To carry out their activities, Research Teams of the Frédéric Joliot Institute for Life Sciences have developed high-profile technological platforms in many areas : biomedical imaging, structural biology, metabolomics, High-Throughput screening, level 3 microbiological safety laboratory...
Within the Institute, the "Funding Research and Technology Transfer" team is at your disposal to identify the scientists and the skills you need to set up a joint project, to define the terms of a collaboration contract or study.
Whether you are an academic, a SME or an industrialist, our team informs and advices you about the possibilities of consortium assembly, technology transfer, patent licensing or use of our platforms.
The team is also at the disposal of the researchers of the institute to accompany them in achieving their valorization objectives.
Conference | Brain
From 1/25/2021 to 1/25/2021
Richard Hochenberger (PARIETAL - Inria/CEA/Université Paris-Saclay) will give a talk on Zoom on January 25th.
Invited by: Florent Meyniel
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.
CEA is a French government-funded technological research organisation in four main areas: low-carbon energies, defense and security, information technologies and health technologies. A prominent player in the European Research Area, it is involved in setting up collaborative projects with many partners around the world.