dcmroot = /home/afrancis/Imaging set dcmlist = (109123/109123_7T_DWI_dir72_AP_SBRef.nii.gz) set bvecfile = /home/afrancis/Imaging/109123/109123_7T_DWI_dir72_AP.bvec set bvalfile = /home/afrancis/Imaging/109123/109123_7T_DWI_dir72_AP.bval # Perform correction for B0 inhomogeneity distortions? set dob0 = 2 # Perform correction for eddy-current distortions? # 0: No correction # 1: Perform registration-based correction with eddy_correct # 2: Perform model-based correction with eddy (default) set doeddy = 2 # Rotate diffusion gradient vectors to match eddy-current compensation? # Only used if doeddy = 1 or 2 # Default: 1 (yes) set dorotbvecs = 1 # Intra-subject (diffusion-to-T1) registration method # 1: Affine with a correlation ratio cost # 2: Affine with a mutual information cost # 3: Affine with a boundary-based cost (default) # set intrareg = 3 # Degrees of freedom for intra-subject registration # Can be 6 (rigid), 9 (rigid+scaling), or 12 (full affine) # Default: 6 for infants, 9 otherwise # set intradof = 6 # Maximum rotation angle (degrees) for intra-subject registration # Default: 3 for infants, 90 otherwise set intrarot = 90 # Inter-subject registration method # 1: Affine T1-to-T1 with a correlation ratio cost # 2: Affine T1-to-T1 with a mutual information cost # 3: Affine T1-to-T1 with a robust cost (default for infants) # 4: Nonlinear T1-to-T1 with CVS # 5: Nonlinear FA-to-FA with SyN (default) # set interreg = 5 # Use brain mask extracted from T1 image instead of low-b diffusion image? # Has no effect if there is no T1 data # Default: 1 (yes) set usemaskanat = 1 # Fractional intensity threshold for BET mask extraction from low-b images # This mask is used only if usemaskanat = 0 # Default: 0.3 set thrbet = 0.5 set pathlist = ( cc.bodyc cc.bodyp cc.bodypf cc.bodypm cc.bodyt cc.genu cc.rostrum cc.splenium mcp lh.af rh.af lh.ar rh.ar lh.atr rh.atr lh.cbd rh.cbd lh.cbv rh.cbv lh.cst rh.cst lh.emc rh.emc lh.fat rh.fat lh.fx rh.fx lh.ilf rh.ilf lh.mlf rh.mlf lh.or rh.or lh.slf1 rh.slf1 lh.slf2 rh.slf2 lh.slf3 rh.slf3 lh.uf rh.uf ) # Number of path control points # It can be a single number for all paths or a different number for each of the # paths specified in pathlist # Default: 7 for the forceps major, 6 for the corticospinal tract, # 4 for the angular bundle, and 5 for all other paths set ncpts = (7 7 5) # List of training subjects # This text file lists the locations of training subject directories # Default: $FREESURFER_HOME/trctrain/hcp/trainlist.txt set trainfile = $FREESURFER_HOME/trctrain/hcp/trainlist.txt # Number of "sticks" (anisotropic diffusion compartments) in the bedpostx # ball-and-stick model # Default: 2 # set nstick = 2 # Number of MCMC burn-in iterations # (Path samples drawn initially by MCMC algorithm and discarded) # Default: 200 set nburnin = 200 # Number of MCMC iterations # (Path samples drawn by MCMC algorithm and used to estimate path distribution) # Default: 7500 # set nsample = 7500 # Frequency with which MCMC path samples are retained for path distribution # Default: 5 (keep every 5th sample) set nkeep = 5 # Reinitialize path reconstruction? # This is an option of last resort, to be used only if one of the reconstructed # pathway distributions looks like a single curve. This is a sign that the # initial guess for the pathway was problematic, perhaps due to poor alignment # between the individual and the atlas. Setting the reinit parameter to 1 and # rerunning "trac-all -prior" and "trac-all -path", only for the specific # subjects and pathways that had this problem, will attempt to reconstruct them # with a different initial guess. # Default: 0 (do not reinitialize) # set reinit = 0