TAPAS PhysIO 工具箱的实时脚本演示，用于生理（心脏和呼吸）噪声建模和 fmri 数据校正.zip

# PhysIO-Live This repository contains a Live-Script demo of the [TAPAS PhysIO toolbox](https://github.com/translationalneuromodeling/tapas/tree/master/PhysIO) for physiological (cardiac and respiratory) noise modelling and correction of fmri data.  </br> ## How to work with this repository ### There are three ways to work with this repository: - Run online [](https://matlab.mathworks.com/open/github/v1?repo=likeajumprope/PhysIO-Live&file=main.mlx) - Run locally on your machine - View on [](https://au.mathworks.com/matlabcentral/fileexchange/128779-physio-live) ### To clone this repository and run it locally on your machine: #### 1. Clone this repository *recursively*. This way, all dependent libraries, e.g., [SPM](https://www.fil.ion.ucl.ac.uk/spm/) and [TAPAS PhysIO](https://github.com/translationalneuromodeling/tapas/tree/master/PhysIO) are automatically installed as well. ``` git clone --recursive https://github.com/likeajumprope/PhysIO-Live ``` - *Note:* Check that the `libs` subfolder is not empty, and e.g,. `libs/tapas` contains files. </br> #### 2. Get the data. For this live demo, we use the [Forrest Gump](https://openneuro.org/datasets/ds000113/versions/1.3.0) data set. Here we use the audio perception sub data set (see also [here](https://www.studyforrest.org/data.html)) The following files need to be downloaded into the results/sub-01 folder: - sub-01/ses-audiotoryperception/func/sub-01_ses-auditoryperception_task-auditoryperception_run-01_bold.nii.gz (unpack) - sub-01/ses-forestgump/anat/sub-01_ses-forrestgump_T1w.nii.gz (unpack) - sub-01_ses-auditoryperception_func_sub-01_ses-auditoryperception_task-auditoryperception_run-01_physio.tsv - recording-cardresp_physio.json To make the download easier, you can also just open teh terminal run the file `get_files.sh` in the `misc` folder: ``` misc my-username$ ./get_files.sh ``` Move all those files into the results/sub-01 folder. Your folder structure should look like the following: <p align="center"> <img width="500" src="/misc/Folder_structure.png"> </p> </br> Now your folders are ready to go! </br> #### 3. Adapt the environment variables in main.mlx (matlab version > 2019a) or in main.m The two files main.mlx and main.m are identical and ensure the usability of this tutorial for matlab versions that do not support .mlx files. </br> ## Debugging - common issues - Make sure every step is run out of the results/>subjectID< folder! - Make sure tapas, spm/matlabbatch are on the path. Any "cannot find/open file" error is usually due to the relevant folder not being on the path. - Some operations take some time. A wheel of doom when hovering over the batch editor indicates that the process is still running! - When cloning the repository, pulling the wikidocs of TAPAS Physio might fail. Don't worry about that, the demo is fully functional! </br> ## Literature Please cite this software (PhysIO) as follows: 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.](https://pubmed.ncbi.nlm.nih.gov/27832957/) Journal of Neuroscience Methods 276, 56-72. doi:10.1016/j.jneumeth.2016.10.019 Please also cite the parent software collection TAPAS: Fraessle, 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., Mueller-Schrader, M., Pereira, I., Petzschner, F.H., Raman, S., Schoebi, D., Toussaint, B., Weber, L.A., Yao, Y., Stephan, K.E., 2021. [TAPAS: an open-source software package for Translational Neuromodeling and Computational Psychiatry.](https://doi.org/10.3389/fpsyt.2021.680811) Frontiers in Psychiatry 12, 857. https://doi.org/10.3389/fpsyt.2021.680811 If you use respiratory volume per time (RVT) regressors or preprocessing of respiratory traces, please also cite: Harrison, S.J., Bianchi, S., Heinzle, J., Stephan, K.E., Iglesias, S., Kasper L., 2021. [A Hilbert-based method for processing respiratory timeseries.](https://doi.org/10.1016/j.neuroimage.2021.117787) NeuroImage, 117787. https://doi.org/10.1016/j.neuroimage.2021.117787 (C) 2023 Johanna Bayer, supervised by Lars Kasper, supported by Mathworks Inc.