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'''# Unpack Data into the FSFAST Hierarchy using "unpackscmdir"'''
1. QA Check after unpacking
* '''A''' - Check unpacked data (time points, # of slices ..etc)
* '''B''' - Check FSFAST hierarchy in session folder
'''# Reconstruction Anatomical using "recon-all all"'''
1. Set SUBJECTS_DIR
2. QA Check
* '''A''' - Check talairach transformation
* '''B''' - Check skull strip, white matter & pial surface
* '''C''' - Re-run "recon-all" if edits are made
* '''D''' - Check hierarchy of reconstructed anatomical data
'''# Assembling the Data into the FSFAST Hierarchy'''
1. Make FSFAST basic hierarchy (only if data are not unpacked in FSFAST hierarchy)
2. Link to FreeSurfer anatomical analysis
* '''A''' - Make subjectname file in the session directory to link a subject's functional & structural data
3. Create a sessid file (text file with list of your sessions)in your Study DIR.
4. Create a Stimulus Schedule (Paradigm file) in bold folder (A "paradigm" file is a record of which stimulus was presented when & for how long. Each paradigm file has four columns:
* '''A''' - Stimulus onset time (sec)
* '''B''' - Condition ID code (0, 1, 2, ...)
* '''C''' - Stimulus Duration (sec)
* '''D''' - Stimulus Weight (usually 1)
'''# Preprocessing of fMRI Data ()'''
{{{
preproc-sess -s <subjid> -fwhm <#>
}}}
1. By default this will do motion correction, smoothing & brain masking
2. Quality Check (plot-twf-sess)
3. Examine additions to FSFAST hierarchy (in each run of bold dir):
* ''' ''' - f.nii (the raw data)
* ''' ''' - fmc.nii (motion corrected-MC)
* ''' ''' - fmcsm5.nii (MC & smoothed)
* ''' ''' - fmc.mcdat - text file with the MC parameters (AFNI)
* ''' ''' - mcextreg.bhdr - binary mask of the brain
'''# Function-Structure Registration'''
View unregistered
{{{
tkregister-sess -s <subjid> -regheader)
}}}
Run automatic registration
{{{
spmregister-sess -s <subjid>
}}}
Check automatic registration
{{{
tkregister-sess -s <subjid>
}}}
* '''A''' - Make edits if needed using scale as the last resort
Check talairach registration
{{{
tkregister2 --s <subjid> --fstal --surf
}}}
'''# First-Level (Group) Analysis '''
{{{
mkanalysis-sess gui
}}}
1. Setting up models of the task-related components
2. Setting up models of the nuisance components
3. Defining contrasts
4. Fitting the model
5. Making inferences
6. Input files: (*.par & fmcsm#)
'''# Analyze First Level '''
{{{
selxavg3-sess -s <subjid> -analysis <analysis name>
}}}
1. Examine additions to the FSFAST hierarchy (~bold/analysis):
* ''' ''' - beta.nii - regression coefficients
* ''' ''' - rvar.nii - residual error variance
* ''' ''' - mask.nii - mask (copy of bold/masks/brain.nii)
* ''' ''' - meanfunc.nii - mean functional image
* ''' ''' - fsnr.nii - functional SNR map
* ''' ''' - X.mat - design matrix (in matlab format)
* ''' ''' - dof - text file with degrees of freedom
* ''' ''' - fwhm.dat - smoothness estimate (Full-Width/Half-Max)
* ''' ''' - ~contrast folder/s:
* ''' ''' - ces.nii - contrast effect size (contrast matrix * regression coef)
* ''' ''' - cesvar.nii - variance of CES
* ''' ''' - sig.nii - significance map (-log10(p))
2. Visualization
* '''A''' - Volume-based visualization using "tkmedit-sess"
* '''B''' - Surface-based visualization using "tksurfer-sess"
'''# Higher-Level (Group) Analysis--Volume-based (MNI305/fsaverage)'''
1. Assemble the contrast Data using "isxconcat-sess"
{{{
isxconcat-sess -s <sessid> -analysis <analysis name> -c <contrast name> -o <outdir>
}}}
* '''A ''' - (~ output dir):
* ''' ''' - tal.meanfunc.nii (stack where each "time point" is the mean f image of each subject sampled in the MNI305 space)
* ''' ''' - tal.masks.nii (binary masks for all the subjects)
* ''' ''' - tal.fsnr.nii (functional SNR maps from each subject)
* ''' ''' - tal.mask.nii (single binary mask made from the intersection of the individuals)
* ''' ''' - ffxdof.dat (fixed-effects DOF across all subjects)
* ''' ''' - sessid.txt (list of sessions, the corresponding freesurfer subject name, & the DOF contributed by each subject))
* ''' ''' - ~contrast folder:
* ''' ''' - tal.ces.nii (contrast maps for each of the subjects)
* ''' ''' - tal.cesvar.nii (variance of the contrast for each subject (i.e., the square of the standard error). This variance is needed for fixed-effects & weighted random-effects analysis.)
