This Brainlife.io app reads the .info attribute of an MNE Raw object and writes it to a text file for easy viewing. It also summarizes key acquisition parameters (channel types, sampling frequency, duration, digitized head points, filter settings, projectors) and, when channel positions or digitized head points are available, renders them with raw.plot_sensors() and simple 3D scatter plots for visual inspection in the Brainlife.io interface.
The app generates:
- A text dump of the raw data's
.infoattribute - A 2D electrode montage plot (when channel positions are available)
- 3D scatter plots of electrode positions and digitized head points (when available)
- A
product.jsonsummary of key acquisition parameters, with the figures above embedded
raw(neuro/meeg/mne/raw): continuous MEG/EEG data whose.infoattribute is read (required)
out_dir/info.txt(neuro/meg/fif-override, taginfo): text dump of the raw data's.infoattributeout_figs/montage_2d.png: 2D electrode montage plot, produced when channel positions are availableout_figs/electrodes_3d.png: 3D scatter plot of electrode positions, produced when channel positions are availableout_figs/digitized_head_points_3d.png: 3D scatter plot of digitized head points, produced when digitized head points are availableproduct.json: structured summary of channel types, sampling rate, duration, filters and projectors, with the figures above embedded for display in the Brainlife.io interface
This app reads no configuration parameters beyond its input file (see Inputs above).
- Select your MEG/EEG raw dataset as the
rawinput. - Submit the process.
- Inspect
info.txt, the generated figures, and theproduct.jsonsummary in the process viewer.
# Edit config.json to point "raw" at real data, then:
python main.py- Kamilya Salibayeva (Indiana University)
- Maximilien Chaumon, Paris Brain Institute
We kindly ask that you cite the following articles when publishing papers and code using this app:
- Hayashi, S., Caron, B.A., Heinsfeld, A.S. et al. brainlife.io: a decentralized and open-source cloud platform to support neuroscience research. Nat Methods 21, 809–813 (2024). https://doi.org/10.1038/s41592-024-02237-2
- Gramfort, A. et al. MEG and EEG data analysis with MNE-Python. Front. Neurosci. 7, 267 (2013). https://doi.org/10.3389/fnins.2013.00267
- 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
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.
Copyright (c) 2026 MEEG Brainlife team. Licensed under AGPL-3.0, see license.txt.