ArticleFrontiers in neuroscience2025
osl-ephys: a Python toolbox for the analysis of electrophysiology data.
Article in Frontiers in neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Robust and replicable effects of ageing on resting-state brain electrophysiology measured with MEG.eLife · 2026Article
- Varying patterns of association between cortical large-scale networks and subthalamic nucleus activity in Parkinson's disease.NPJ Parkinson's disease · 2026Article
- Effects of Age on Resting-State Cortical Networks.Human brain mapping · 2026Article
- Temporally Defined Brain Network Activation Associated With Slowed Information Processing Speed in Multiple Sclerosis.Human brain mapping · 2026Article
- Divergence of cortical neurophysiology across different neurodegenerative disorders compared to healthy ageing.Progress in neurobiology · 2026Article
- Large-scale cortical functional networks are organized in structured cycles.Nature neuroscience · 2025Article
- Distinct alpha networks modulate different aspects of perceptual decision-making.PLoS biology · 2025Article
- Evidence for Transient, Uncoupled Power and Functional Connectivity Dynamics.Human brain mapping · 2025Article
- Towards a 384-channel magnetoencephalography system based on optically pumped magnetometers.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Modelling variability in functional brain networks using embeddings.Imaging neuroscience (Cambridge, Mass.)Article
- Modelling discrete states and long-term dynamics in functional brain networks.Imaging neuroscience (Cambridge, Mass.)Article
- MEG-GPT: A transformer-based foundation model for magnetoencephalography data.Imaging neuroscience (Cambridge, Mass.)Article
- From early to contemporary normative modeling: Mapping individual differences in neurophysiological signals.Imaging neuroscience (Cambridge, Mass.)Article
- Canonical Hidden Markov Model Networks for studying M/EEG.Imaging neuroscience (Cambridge, Mass.)Article
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Authors and funding
4 authors.
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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.
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