* ''' ''' - "osgm" directory (one-sample-group-mean corresponds to a group design matrix that is simply a column of 1s. This will be used later in group analysis (i.e. in mri_gmfit))
2. Quality Assurance
* '''A''' - Check registration using "tkregister2"
* '''B''' - Check the individual masks using "tkmedit"
* '''C''' - Look at the functional SNR mapsusing "tkmedit"
3. Group GLM Analysis using "mri_glmfit"
* '''A''' - Random Effects
{{{
mri_glmfit --y tal.ces.nii --osgm --mask ../tal.mask.nii --glmdir tal.rfx.osgm --nii
}}}
* ''' ''' - Input: tal.ces.nii,tal.mask.nii
* ''' ''' - Output: tal.rfx.osgm, beta.nii, sig.nii & osgm folder
* '''B''' - Weighted Random Effects
{{{
mri_glmfit --y tal.ces.nii --osgm --glmdir tal.wrfx.osgm --nii --mask ../tal.mask.nii \
--wls tal.cesvar.nii
}}}
* ''' ''' - Similar to Random effects except that the first-level noise variances (tal.cesvar.nii) are passed
* '''C''' - Fixed Effects
{{{
mri_glmfit --y tal.ces.nii --osgm --glmdir tal.ffx.osgm --nii --mask ../tal.mask.nii \
--yffxvar tal.cesvar.nii --ffxdofdat ../ffxdof.dat
}}}
* ''' ''' - Also included --yffxvar, & -- ffxdofdat
4. Output & visualization
* '''A''' - First concatenate sig.nii files to a single file using "mri_concat"
* '''B''' - Visualize using "tkmedit"
5. Correction for Multiple Comparisons/Cluster Analysis using "mri_volcluster"
* '''A''' - Examine additions to the FSFAST hierarchy:
* ''' ''' - tal.rfx.osgm/osgm/cluster.sum (table shows the size of each cluster in voxels and mm^3, the talairach coordinate, the maximum significance in the cluster, & the clusterwise p-value (CWP))
* ''' ''' - cwsig.cluster.nii (map of the clusters with the voxel value equal to the -log10(pvalue))
* ''' ''' - sig.cluster.nii (original sig map with non-cluster voxels removed)
* ''' ''' - ocn.cluster.nii (map where the value at each voxel is replaced by the number of the cluster that the voxel is associated with)
'''# Higher-Level (Group) Analysis--Surface-based (MNI305/fsaverage)'''
1. Assemble the Data (isxconcat-sess)
{{{
isxconcat-sess -s <sessid> -analysis <analysis name> -c <contrast name> -o <outdir> -hemi <?h>
}}}
* '''A''' - Examine additions to the FSFAST hierarchy (~ output dir):
* ''' ''' - ?h.meanfunc.nii
* ''' ''' - ?h.mask.nii
* ''' ''' - ?h.fsnr.nii
* ''' ''' - ?h.ces.nii
* ''' ''' - ?h.cesvar.nii
2. Group GLM Analysis(mri_glmfit)"--surf fsaverage lh" added to volume based.)
* '''A''' - Random Effects
* '''B''' - Weighted Random Effects
* '''C''' - Fixed Effects
3. Output and visualization (mri_concat and tksurfer)
* '''A''' - Random Effects
* '''B''' - Weighted Random Effects
* '''C''' - Fixed Effects
4. Correction for Multiple Comparisons/Cluster Analysis (mri_volcluster)
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