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Frequently Asked Questions (FAQ)
================================
1. What is the PhysIO Toolbox?
------------------------------
PhysIO is a toolbox for model-based physiological noise correction of fMRI data.
PhysIO stands for Physiological Input/Output toolbox, which summarizes its core purpose. A quote from our [paper](http://dx.doi.org/10.1016/j.jneumeth.2016.10.019>):
> In short, the toolbox transforms physiological input, i.e. peripheral recordings, into physiological output, i.e. regressors encoding components of physiological noise [...] A modular Matlab implementation supports command-line operation and is compatible with all major fMRI analysis packages via the export of regressor text-files. For the Statistical Parametric Mapping [SPM](<http://www.fil.ion.ucl.ac.uk/spm>) software package in particular, PhysIO features a full integration as a Batch Editor Tool, which allows user-friendly, GUI-based setup and inclusion into existing preprocessing and modeling pipelines.
2. How do I cite PhysIO?
------------------------
The core reference for PhysIO is: _The PhysIO Toolbox for Modeling Physiological Noise in fMRI Data_ (http://dx.doi.org/10.1016/j.jneumeth.2016.10.019)
Please cite this paper if you use PhysIO in your work. Moreover, this paper is also a good source for more information on PhysIO (see next question).
A standard snippet to include in your method section could look like the following, assuming you use our specific implementation of RETROICOR, which uses Fourier expansions of different order for the estimated phases of cardiac pulsation (3rd order), respiration (4th order) and cardio-­‐respiratory interactions (1st order) following (Harvey et al., 2008)
> Correction for physiological noise was performed via RETROICOR [1,2] using Fourier
> expansions of different order for the estimated phases of cardiac pulsation (3rd order),
> respiration (4th order) and cardio-­‐respiratory interactions (1st order) [2]: The
> corresponding confound regressors were created using the Matlab PhysIO Toolbox ([4],
> open source code available as part of the TAPAS software collection:
> https://www.tnu.ethz.ch/en/software/tapas.html).
1. Glover, G.H., Li, T.Q. & Ress, D. Image-­‐based method for retrospective correction
of PhysIOlogical motion effects in fMRI: RETROICOR. Magn Reson Med 44, 162-­‐
7 (2000).
2. Hutton, C. et al. The impact of PhysIOlogical noise correction on fMRI at 7 T.
NeuroImage 57, 101-­‐112 (2011).
3. Harvey, A.K. et al. Brainstem functional magnetic resonance imaging:
Disentangling signal from PhysIOlogical noise. Journal of Magnetic Resonance
Imaging 28, 1337-­‐1344 (2008).
4. Kasper, L., Bollmann, S., Diaconescu, A.O., Hutton, C., Heinzle, J., Iglesias, S.,
Hauser, T.U., Sebold, M., Manjaly, Z.-M., Pruessmann, K.P., Stephan, K.E., 2016.
The PhysIO Toolbox for Modeling PhysIOlogical Noise in fMRI Data. Journal of
Neuroscience Methods accepted. doi:10.1016/j.jneumeth.2016.10.019
If you use respiratory‐volume-­per time (RVT), heart-‐rate
variability (HRV), noise ROIs or 12/24 regressor motion modeling, also include the
respective references:
5. Behzadi, Y., Restom, K., Liau, J., Liu, T.T., 2007. A component based noise
correction method (CompCor) for BOLD and perfusion based fMRI. NeuroImage 37,
90–101. doi:10.1016/j.neuroimage.2007.04.042
6. Birn, R.M., Smith, M.A., Jones, T.B., Bandettini, P.A., 2008. The respiration response
function: The temporal dynamics of fMRI s ignal fluctuations related to changes in
respiration. NeuroImage 40, 644–654. doi:10.1016/j.neuroimage.2007.11.059
PhysIO Toolbox | Citing this work 20
7. Chang, C., Cunningham, J.P., Glover, G.H., 2009. Influence of heart rate on the
BOLD signal: The cardiac response function. NeuroImage 44, 857–869.
doi:10.1016/j.neuroimage.2008.09.029
8. Siegel, J.S., Power, J.D., Dubis, J.W., Vogel, A.C., Church, J.A., Schlaggar, B.L.,
Petersen, S.E., 2014. Statistical improvements in functional magnetic resonance
imaging analyses produced by censoring high-motion data points. Hum. Brain Mapp.
35, 1981–1996. doi:10.1002/hbm.22307
3. Where do I find more documentation for PhysIO?
-------------------------------------------------
* The paper describing its structure, objective and modules:
* README.md in the main folder when downloading
- For help on installation and getting started
* Quickstart
- PDF (or markdown .md file)
- Tutorial matlab-scripts
* Reference Manual (for developers)
4. I am using FSL, AFNI, BrainVoyager, etc., for my fMRI Analyses. Do I need SPM for PhysIO to work?
----------------------------------------------------------------------------------------------------
No, the basic functionality of PhysIO, i.e. creating nuisance regressors for your GLM analysis, is available in plain Matlab. The following extra functionality related to automatising and assessing noise correction, require the installation of SPM:
- GUI (SPM Batch Editor)
- Pipeline dependencies (automatic input of realignment parameters, feed-in of multiple regressors file to GLM)
- Model assessment via F-tests and automatic F-map/tSNR report
- Noise-ROIs model (read-in of nifti files via SPM)
5. I cannot find the answer to my question in the FAQ. Whom do I ask for help?
------------------------------------------------------------------------------
Subscribe to our TAPAS mailing list by clicking **Subscribe** on the left side of [this website]( <https://sympa.ethz.ch/sympa/info/tapas>)
Afterwards you can send e-mails with your questions to `tapas@sympa.ethz.ch`. Both, core developers of PhysIO and experienced users are receiving your e-mail and are eager to help.
The mailing list also has a searchable archive (click **Archive** on the left of above-mentioned website), where you might already find the answer to your question.
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