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This lesson introduces the practical exercises which accompany the previous lessons on animal and human connectomes in the brain and nervous system. 

Difficulty level: Intermediate
Duration: 4:10
Speaker: : Dan Goodman

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

Difficulty level: Intermediate
Duration: 50:44
Speaker: : Caterina Gratton

This lecture presents an overview of functional brain parcellations, as well as a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation.

Difficulty level: Advanced
Duration: 50:28
Speaker: : Pierre Bellec

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

Difficulty level: Intermediate
Duration: 50:18
Speaker: : Jeff Grethe

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.

Difficulty level: Intermediate
Duration: 1:09:33
Speaker: : Sean Hill

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. 

Difficulty level: Intermediate
Duration: 1:32:53

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

Difficulty level: Intermediate
Duration: 39:05
Speaker: : Jil Meier

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

Difficulty level: Intermediate
Duration: 37:12
Speaker: : Julie Courtiol

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.

Difficulty level: Intermediate
Duration: 17:08
Speaker: : Ari Ercole

This lecture focuses on ontologies for clinical neurosciences.

Difficulty level: Intermediate
Duration: 21:54

This talks presents an overview of the potential for data federation in stroke research.

Difficulty level: Intermediate
Duration: 21:37

This lecture explains the need for data federation in medicine and how it can be achieved.

Difficulty level: Intermediate
Duration: 27:09
Speaker: : Philippe Ryvlin

In this session the Medical Informatics Platform (MIP) federated analytics is presented. The current and future analytical tools implemented in the MIP will be detailed along with the constructs, tools, processes, and restrictions that formulate the solution provided. MIP is a platform providing advanced federated analytics for diagnosis and research in clinical neuroscience research. It is targeting clinicians, clinical scientists and clinical data scientists. It is designed to help adopt advanced analytics, explore harmonized medical data of neuroimaging, neurophysiological and medical records as well as research cohort datasets, without transferring original clinical data. It can be perceived as a virtual database that seamlessly presents aggregated data from distributed sources, provides access and analyze imaging and clinical data, securely stored in hospitals, research archives and public databases. It leverages and re-uses decentralized patient data and research cohort datasets, without transferring original data. Integrated statistical analysis tools and machine learning algorithms are exposed over harmonized, federated medical data.

Difficulty level: Intermediate
Duration: 15:05

The Medical Informatics Platform (MIP) is a platform providing federated analytics for diagnosis and research in clinical neuroscience research. The federated analytics is possible thanks to a distributed engine that executes computations and transfers information between the members of the federation (hospital nodes). In this talk the speaker will describe the process of designing and implementing new analytical tools, i.e. statistical and machine learning algorithms.  Mr. Sakellariou will further describe the environment in which these federated algorithms run, the challenges and the available tools, the principles that guide its design and the followed general methodology for each new algorithm. One of the most important challenges which are faced is to design these tools in a way that does not compromise the privacy of the clinical data involved. The speaker will show how to address the main questions when designing such algorithms: how to decompose and distribute the computations and what kind of information to exchange between nodes, in order to comply with the privacy constraint mentioned above. Finally, also the subject of validating these federated algorithms will be briefly touched.

Difficulty level: Intermediate
Duration: 20:26
Speaker: : Jason Skellariou

The Medical Informatics Platform (MIP) Dementia had been installed in several memory clinics across Europe allowing them to federate their real-world databases. Research open access databases had also been integrated such as ADNI (Alzheimer’s Dementia Neuroimaging Initiative), reaching a cumulative case load of more than 5,000 patients (major cognitive disorder due to Alzheimer’s disease, other major cognitive disorder, minor cognitive disorder, controls). The statistic and machine learning tools implemented in the MIP allowed researchers to conduct easily federated analyses among Italian memory clinics (Redolfi et al. 2020) and also across borders between the French (Lille), the Swiss (Lausanne) and the Italian (Brescia) datasets.

Difficulty level: Intermediate
Duration: 16:44
Speaker: : Mélanie Leroy

This lecture discusses risk-based anonymization approaches for medical research.

Difficulty level: Intermediate
Duration: 15:43
Speaker: : Fabian Prasser

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.

Difficulty level: Intermediate
Duration: 24:52
Speaker: : Katrin Amunts

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

Difficulty level: Intermediate
Duration: 21:57
Speaker: : Paul Boon

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. 

Difficulty level: Intermediate
Duration: 4:48
Speaker: : Marcus Ghosh

In this lesson, you will learn about how machine learners and computational neuroscientists design and build models of neuronal synapses. 

Difficulty level: Intermediate
Duration: 8:59
Speaker: : Dan Goodman