Freesurfer Abridged: Difference between revisions
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# Bold file preparation | # Bold file preparation | ||
#* Semcat processing | #* Semcat processing | ||
#** | #** In terminal, <code> matlab &</code> | ||
#** | #** In matlab, <code>startup_smp12</code> | ||
#** | #** | ||
#* LDT processing | #* LDT processing | ||
#** In terminal, <code>matlab &</code> | |||
#** nii_4D_drop_vols('f.nii', [# vols to drop-- see #LINK>]) | |||
#** set_TR(2.047, [1 2 3 4 5 6], 'f.nii') | |||
#** d=datenum('DD-Mmm-YYYY') (e.g. '05-Oct-1997') | |||
#** subj_ID='0183' | |||
#** FSTSExtractor('prefix', 'LDT_', 'subject', subj_ID, 'run', i, 'tr', 2.047, 'volumes_dropped', <initial # drop vols>, 'date', d) | |||
#*** This step must be completed for each f.nii file in each bold folder | |||
#*** IT IS VERY IMPORTANT to look at what volumes to drop. It will likely not be the same for each bold file, unless it is a newer LDT participant. You can find more information #LINK here. | |||
# Analysis | # Analysis | ||
#* cd to subject folder | |||
#* mkanalysis.sh | |||
# Contrasts | # Contrasts | ||
#* cd to subject folder | |||
#* Run <code>mkcontrast.sh</code> | |||
# Pre-processing | # Pre-processing | ||
#* Run <code>preproc-sess -per-run -fwhm 6 -surface self lhrh -fsd bold -s FS_<subj_ID></code> | |||
# Selxavg | # Selxavg | ||
#* Run <code>selxavg3-sess -s <subjectname> -analysis <analysis path></code> | |||
#* Analysis path is where your LDT.?h.sm6 folders are. | |||
# (Optional) Clut and Subparcellation | # (Optional) Clut and Subparcellation | ||
#* Run <code>clut.sh FS_<subj_ID></code> | |||
#* Run <code>subpar.py FS_<subj_ID></code> | |||
# Blobs | # Blobs | ||
== Timeseries Analysis == | == Timeseries Analysis == |
Revision as of 13:24, 8 December 2017
Setting Up
- Note: I am using FS_0184 (semcat) as an example; fill in the parts specific to FS_0184 with the parts specific to your subject
This is an abridged version of the more detailed list provided elsewhere in the wiki.
Structural
- Slicer
- In terminal,
Slicer &
- Load data brainmask.nii
- Save data as brainmask.mgz
- Results: creates brainmask.mgz file
- In terminal,
- Autorecon 1
- In terminal,
autorecon1_SC.sh FS_0184
- Don't bother editing after this step; skip to autorecon 2
- Result: populates mri folder (includes "T1.mgz")
- In terminal,
- Autorecon 2
- In terminal,
autorecon2_SC.sh FS_0184
- Editing
- One terminal,
tksurfer FS_0184 lh inflated
- In another terminal,
tkmedit FS_0184 brainmask.mgz -aux T1.mgz -surfs
- Look for any noticable spikes in the tksurfer brain and edit the brainmask (tkmedit). See wiki page for details; this is the most labor intensive part of anatomical so make sure you're doing it right.
- One terminal,
- Results: creates lh.cortex.label and rh.cortex.label in label folder
- In terminal,
- Autorecon 3
- In terminal,
autorecon3_SC.sh FS_0184
- Editing
- In terminal,
tksurfer -annot aparc FS_0184 lh pial
- If needed, reference
tksurfer -annot aparc fsaverage lh pial
- Repeat with right hemi
- Make sure to EXPORT ANNOTATION! Do not "save overlay!"
- Again, be sure to see the autorecon3 page
- In terminal,
- Result: populates label folder (includes "lh.aparc.annot" and "rh.aparc.annot")
- In terminal,
Functional
- Bold file preparation
- Semcat processing
- In terminal,
matlab &
- In matlab,
startup_smp12
- In terminal,
- LDT processing
- In terminal,
matlab &
- nii_4D_drop_vols('f.nii', [# vols to drop-- see #LINK>])
- set_TR(2.047, [1 2 3 4 5 6], 'f.nii')
- d=datenum('DD-Mmm-YYYY') (e.g. '05-Oct-1997')
- subj_ID='0183'
- FSTSExtractor('prefix', 'LDT_', 'subject', subj_ID, 'run', i, 'tr', 2.047, 'volumes_dropped', <initial # drop vols>, 'date', d)
- This step must be completed for each f.nii file in each bold folder
- IT IS VERY IMPORTANT to look at what volumes to drop. It will likely not be the same for each bold file, unless it is a newer LDT participant. You can find more information #LINK here.
- In terminal,
- Semcat processing
- Analysis
- cd to subject folder
- mkanalysis.sh
- Contrasts
- cd to subject folder
- Run
mkcontrast.sh
- Pre-processing
- Run
preproc-sess -per-run -fwhm 6 -surface self lhrh -fsd bold -s FS_<subj_ID>
- Run
- Selxavg
- Run
selxavg3-sess -s <subjectname> -analysis <analysis path>
- Analysis path is where your LDT.?h.sm6 folders are.
- Run
- (Optional) Clut and Subparcellation
- Run
clut.sh FS_<subj_ID>
- Run
subpar.py FS_<subj_ID>
- Run
- Blobs