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--- biac:analysis:physiological:cigal_pdigm [2022/01/20 14:45]
cmp12 [This topic does not exist yet]
+++ biac:analysis:physiological:cigal_pdigm [2023/02/23 18:43]
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-These types of corrections should be done **before** any type of slice-time correction or pre-processing.
-===== physio_run.py =====
-There is currently a tool for running AFNI-based correction of functional image data using physiological data.  In the future it may support FSL-based correction.
-<code>
-physio_run.py --help
-</code>
-<code>
-Usage:
-physio_run.py /path/to/run4.bxh /path/to/pdigm5_12345_4_2 OUTPUTPREFIX [ -f FORMAT ]
-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
-    OUTPUTPREFIX is the prefix for the physio-corrected output
-    FORMAT: what pipeline to use, only supports 'afni' for now (default)
-Options:
-  -h, --help            show this help message and exit
-  -f string, --format=string
-                        output format ( afni )
-</code>
-''physio_run.py'' runs ''physio_create.py'' under the hood to write physiological data in the format AFNI requires (see below for how to run ''physio_create.py'' yourself to create data usable by FSL), and then runs various AFNI tools to actually create the physio-corrected image data.
-The outputs will be OUTPUTPREFIX.bxh, OUTPUTPREFIX.nii.gz, OUTPUTPREFIX_cardiac.txt and OUTPUTPREFIX_respiration.txt.  OUTPUTPREFIX.bxh can be used as the input for ''resting_pipeline.py''.
-===== physio_create.py =====
-The underlying tool used by ''physio_run.py'' to create the regressors is ''physio_create.py''.  It takes an input image 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 tool uses various fields from the bxh and pdigm file to output "corrected" (physiological) data/regressors.  "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 to do the corrections, 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/ --hz 100
-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
-    HZ sampling rate
-    FORMAT: defaults to fsl
-        - fsl = cardio,resp,TR pulse ( 3 column file )
-        - npm = time,cardio,resp ( 3 column file )
-        - afni = cardiac.txt, respiration.txt, script.m
-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 )
-  --hz                  sampling rate is hz ( 100 )
-  -o PATH, --outpath=PATH
-                        location to store output files
-</code>
-===== AFNI details =====
-This section details the steps that the tool ''physio_run.py'' (described above) does for you automatically.
-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 --hz 100 </code>
-This would create my "cardiac.txt" and "respiration.txt", and a MATLAB script script.m that will create the regressors, and has the following contents:
-<code matlab>
-addpath /usr/local/packages/MATLAB/afni/
-Opt.Respfile = '/path/to/respiration.txt'
-Opt.Cardfile = '/path/to/cardiac.txt'
-Opt.VolTR = 1.5
-Opt.Nslices = 34
-Opt.PhysFS = 100
-Opt.SliceOrder = 'alt+z'
-%please choose the correct order if not running interleaved: **'alt+z'**/'alt-z'/'seq+z'/'seq-z'
-RetroTS(Opt)
-</code>
-The output of runnning the MATLAB script 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 HEAD/BRIK to a nifti file, then proceed to whatever you're doing afterwards:
-<code bash>
-#convert afni to nii, create bxh
-bxh2analyze --niigz -s 12345.results/pb02.12345.r01.ricor+orig.BRIK physiocorrected
-</code>
-Run the resting state pipeline:
-<code bash>resting_pipeline.py -f physiocorrected.bxh -s 0,1,2,3,4,5,6,7 -p func --sliceorder odd</code>

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