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

This talk presents state-of-the-art methods for ensuring data privacy with a particular focus on medical data sharing across multiple organizations.

This lecture talks about the usage of knowledge graphs in hospitals and related challenges of semantic interoperability.

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 tutorial introduces pipelines and methods to compute brain connectomes from fMRI data. With corresponding code and repositories, participants can follow along and learn how to programmatically preprocess, curate, and analyze functional and structural brain data to produce connectivity matrices. 

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

In this final lecture of the INCF Short Course: Introduction to Neuroinformatics, you will hear about new advances in the application of machine learning methods to clinical neuroscience data. In particular, this talk discusses the performance of SynthSeg, an image segmentation tool for automated analysis of highly heterogeneous brain MRI clinical scans.

This lesson gives an introduction to the central concepts of machine learning, and how they can be applied in Python using the scikit-learn package. 

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

This lesson provides an overview of the current status in the field of neuroscientific ontologies, presenting examples of data organization and standards, particularly from neuroimaging and electrophysiology. 

This lecture focuses on ontologies for clinical neurosciences.

This lecture discusses the the importance and need for data sharing in clinical neuroscience.

This lecture presents the Medical Informatic Platform's data federation for Traumatic Brain Injury.

This lecture gives insights into the Medical Informatics Platform's current and future data privacy model.

This lecture explains the concept of federated analysis in the context of medical data, associated challenges. The lecture also presents an example of hospital federations via the Medical Informatics Platform.

This lecture gives an overview on the European Health Dataspace. 

This lecture presents the Medical Informatics Platform's data federation in epilepsy.

This lecture presents the Medical Informatics Platform's data federation in epilepsy.

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 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.