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In this module, you will work with human EEG data recorded during a steady-state visual evoked potential study (SSVEP, aka flicker). You will learn about spectral analysis, alpha activity, and topographical mapping. The MATLAB code introduces functions, sorting, and correlation analysis.

Difficulty level: Intermediate
Duration: 8:51
Speaker: : Mike X. Cohen

This lecture on generating TVB ready imaging data by Paul Triebkorn is part of the TVB Node 10 series, a 4 day workshop dedicated to learning about The Virtual Brain, brain imaging, brain simulation, personalised brain models, TVB use cases, etc. TVB is a full brain simulation platform.

Difficulty level: Intermediate
Duration: 1:40:52
Speaker: : Paul Triebkorn
Course:

This book was written with the goal of introducing researchers and students in a variety of research fields to the intersection of data science and neuroimaging. This book reflects our own experience of doing research at the intersection of data science and neuroimaging and it is based on our experience working with students and collaborators who come from a variety of backgrounds and have a variety of reasons for wanting to use data science approaches in their work. The tools and ideas that we chose to write about are all tools and ideas that we have used in some way in our own research. Many of them are tools that we use on a daily basis in our work. This was important to us for a few reasons: the first is that we want to teach people things that we ourselves find useful. Second, it allowed us to write the book with a focus on solving specific analysis tasks. For example, in many of the chapters you will see that we walk you through ideas while implementing them in code, and with data. We believe that this is a good way to learn about data analysis, because it provides a connecting thread from scientific questions through the data and its representation to implementing specific answers to these questions. Finally, we find these ideas compelling and fruitful. That’s why we were drawn to them in the first place. We hope that our enthusiasm about the ideas and tools described in this book will be infectious enough to convince the readers of their value.

 

Difficulty level: Intermediate
Duration:
Speaker: :

This lecture focuses on ontologies for clinical neurosciences.

Difficulty level: Intermediate
Duration: 21:54

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

Difficulty level: Intermediate
Duration: 25:22
Speaker: : Thomas Berger

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

Difficulty level: Intermediate
Duration: 25:55
Speaker: : Stefano Finazzi

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

Difficulty level: Intermediate
Duration: 17:29
Speaker: : Yannis Ioannidis

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.

Difficulty level: Intermediate
Duration: 19:15
Speaker: : Yannis Ioannidis

This lecture gives an overview on the European Health Dataspace. 

Difficulty level: Intermediate
Duration: 26:33

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

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

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

Difficulty level: Intermediate
Duration: 26:51
Speaker: : Pawel Swieboda

DAQCORD is a framework for the design, documentation and reporting of data curation methods in order to advance the scientific rigour, reproducibility and analysis of the data. This lecture covers the rationale for developing the framework, the process in which the framework was developed, and ends with a presentation of the framework. While the driving use case for DAQCORD was clinical traumatic brain injury research, the framework is applicable to clinical studies in other domains of clinical neuroscience research.

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

This presentation discusses the impact of data sharing in stroke.

Difficulty level: Intermediate
Duration: 16:33
Speaker: : Valeria Caso

This talks discusses data sharing in the context of dementia. It explains why data sharing in dementia is important, how data is usually shared in the field and illustrates two examples: the Netherlands Consortium Dementia cohorts and the European Platform for Neurodegenerative Diseases.

Difficulty level: Intermediate
Duration: 21:21

This talk introduces data sharing initiatives in Epilepsy, particularly across Europe.

Difficulty level: Intermediate
Duration: 13:56
Speaker: : J. Helen Cross

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

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 talks presents ethics requirements of the Medical Informatics Platform, a data sharing platform for medical data using data federation mechanisms. The talk presents how the Medical Informatics Platform (MIP) works and which ethical requirements need to be considered when working with federated data.

Difficulty level: Intermediate
Duration: 16:25
Speaker: : Erika Borcel