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--- biac:analysis:physiological [2011/11/03 18:40] – [Physiological Correction Methods] petty
+++ biac:analysis:physiological [2022/01/20 14:46] – cmp12
@@ 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.
+===== Generate resampled TSV from raw GE physio files automatically copied from the scanners  =====
-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.
+Stock GE physio is hardcoded by GE to be 25Hz for respiration and 100Hz for pulse.  The continuous gating files will start 30 seconds before the scan is triggered.
-This tool 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 to do the corrections, then output new text data in the format requested.
+<code>
+[cmp12@blade17 20211218_03399]$ /usr/local/packages/biacpython/bin/convert_GEphysio.py --help
+usage: convert_GEphysio.py [-h] --xmlh XMLFNAME [--json JSONFNAME] --physdir
+                           PHYSDIR [--bidsout] [--afnislicetime]
+                           [--delay DELAYTIME]
+create 100Hz resampled TSV from raw GE physio data
+optional arguments:
+  -h, --help         show this help message and exit
+  --xmlh XMLFNAME    BXH data
+  --json JSONFNAME   JSON data
+  --physdir PHYSDIR  physio directory
+  --bidsout          write BIDS specific TSV data and json sidecar
+  --afnislicetime    write AFNI slicetiming 1D files for RetroTS and tshift
+  --delay DELAYTIME  time past ending time of functional to end search for
+                     matching physio files
-<code>
-physio_create.py --help
 </code>
-<code>
+Provide a valid BXH ( and JSON if possible ) and a path to your subject physio folder to convert_GEphysio.py function.  If the BXH does not contain slice timing information the JSON is required.
-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:
+This function will search the physio directory for physio files within a specified time range based on the functional scantime + timepoints + a default delay in writing.
-    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
+If matching respiration and pulse files are found theoretical scan triggers on each TR will be created and the respiration and pulse data will be resampled to 100Hz and locked to the onset of the scan.  If disdaqs are detected in the BXH the corresponding physio time will be discarded.
-Options:
+<code>
-  -h, --help            show this help message and exit
+/usr/local/packages/biacpython/bin/convert_GEphysio.py --xmlh Data/Func/20211218_03399/bia6_03399_004_01.bxh --physdir Data/Func/20211218_03399 --bidsout
-  -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 =====
+By default you will get a 100Hz resampled TSV with headers and timing.
-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".
+The **--bidsout** flag will output a TSV without headers and a BIDS sidecar with appropriate column labels and sampling frequency.
-Now set-up build the regressors that will be used in afni with their matlab tool.
-<code matlab>
+The **--afnislicetime** flag will output two 1D slicetiming files to be used with RetroTS.py and afni_proc.py directly.
-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
-RetroTS(Opt)
+=== Using afni ===
-</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.
+You can create regressors for afni preprocessing from output files above using RetroTS.py
-Convert your data to 4D nifti if you haven't already done so:
+<code>
-<code bash>bxh2analyze --niigz -s input.bxh run004</code>
+python3 /usr/local/packages/afni/21.1.04/RetroTS.py -phys_file series013_01_physio.tsv -phys_json series013_01_physio.json -n 42 -v 2 -slice_order series013_01_slicetimingV.1D -prefix  series013_01
-Create the afni script which you will use to actually run the 3dretroicor functionality:
+-n #slices
-<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
+-v TR in seconds
-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:
+RetroTS will produce "slibase" regressors to be used with retroicor during afni preprocessing, or afni retroicor regression
-<code bash>resting_pipeline.py -f pb02.12345.r01.ricor.bxh -s 1,2,3,4,5,6,7 -p func --sliceorder odd</code>
-===== FSL Feat =====
-We've gotten the FSL beta functions for physiological correction, which we'll test.
-They are based on the same algorithms used in afni with retroicor.  Once things are functioning, they'll be installed on the cluster.
-More information can be seen here:
-[[http://www.fmrib.ox.ac.uk/Members/jon/physiological-noise-correction]]
-The beta options will allow you to plug in the resulting regressors directly into Feat.  After pre-processing you can use the **res4d.nii.gz** files for further analysis ( filtered_func_data would not have the physio regressor removed ).
+====== CIGAL pdigm specific ======
+[[biac:analysis:physiological:cigal_pdigm| CIGAL pdigm specific physio correction methods]]