app-mean-transformation-matrix

APP UNDER DEVELOPMENT PRIVATE APP ON BL

This app aims at computing the mean transformation matrix across all runs of a MEG session to correct the head position of all runs thanks to this matrix. This mean transformation matrix is stored in an empty .fif file, which then can be passed as a parameter in mne.preprocessing.maxwell_filter (destination parameter).

GitHub repository

https://github.com/AuroreBussalb/app-mean-transformation-matrix

Brainlife datatype used:

• For input: neuro/meg/fif

• For output: neuro/meg/fif-override

Inputs of the App:

Output of the App:

Besides, in the output directory, there are the optional files we will use in a next App. This is mandatory, because the App that will be run after app-mean-transformation-matrix will take as input all the files in app-mean-transformation-matrix’s output directory corresponding to the datatype of the input of the next App (see How to run Apps one after another).

Parameters of the App

The parameters of the App correspond to the parameters passed to the Python functions used in the App. They are listed in the config.json.example when you test your App locally, then when you register you App on Brainlife, you enter them and a config.json is created by Brainlife.

Here, we used the parameters set by default by mne.

Next improvements

• Rename it into “app-compute-realigment-matrix”?

• Allow the user to compute a destination.fif that is not the mean of all the runs but a specific run? To do so, it would be best not to save the entire .fif file (i.e. the MEG signal) but to extract the raw.info[“dev_head_t"]["trans"] from this file and put it in an empty fif file, like we do when we compute the mean of the runs (it would save space).