The tutorial is intended primarily for beginners, but it will also beneficial to experimentalists who understand electroencephalography and event related techniques, but need additional knowledge in annotation, standardization, long-term storage and publication of data.
Introduction to the first phases of EEG/ERP data lifecycle
The course is an introduction to the field of electrophysiology standards, infrastructure, and initiatives.
This lecture contains an overview of the Australian Electrophysiology Data Analytics Platform (AEDAPT), how it works, how to scale it, and how it fits into the FAIR ecosystem.
Tutorial on how to simulate brain tumor brains with TVB (reproducing publication: Marinazzo et al. 2020 Neuroimage). This tutorial comprises a didactic video, jupyter notebooks, and full data set for the construction of virtual brains from patients and health controls. Authors: Hannelore Aerts, Michael Schirner, Ben Jeurissen, DIrk Van Roost, Eric Achten, Petra Ritter, Daniele Marinazzo
As models in neuroscience have become increasingly complex, it has become more difficult to share all aspects of models and model analysis, hindering model accessibility and reproducibility. In this session, we will discuss existing resources for promoting FAIR data and models in computational neuroscience, their impact on the field, and the remaining barriers
This lecture covers how to make modeling workflows FAIR by working through a practical example, dissecting the steps within the workflow, and detailing the tools and resources used at each step.
This session will explore some practical use cases and see whether these affect your repository, your tool, or your research.
Peer Herholz gives a tour of how popular virtualization tools like Docker and Singularity are playing a crucial role in improving reproducibility and enabling high-performance computing in neuroscience.
The lecture focuses on rationale for employing neuroimaging methods for movement disorders