Sessions

We’ll have 4 sessions in total, divided into hands-on tutorials, talks/discussions and open hacking. They will aim at providing an introduction to various parts of the “open & reproducible (neuro)science” realm, as well as foster interdisciplinary research and respective approachs.

Session 1 - Round Table

“Thinking about breaking cross-technique and cross-species boundaries in data analysis” with Janelle Pakan

Session 2 - Hands-on tutorial

“M/EEG and MRI analysis in Python using MNE and Nipype” with Malte Gueth (Center for Molecular and Behavioral Neuroscience, Rutgers University Newark, USA). This workshop will be an introductory overview of M/EEG and MRI analysis in Python. Both preprocessing and inferential statistics will be covered.

Session 3 - Open Hacking

Free hacking on (your own) projects, get feedback and support regarding data/project management (BIDS, computational environments, BIDS-Apps, QC, version control, etc.) and various analyses (connectivity, uni-/multivariate statistics, machine learning, encoding, etc.) with Alexander Weuthen and Peer Herholz.

Session 4 - Unconference

“Sharing is Caring: Sneak Peek at the World of Open-source with GitHub” with Soumick Chatterjee.

Abstract: Open-source tools have the potential to simplify our research life and help us save ample amount of time – by not repeating things already done by others. On the other hand, we should also support the community by making our research open. When it comes to coding, we need the support of version controlling and open-source code sharing platform GitHub to achieve this goal. In my talk, I will be providing a gentle introduction to version controlling using GitHub – while also introducing some open-source tool for image analysis, machine learning (including deep learning).