Journal article
osl-ephys: a Python toolbox for the analysis of electrophysiology data
- Abstract:
- We describe OHBA Software Library for the analysis of electrophysiology data (osl-ephys). This toolbox builds on top of the widely used MNE-Python package and provides unique analysis tools for magneto−/electro-encephalography (M/EEG) sensor and source space analysis, which can be used modularly. In particular, it facilitates processing large amounts of data using batch parallel processing, with high standards for reproducibility through a config API and log keeping, and efficient quality assurance by producing HTML processing reports. It also provides new functionality for doing coregistration, source reconstruction and parcellation in volumetric space, allowing for an alternative pipeline that avoids the need for surface-based processing, e.g., through the use of Fieldtrip. Here, we introduce osl-ephys by presenting examples applied to a publicly available M/EEG data (the multimodal faces dataset). osl-ephys is open-source software distributed on the Apache License and available as a Python package through PyPi and GitHub.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 4.2MB, Terms of use)
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- Publisher copy:
- 10.3389/fnins.2025.1522675
Authors
+ Wellcome Trust
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- Funder identifier:
- https://ror.org/029chgv08
- Grant:
- 106183/Z/14/Z
- 203139/Z/16/Z
- 215573/Z/19/Z
+ Medical Research Council
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- Funder identifier:
- https://ror.org/03x94j517
- Grant:
- RG94383/RG89702
+ National Institute for Health Research
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- Funder identifier:
- https://ror.org/0187kwz08
- Grant:
- NIHR203316
- Publisher:
- Frontiers Media
- Journal:
- Frontiers in Neuroscience More from this journal
- Volume:
- 19
- Article number:
- 1522675
- Publication date:
- 2025-02-21
- Acceptance date:
- 2025-01-30
- DOI:
- EISSN:
-
1662-453X
- ISSN:
-
1662-4548
- Language:
-
English
- Keywords:
- Pubs id:
-
2092077
- Local pid:
-
pubs:2092077
- Deposit date:
-
2025-03-06
- ARK identifier:
Terms of use
- Copyright holder:
- van Es et al
- Copyright date:
- 2025
- Rights statement:
- © 2025 van Es, Gohil, Quinn and Woolrich. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
- Licence:
- CC Attribution (CC BY)
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