Welcome to the FieldTrip website

FieldTrip is the MATLAB software toolbox for MEG, EEG, iEEG and NIRS analysis. It offers preprocessing and advanced analysis methods, such as time-frequency analysis, source reconstruction using dipoles, distributed sources and beamformers and non-parametric statistical testing. It supports the data formats of all major MEG systems and of the most popular EEG, iEEG and NIRS systems. New data formats can be added easily. FieldTrip contains high-level functions that you can use to construct your own analysis protocols as a MATLAB script.

The FieldTrip software is released free of charge as open source software under the GNU general public license.

Please cite the FieldTrip reference paper when you have used FieldTrip in your study.

Robert Oostenveld, Pascal Fries, Eric Maris, and Jan-Mathijs Schoffelen. FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data. Computational Intelligence and Neuroscience, vol. 2011, Article ID 156869, 9 pages, 2011. doi:10.1155/2011/156869.

To get started with FieldTrip, continue reading the getting started documentation.

News and announcements

23 November, 2019

Niels Kloosterman and his team have written code to perform multiscale entropy analysis, and published this on github. The code is in FieldTrip style, and easily interfaces with FieldTrip’s raw data structure. Go and check out how this works.

11 September, 2019

Over the summer Caroline Witton and Robert have been busy finalizing the MEG epilepsy tutorial, which has in fact already been hiding on our website for quite some time. About two weeks ago Elaine Foley presented it at SuSIE, the Summer School on Imaging in Epilepsy, Epilepsy Surgery and Epilepsy Research, where it was received with enthusiasm. The tutorial demonstrates kurtosis beamforming and virtual channel time series analysis, both on Neuromag and on CTF data, for multiple ptients of whom the data is shared on our FTP server. It also demonstrates how to visualize source reconstruction results with MRIcro and AnyWave.

01 July, 2019

Two weeks ago, our external contributors Lau Møller Andersen (NatMEG, Stockholm) and Britta Westner (CFIN, Aarhus) presented a well-received EEG training workshop at the RITMO center at the University of Oslo. More information, including the material that they presented at the workshop can be found here. Are you also interested in organizing a workshop by yourself? Then check out this FAQ.

(Photo copyright Annica Thomson, University of Oslo). More photos of the RITMO workshop can be found here.

25 June, 2019

EEG-BIDS, an extension to the brain imaging data structure for electroencephalography and iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology have just been published in Scientific Data. These two papers describe the extension to the BIDS standard to allow it not only to store raw (f)MRI and MEG, but also EEG and iEEG data. The full specification is here; you can find further documentation and examples to work with BIDS here on this website.

5 April, 2019

Jan-Mathijs and Robert just published a paper in Scientific data, which is a Data Descriptor of our MOUS dataset, a 204-subject multimodal neuroimaging dataset collected by MPI and DCCN researchers, which is now shared with the wider research community at our Donders data repository. The data are organized according to BIDS. Go and check it out!

24 March, 2019

We just completed the first ECoG/SEEG toolkit at the UC Davis Medical Center in Sacramento, California. The three-day event was packed with lectures, hands-on sessions, and fruitful discussions, with people visiting from all over the US (and beyond). Many thanks also to neurosurgeon Fady Girgis and neuroscientist Bob Knight for providing lectures on the clinical aspects and research applications of intracranial EEG. We plan to upload videos of the lectures, so stay tuned.

13 March, 2019

Check it out! Matthias Treder has kindly contributed a tutorial and some code (streamlined a bit by yours truly) that now allows you to perform MVPA analysis in FieldTrip, using his awesome MVPA-light toolbox ! For now it is well supported, documented and tested for channel level time domain data, but in the near future (and with your help) we will also ensure support for frequency domain and source level data. For now you can just use ft_timelockstatistics with cfg.method=’mvpa’. The tutorial can be found here.

11 January, 2019

All the best wishes for the new year to all of you on behalf of the FieldTrip team! According to Google Scholar, the FieldTrip paper has now been cited more than 3000 times. We are happy that the project provides so many of you with helpful tools that facilitate you to contribute to the scientific community.

Recent improvements to the code

All changes to the code can be tracked on Twitter and GitHub.