This talk gives an overview of the Human Brain Project, a 10-year endeavour putting in place a cutting-edge research infrastructure that will allow scientific and industrial researchers to advance our knowledge in the fields of neuroscience, computing, and brain-related medicine.

This lecture gives an introduction to the European Academy of Neurology, its recent achievements and ambitions.

This lesson is a general overview of overarching concepts in neuroinformatics research, with a particular focus on clinical approaches to defining, measuring, studying, diagnosing, and treating various brain disorders. Also described are the complex, multi-level nature of brain disorders and the data associated with them, from genes and individual cells up to cortical microcircuits and whole-brain network dynamics. Given the heterogeneity of brain disorders and their underlying mechanisms, this lesson lays out a case for multiscale neuroscience data integration.

This is the first of two workshops on reproducibility in science, during which participants are introduced to concepts of FAIR and open science. After discussing the definition of and need for FAIR science, participants are walked through tutorials on installing and using Github and Docker, the powerful, open-source tools for versioning and publishing code and software, respectively.

This is a continuation of the talk on the cellular mechanisms of neuronal communication, this time at the level of brain microcircuits and associated global signals like those measureable by electroencephalography (EEG). This lecture also discusses EEG biomarkers in mental health disorders, and how those cortical signatures may be simulated digitally.

This lesson describes the principles underlying functional magnetic resonance imaging (fMRI), diffusion-weighted imaging (DWI), tractography, and parcellation. These tools and concepts are explained in a broader context of neural connectivity and mental health. 

This lecture aims to help researchers, students, and health care professionals understand the place for neuroinformatics in the patient journey using the exemplar of an epilepsy patient. 

This lesson continues from part one of the lecture Ontologies, Databases, and Standards, diving deeper into a description of ontologies and knowledg graphs. 

While the previous lesson in the Neuro4ML course dealt with the mechanisms involved in individual synapses, this lesson discusses how synapses and their neurons' firing patterns may change over time. 

In this lesson, you will learn in more detail about neuromorphic computing, that is, non-standard computational architectures that mimic some aspect of the way the brain works. 

This video provides a very quick introduction to some of the neuromorphic sensing devices, and how they offer unique, low-power applications.

This tutorial covers the fundamentals of collaborating with Git and GitHub.

This lecture and tutorial focuses on measuring human functional brain networks, as well as how to account for inherent variability within those networks. 

This lesson provides an overview of Jupyter notebooks, Jupyter lab, and Binder, as well as their applications within the field of neuroimaging, particularly when it comes to the writing phase of your research. 

This lecture introduces you to the basics of the Amazon Web Services public cloud. It covers the fundamentals of cloud computing and goes through both the motivations and processes involved in moving your research computing to the cloud.

This lecture provides an introduction to entropy in general, and multi-scale entropy (MSE) in particular, highlighting the potential clinical applications of the latter. 

This lecture provides an general introduction to epilepsy, as well as why and how TVB can prove useful in building and testing epileptic models. 

This lecture covers the rationale for developing the DAQCORD, a framework for the design, documentation, and reporting of data curation methods in order to advance the scientific rigour, reproducibility, and analysis of data.

This lecture covers how you can make your data public through EBRAINS. This talk focuses on the ethical considerations for sharing data, the requirements that are imposed by various regulations, particularly for sharing human data. The lecture also includes a discussion of how EBRAINS designs its services to deal with the ethical and regulatory aspects of sharing these kinds of data.

This lecture discusses differential privacy and synthetic data in the context of medical data sharing in clinical neurosciences.