| Name | mne-bids-pipeline JSON |
| Version |
1.9.0
JSON |
| download |
| home_page | None |
| Summary | A full-flegded processing pipeline for your MEG and EEG data |
| upload_time | 2024-06-22 10:16:40 |
| maintainer | None |
| docs_url | None |
| author | Eric Larson, Alexandre Gramfort, Mainak Jas |
| requires_python | >=3.10 |
| license | Copyright © 2019-2022, authors of MNE-BIDS-Pipeline All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
neuroscience
psychology
science
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# <img src="https://raw.github.com/mne-tools/mne-bids-pipeline/main/docs/source/assets/mne.svg" alt="MNE Logo" height="20"> MNE-BIDS-Pipeline
<!--keep description in sync with pyproject.toml-->
<!--tagline-start-->
**MNE-BIDS-Pipeline is a full-flegded processing pipeline for your MEG and
EEG data.**
* It operates on data stored according to the [Brain Imaging Data
Structure (BIDS)](https://bids.neuroimaging.io/).
* Under the hood, it uses [MNE-Python](https://mne.tools).
<!--tagline-end-->
## 💡 Basic concepts and features
<!--features-list-start-->
* 🏆 Automated processing of MEG and EEG data from raw data to inverse solutions.
* 🛠️ Configuration via a simple text file.
* 📘 Extensive processing and analysis summary reports.
* 🧑🤝🧑 Process just a single participant, or as many as several hundreds of participants – in parallel.
* 💻 Execution via an easy-to-use command-line utility.
* 🆘 Helpful error messages in case something goes wrong.
* 👣 Data processing as a sequence of standard processing steps.
* ⏩ Steps are cached to avoid unnecessary recomputation.
* ⏏️ Data can be "ejected" from the pipeline at any stage. No lock-in!
* ☁️ Runs on your laptop, on a powerful server, or on a high-performance cluster via Dask.
<!--features-list-end-->
## 📘 Installation and usage instructions
Please find the documentation at
[**mne.tools/mne-bids-pipeline**](https://mne.tools/mne-bids-pipeline).
## ❤ Acknowledgments
The original pipeline for MEG/EEG data processing with MNE-Python was built
jointly by the [Cognition and Brain Dynamics Team](https://brainthemind.com/)
and the [MNE Python Team](https://mne.tools), based on scripts originally
developed for this publication:
> M. Jas, E. Larson, D. A. Engemann, J. Leppäkangas, S. Taulu, M. Hämäläinen,
> A. Gramfort (2018). A reproducible MEG/EEG group study with the MNE software:
> recommendations, quality assessments, and good practices. Frontiers in
> neuroscience, 12. <https://doi.org/10.3389/fnins.2018.00530>
The current iteration is based on BIDS and relies on the extensions to BIDS
for EEG and MEG. See the following two references:
> Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G.,
> Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension
> to the brain imaging data structure for electroencephalography. Scientific
> Data, 6, 103. <https://doi.org/10.1038/s41597-019-0104-8>
> Niso, G., Gorgolewski, K. J., Bock, E., Brooks, T. L., Flandin, G., Gramfort, A.,
> Henson, R. N., Jas, M., Litvak, V., Moreau, J., Oostenveld, R., Schoffelen, J.,
> Tadel, F., Wexler, J., Baillet, S. (2018). MEG-BIDS, the brain imaging data
> structure extended to magnetoencephalography. Scientific Data, 5, 180110.
> <https://doi.org/10.1038/sdata.2018.110>
Raw data
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"description": "# <img src=\"https://raw.github.com/mne-tools/mne-bids-pipeline/main/docs/source/assets/mne.svg\" alt=\"MNE Logo\" height=\"20\"> MNE-BIDS-Pipeline\n\n<!--keep description in sync with pyproject.toml-->\n\n<!--tagline-start-->\n**MNE-BIDS-Pipeline is a full-flegded processing pipeline for your MEG and\nEEG data.**\n\n* It operates on data stored according to the [Brain Imaging Data\nStructure (BIDS)](https://bids.neuroimaging.io/).\n* Under the hood, it uses [MNE-Python](https://mne.tools).\n\n<!--tagline-end-->\n\n## \ud83d\udca1 Basic concepts and features\n\n<!--features-list-start-->\n\n* \ud83c\udfc6 Automated processing of MEG and EEG data from raw data to inverse solutions.\n* \ud83d\udee0\ufe0f Configuration via a simple text file.\n* \ud83d\udcd8 Extensive processing and analysis summary reports.\n* \ud83e\uddd1\u200d\ud83e\udd1d\u200d\ud83e\uddd1 Process just a single participant, or as many as several hundreds of participants \u2013 in parallel.\n* \ud83d\udcbb Execution via an easy-to-use command-line utility.\n* \ud83c\udd98 Helpful error messages in case something goes wrong.\n* \ud83d\udc63 Data processing as a sequence of standard processing steps.\n* \u23e9 Steps are cached to avoid unnecessary recomputation.\n* \u23cf\ufe0f Data can be \"ejected\" from the pipeline at any stage. No lock-in!\n* \u2601\ufe0f Runs on your laptop, on a powerful server, or on a high-performance cluster via Dask.\n\n<!--features-list-end-->\n\n## \ud83d\udcd8 Installation and usage instructions\n\nPlease find the documentation at\n[**mne.tools/mne-bids-pipeline**](https://mne.tools/mne-bids-pipeline).\n\n## \u2764 Acknowledgments\n\nThe original pipeline for MEG/EEG data processing with MNE-Python was built\njointly by the [Cognition and Brain Dynamics Team](https://brainthemind.com/)\nand the [MNE Python Team](https://mne.tools), based on scripts originally\ndeveloped for this publication:\n\n> M. Jas, E. Larson, D. A. Engemann, J. Lepp\u00e4kangas, S. Taulu, M. H\u00e4m\u00e4l\u00e4inen,\n> A. Gramfort (2018). A reproducible MEG/EEG group study with the MNE software:\n> recommendations, quality assessments, and good practices. Frontiers in\n> neuroscience, 12. <https://doi.org/10.3389/fnins.2018.00530>\n\nThe current iteration is based on BIDS and relies on the extensions to BIDS\nfor EEG and MEG. See the following two references:\n\n> Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G.,\n> Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension\n> to the brain imaging data structure for electroencephalography. Scientific\n> Data, 6, 103. <https://doi.org/10.1038/s41597-019-0104-8>\n\n> Niso, G., Gorgolewski, K. J., Bock, E., Brooks, T. L., Flandin, G., Gramfort, A.,\n> Henson, R. N., Jas, M., Litvak, V., Moreau, J., Oostenveld, R., Schoffelen, J.,\n> Tadel, F., Wexler, J., Baillet, S. (2018). MEG-BIDS, the brain imaging data\n> structure extended to magnetoencephalography. Scientific Data, 5, 180110.\n> <https://doi.org/10.1038/sdata.2018.110>\n",
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