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......@@ -28,54 +28,71 @@ Citing from the introduction of our [paper](http://dx.doi.org/10.1016/j.jneumeth
## 3. 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)
The **core references for PhysIO** are:
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).
1. 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., 2017.
*The PhysIO Toolbox for Modeling Physiological Noise in fMRI Data*.
Journal of Neuroscience Methods 276, 56-72. https://doi.org/10.1016/j.jneumeth.2016.10.019
- *main PhysIO Toolbox reference, also a good starting point to learn about more about the methods in PhysIO (see next question)*
2. Frässle, S., Aponte, E.A., Bollmann, S., Brodersen, K.H., Do, C.T., Harrison, O.K., Harrison, S.J., Heinzle, J., Iglesias, S., Kasper, L., Lomakina, E.I., Mathys, C., Müller-Schrader, M., Pereira, I., Petzschner, F.H., Raman, S., Schöbi, D., Toussaint, B., Weber, L.A., Yao, Y., Stephan, K.E., 2021. *TAPAS: an open-source software package for Translational Neuromodeling and Computational Psychiatry*. Frontiers in Psychiatry 12, 857. https://doi.org/10.3389/fpsyt.2021.680811
- *main TAPAS software collection reference, see [main TAPAS README](https://github.com/translationalneuromodeling/tapas#readme) for more details on TAPAS itself*
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)
Please cite these papers if you use PhysIO in your work. Here is a minimum example snippet:
> 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.translationalneuromodeling.org/tapas).
> The analysis was performed using the Matlab PhysIO Toolbox ([1], version x.y.z,
> open-source code available as part of the TAPAS software collection: [2],
> <https://www.translationalneuromodeling.org/tapas>)
1. Glover, G.H., Li, T.Q. & Ress, D. Image-­‐based method for retrospective correction
If you use respiratory volume per time (RVT) regressors or preprocess respiratory traces
for RETROICOR, please also cite:
3. Harrison, S.J., Bianchi, S., Heinzle, J., Stephan, K.E., Iglesias, S., Kasper L., 2021.
A Hilbert-based method for processing respiratory timeseries.
NeuroImage, 117787. https://doi.org/10.1016/j.neuroimage.2021.117787
- *superior RVT computation, preprocessing of respiratory traces*
A **standard comprehensive 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), and include respiratory volume per time (RVT) as well as heart-rate variability (HRV) regressors.
> Physiological noise correction was performed using the Matlab PhysIO Toolbox ([1], version x.y.z,
> open-source code available as part of the TAPAS software collection: [2],
> <https://www.translationalneuromodeling.org/tapas>). A RETROICOR model [4,5]) was employed, using Fourier expansions of different order for the estimated phases of cardiac pulsation (3rd order),
> respiration (4th order) and cardio-­‐respiratory interactions (1st order) [6]. Furthermore, respiratory volume per time (RVT, [3,7]) and heart rate variability (HRV, [8]) were modeled.
4. 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.
5. 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:
6. 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., 2017. The PhysIO Toolbox for Modeling Physiological Noise in fMRI Data. Journal of Neuroscience Methods 276, 56–72. 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
7. 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
8. 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.,
If you use **noise ROIs (aCompCor) or 12/24 regressor motion modeling**, also include the
respective references:
9. 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
- *aCompCor*
10. 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
- *Motion Regressors*
## 4. Where do I find more documentation for PhysIO?
......@@ -276,5 +293,4 @@ pointers and templates. Before you contact us, please try the following:
[tapas@sympa.ethz.ch](https://sympa.ethz.ch/sympa/info/tapas),
which has a searchable [archive](https://sympa.ethz.ch/sympa/arc/tapas).
3. For new requests, we would like to ask you to submit them as
[issues](https://github.com/translationalneuromodeling/tapas/issues) on our github release page for TAPAS.
[issues](https://github.com/translationalneuromodeling/tapas/issues) on our github release page for TAPAS.
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