Evoked

Brainlife App to detect ECG related components using find_bads_ecg function.

app-evoked documentation

1. Input file is:

   • epoch/fif epoch data file

2. Input parameters:

   • ch_type The channel type to plot. For 'grad', the gradiometers are collected in pairs and the RMS for each pair is plotted. If None the first available channel type from order shown above is used. Defaults to None.
   • timepoints_from The starting time point(s) to plot.
   • timepoints_to The final time point(s) to plot.
   • step Step of time point(s) to be plot.

3. Ouput files are:

   • evoked/fif evoked file.

Authors

• Saeed ZAHRAN(saeedzahranutc@gmail.com)

Citations

We kindly ask that you cite the following articles when publishing papers and code using this code.

- brainlife.io Publishing and Apps:

Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

- MNE-Python package:

Gramfort A, Luessi M, Larson E, Engemann DA, Strohmeier D, Brodbeck C, Goj R, Jas M, Brooks T, Parkkonen L, and Hämäläinen MS. MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience, 7(267):1–13, 2013. https://doi.org/10.3389/fnins.2013.00267

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your publications and code reusing this code.

MIT Copyright (c) 2021 brainlife.io The University of Texas at Austin and Indiana University