Differences

This shows you the differences between two versions of the page.

--- biac:analysis:resting_pipeline [2012/07/06 12:34] – [Python/FSL Resting State Pipeline] gadde
+++ biac:analysis:resting_pipeline [2013/02/13 20:28] – [Step 7] petty
@@ Line 34: / Line 34: @@
                         run
   -p func, --prefix=func
                         prefix for all resulting images, defaults to name of
                         input
+  --t1=/path/to/BXH     bxh ( or nifti ) file for the anatomical T1
   -s 0,1,2,3, --steps=0,1,2,3
                         comma seperated string of steps. 'all' will run
@@ Line 59: / Line 60: @@
                         AC point of reference image if not using standard MNI
                         brain
-  --betfval=0.5         f value to use while skull stripping. default is 0.5
+  --betfval=0.4         f value to use while skull stripping. default is 0.4
+  --anatbetfval=0.5     f value to use while skill stripping ANAT. default is 0.5
   --lpfreq=0.08         frequency cutoff for lowpass filtering in HZ.  default
                         is .08hz
@@ Line 151: / Line 153: @@
   * the functional run is meaned across time with fslmaths, then bet is applied.  the resulting mask is then applied to the entire run of data
   * if you find that bet is doing a poor job finding the edges you can adjust the intensity threshold with **--betfval**
-    * this is equivalent of **-f** when actually running bet.  the default is 0.5, but smaller values will be more conservative in finding the edges of the brain ( ie: larger mask )
+    * this is equivalent of **-f** when actually running bet.  the default is 0.4 (same as feat), but smaller values will be more conservative in finding the edges of the brain ( ie: larger mask )
+  * if provided T1 anatomical is skull stripped. **--anatbetfval** is used to control intensity threshold, the default is 0.5 (same as feat)
 ==== Step 4 ====
   * normalize the data using flirt
@@ Line 159: / Line 161: @@
   * if your subject has already been normalized during standard pre-processing of other runs, please provide the flirt matrix from pre-stats with **--flirtmat** ( most likely example_func2standard.mat)
     * this will apply the previously determined flirt matrix to your functional data instead of trying to calculate a new matrix based on the functionals.  the matrix from pre-stats was likely calculated using a high-resolution anatomical, also this will assure that your resting state runs are in the same space as the other runs from your subject.
+  * if you've provided at T1 anatomical image then this sequence is followed:
+    * func-2-t1
+    * t1-2-standard
+    * flirt matrices are concatenated to create func-2-standard
+  * if no T1 is provided, then the functional is used for the flirt normalization
 ==== Step 5 ====
@@ Line 172: / Line 179: @@
 ==== Step 7 ====
   * if defaults are used, then the aal_MNI_V4 label file is used to extract the average timeseries for each of the 116 regions
+  * if --dvarsthreshold or --motionthreshold are specified, then the ROI-averaged timeseries are further filtered ("scrubbed") by removing timepoints that exceed the given thresholds
   * cross correlation coefficients are found for the entire matrix of 116x116 regions
   * this step produces 4 files:
@@ Line 194: / Line 202: @@
 * that is the zr_values from the subject.graphml displayed in matplotlib.  the cursor shows the intersecting region at the bottom, and if you click, time courses are displayed.  we're working on a release (cp - 3/30/12)
-For a beta version of the viewer:
+For the rs-pipeline viewer:
 <code>
-/usr/local/packages/biacpython/bin/beta_viewer.py --help
+/usr/local/packages/biacpython/bin/rspipe_viewer.py --help
 Usage:
-beta_viewer.py --graphml /path/to/subject.graphml --stat zrvalue
+rspipe_viewer.py --graphml /path/to/subject.graphml --stat zrvalue
 Program to display graphml output from resting_pipeline