Two NatMEG workshops on cluster-based permutation statisitcs and GitHub

Two NatMEG workshops on non-parametric cluster-based statistics and Git/GitHub

We are happy to announce two workshops hosted by NatMEG on non-parametric cluster-based statistics for analysing MEG/EEG (and related data types), and on using Git and GitHub in neuroscientific work. Both workshops will combine lectures and practical hands-on exercise.

The workshops will be online and free to attend. To sign-up for wither workshop send an email to Please state your name and affiliation in the email and which of the workshops you are interested in joining.

Non-Parametric Cluster-Based Permutation Tests for Analysing Neural Time-Series.

Tuesday, March 9th 15:00-17:00.

Statistical testing on EEG and MEG data can be tricky due to the high dimensionality of the data and the autocorrelation of the signals in both time and space. If not managed correctly, statistics on MEG/EEG data have a large false-positive rate and lead to erroneous results. Non-parametric cluster-based permutation tests are statistics developed to analyse MEG/EEG signals (and other types of neural time-series). It uses the features of the signals to provide valid statistical inference. The lecture will introduce the (simple) logic behind non-parametric cluster-based permutation tests and their interpretations and misinterpretations. The hands-on tutorial will teach you how to do cluster-based permutation tests with the FieldTrip toolbox in MATLAB. The workshop is aimed at researchers at all levels working with EEG, MEG, ECoG, fNIRS or similar methods, but open for everybody interested in robust statistical analysis of neural time-series.

Using Git/GitHub in Scientific Collaborations.

Tuesday, March 16th 15:00-17:00.

Analysis of neuroscientific data requires making analysis scripts for data processing. Sometimes we need to collaborate and share analysis scripts, which can be a burden to maintain version control. Furthermore, more and more scientific journals require researchers to share analysis script when publishing scientific papers. Git and GitHub is one tool that makes sit easier to share and collaborate on data analysis. This lecture will focus on why and how to use GitHub in (neuro-) scientific collaborations and project management. The lecture is followed by a hands-on tutorial to master the basics of Git/GitHub for scientific collaboration. The workshop for all researchers at any career level, who have little or no experience working with Git/GitHub but would like to be the Git wizard of their research group.