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Published November 14, 2022 | Version 0.1.1
Software Open

OHBA Software Library in Python (OSL)

Creators

  • 1. Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University Department of Psychiatry, Warneford Hospital, Oxford, UK; Centre for Human Brain Health, School of Psychology, University of Birmingham, UK
  • 2. Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University Department of Psychiatry, Warneford Hospital, Oxford, UK

Description

The OHBA Software Library (OSL) is created by the OHBA Analysis Group, OHBA, University of Oxford, UK. OSL is a Python package for running M/EEG analysis, and it is the successor of the MATLAB OSL package. OSL in Python integrates well-known software packages like MNE-Python and FSL into its own analysis functions and design philosophy.

At the core of OSL sits a configuration user interface, which allows the user to set up a pipeline for processing the data in the most concise way, without losing any flexibility. The config structure is typically on the size of one to two dozen lines of code that capture an entire (pre-) processing pipeline, and can easily be shared for reproducibility and replicability. Moreover, it contains tools for batch and parallel processing, as well as a set of reporting tools for quality control of processed (batch) data.

OSL is under constant development to incorporate new functionalities. The most recent version of OSL can always be found on GitHub; this is also where issue reporting and feature requests take place. Version 0.1.1 of OSL has the following features:

  • Interface to ELEKTA's Maxfilter software
  • Preprocessing of M/EEG data
  • FSL-based surface extraction and coregistration of M/EEG, headshape, and sMRI data
  • Volumetric source reconstruction, including parcellation and spatial leakage reduction via orthogonalisation
  • Batch processing using functions from OSL, MNE-Python, and custom written functions
  • Visualizing data and creating reports of processed data
  • Utilities for parallel processing, file handling, etc.

 

Notes

This research was supported by the National Institute for Health Research (NIHR) Oxford Health Biomedical Research Centre. The Wellcome Centre for Integrative Neuroimaging is supported by core funding from the Wellcome Trust (203139/Z/16/Z). C.G. and M.v.E are supported by the Wellcome Trust (215573/Z/19/Z). A.Q. is supported the MRC (RG94383/RG89702) and by the NIHR Oxford Health Biomedical Research Centre. M.W. is supported by NIHR Oxford Health Biomedical Research Centre, the Wellcome Trust (106183/Z/14/Z and 215573/Z/19/Z), and the New Therapeutics in Alzheimer's Diseases (NTAD) study supported by the MRC and the Dementia Platform UK.

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osl-0.1.1.zip

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Additional details

Funding

Exploring the Mechanisms of Distributed Spontaneous Brain Activity. 106183
Wellcome Trust
Integrative imaging of brain structure and function in populations and individuals 215573
Wellcome Trust
Wellcome Centre for Integrative Neuroimaging 203139
Wellcome Trust

References

  • The OHBA Software Library (OSL). https://github.com/OHBA-analysis/osl-core
  • Alexandre Gramfort, Martin Luessi, Eric Larson, Denis A. Engemann, Daniel Strohmeier, Christian Brodbeck, Roman Goj, Mainak Jas, Teon Brooks, Lauri Parkkonen, and Matti S. Hämäläinen. MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience, 7(267):1–13, 2013. doi:10.3389/fnins.2013.00267.
  • S.M. Smith, M. Jenkinson, M.W. Woolrich, C.F. Beckmann, T.E.J. Behrens, H. Johansen-Berg, P.R. Bannister, M. De Luca, I. Drobnjak, D.E. Flitney, R. Niazy, J. Saunders, J. Vickers, Y. Zhang, N. De Stefano, J.M. Brady, and P.M. Matthews. Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23(S1):208-19, 2004