FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data
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This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.
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T-test designs were used because cluster-based permutation analyses implemented in Fieldtrip are not well suited to 2 x 2 designs.
“T-test designs were used as cluster based permutation analyses implemented in Fieldtrip (the analysis software most commonly used to examine TEPs) are not well suited to 2 x 2 designs (Oostenveld et al., 2011).”
From Investigation of neurobiological responses to theta burst stimulation during recovery from mild traumatic brain injury (mTBI) (2023) · cites this paper as Oostenveld et al., 2011
Section 2.7.7 (page not available) describes FieldTrip’s statistical inference using parametric or nonparametric algorithms, and the Concluding Remarks identify its implementation of nonparametric permutation tests. Neither passage says those analyses are poorly suited to 2 × 2 designs or supports the claim that FieldTrip is the software most commonly used to examine TEPs. (LLM, conf=0.85)
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- Authors
- Oostenveld, R., Fries, P., Maris, E., & Schoffelen, J.-M.
- Affiliations
- Radboud University Nijmegen (NL)
- Corresponding author
- Oostenveld, Robert
- Venue
- Computational Intelligence and Neuroscience
- Publisher
- Wiley
- Published
- 2011
- Volume
- 2011
- Pages
- 1-9
- ISSN
- 1687-5265 (ISSN-L)
- 1687-5273
- PMC
- PMC3021840
- OpenAlex
- W2166073443
- Cited by
- 10,323
- References
- 1
- Citations by year
- 2026: 711 · 2025: 1127 · 2024: 1077 · 2023: 1033 · 2022: 1005 · 2021: 999 · 2020: 870 · 2019: 819 · 2018: 677 · 2017: 521 · 2016: 411 · 2015: 357 · 2014: 285 · 2013: 222 · 2012: 151
- FWCI
- 80.11
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Computational Intelligence and Neuroscience (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- MPG.PuRe (Max Planck Society) (submittedVersion, cc-by-nc-sa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Undergraduate Neuroscience Education and Research
- Keywords
- FieldTrip, open source software, magnetoencephalography, EEG, invasive electrophysiology, MATLAB toolbox, time-frequency analysis, multitaper spectral analysis, source localization, dipole modeling, distributed sources, beamforming, connectivity analysis, permutation tests, nonparametric statistics
- MeSH terms
- Electroencephalography, Humans, Numerical Analysis, Computer-Assisted, Software, User-Computer Interface, Magnetoencephalography, Electrophysiological Phenomena
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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