Power Spectral Density (PSD)

Brainlife App to compute Power Spectral Density (PSD) on MEG files using MNE-Python Welch method mne.time_frequency.psd_welch function

app-peak-frequency documentation

2. Input file is:
   • meg/fif meg data file
3. Ouput files are:
   • A series of files .tsv file containing the PSD, for gradiometers (grad), magnetometers (mag) and electroencephalography (eeg) acording to the channels types contained in raw meg data
   • a plot of the PSD for all channels (grad, mag, eeg) using MNE-Python function
   • a plot of the PSD for all channels (grad, mag, eeg) manually implemented (for reproducibility purposes)

Authors

• Guiomar Niso (guiomar.niso@ctb.upm.es)

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