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--- biac:analysis:physiological [2011/10/25 19:19]
petty [AFNI]
+++ biac:analysis:physiological [2023/02/23 18:43]
@@ Line 1: / Line 1: @@
-====== Physiological Correction Methods ======
-Currently this assumes that you have recorded your physiological responses through Cigal.  Also, these types of corrections should be done **before** any type of slice-time correction or pre-processing.
-There's a python program, than can take your run's bxh header along with your cigal pdigm file to create various types of corrected text files to be used for physio corrections in a number of different packages.
-This tools uses various fields from the bxh and pdigm file to output "corrected" data.  "Corrected" here means accounting for potential time locking issues, different TR in the cigal recording verses the actual data acquisition, ddqs, etc.
-The python tool will call cigal functions directly, then output new text data in the format requested.
-<code>
-physio_create.py --help
-</code>
-<code>
-physio_create.py --bxh /path/to/run4.bxh --pdigm /path/to/pdigm5_12345_4_2 -f fsl --outpath /here/
-Program to produce formatted physiological data:
-    Data will be corrected and recreated from the pdigm file based on information from run data
-    BXH and PDIGM required
-    OUTPATH defaults to PWD
-    FORMAT: defaults to fsl
-        - fsl = cardio,resp,TR pulse ( 3 column file )
-        - npm = time,cardio,resp ( 3 column file )
-        - afni = cardiac.txt, respiration.txt
-Options:
-  -h, --help            show this help message and exit
-  -b FILE, --bxh=FILE   bxh file for run
-  -p FILE, --pdigm=FILE
-                        pdigm file for run
-  -f string, --format=string
-                        output format ( fsl,npm,afni )
-  -o PATH, --outpath=PATH
-                        location to store output files
-</code>
-===== AFNI =====
-Create the AFNI formated physiological text data.
-<code bash>physio_create.py -b Data/Func/20111025_12345/run004.bxh -p Data/Behav/12345/pdigm5_12345_4_2 -f afni</code>
-This would create my "cardiac.txt" and "respiration.txt".
-Now set-up build the regressors that will be used in afni with their matlab tool.
-<code matlab>
-addpath /usr/local/packages/MATLAB/afni/
-Opt.Respfile = '/tmp/there/respiration.txt'
-Opt.Cardfile = '/tmp/there/cardiac.txt'
-Opt.VolTR = 1.5
-Opt.Nslices = 34
-Opt.PhysFS = 100
-RetroTS(Opt)
-</code>
-The output will be "oba.slibase.1D", which is a text file containing regressors to remove from your data on a slice-by-slice basis.
-Convert your data to 4D nifti if you haven't already done so:
-<code bash>bxh2analyze --niigz -s input.bxh run004</code>
-Create the afni script which you will use to actually run the 3dretroicor functionality:
-<code bash>afni_proc.py -subj_id 12345 -dsets run004.nii.gz -blocks despike -do_block ricor -tcat_remove_first_trs 0 -ricor_regs *.slibase.1D -ricor_regs_nfirst 0 -ricor_regre
-ss_method 'per-run'</code>
-The result of the above command would be a tcsh script, which would run the despiking and 3dretroicor correction only.  Run it:
-<code bash>tcsh -xef proc.12345 |& tee output.proc.12345</code>
-There will be a resulting folder with all the afni data inside.  You can convert the afni BRIK to a nifti file, then wrap it with a BXH, then proceed to whatever you're doing afterwards:
-<code bash>
-#convert afni to nii, create bxh
-dAFNItoNIFTI 12345.results/pb02.12345.r01.ricor+orig.BRIK
-fslwrapbxh pb02.12345.r01.ricor.BRIK
-</code>
-Run the resting state pipeline:
-<code bash>resting_pipeline.py -f pb02.12345.r01.ricor.bxh -s 1,2,3,4,5,6,7 -p func --sliceorder odd</code>

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