Richard Hochenberger (PARIETAL - Inria/CEA/Université Paris-Saclay) will give a talk on Zoom on January 25th.

Invited by: Florent Meyniel

Short abstract:

MNE-Python is a software for processing and analysis of electrophysiological brain data. Tightly integrated with the scientific Python ecosystem, it allows beginners and advanced users alike to explore, analyze, and visualize their data – both at the level of sensors as well at the underlying neural sources. As a community-driven free and open-source project, development closely follows the requirements of those who intend to use the software: thousands of psychologists and neuroscientists around the globe. In recent years, functionality for automated artifact detection, largely improved interactive three-dimensional visualizations, and support for new data types like intracranial or fNIRS recordings has been added. An entire ecosystem of tools has evolved around MNE-Python, most notably probably MNE-BIDS, which aims to simplify data exchange through a standardized file format; braindecode, a deep learning library for EEG; and the MNE Study Template, an automated analysis pipeline that transforms raw data into a fully processed and analyzed dataset, only with the help of a simple user-supplied configuration file. On the community development side, we are in the process of implementing different measures to make the MNE project more accessible and inclusive.

Richard Hochenberger will give a brief overview of all these topics; show what MNE-Python can do for you today (and why you should consider switching if you’re not using it already); and present plans for future development.