This tutorial demonstrates how to work with neuronal data using MATLAB, including actional potentials and spike counts, orientation tuing curves in visual cortex, and spatial maps of firing rates.

This lesson instructs users on how to import electrophysiological neural data into MATLAB, as well as how to convert spikes to a data matrix.

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

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

This lecture gives an overview on the European Health Dataspace. 

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. 

Along the example of a patient with bi-temporal epilepsy, we show step by step how to develop a Virtual Epileptic Patient (VEP) brain model and integrate patient-specific information such as brain connectivity, epileptogenic zone and MRI lesions. The patient's brain network model is then evaluated via simulation, data fitting and mathematical analysis. This lecture demonstrates how to develop novel personalized strategies towards therapy and intervention using TVB.

This lecture focuses on higher-level simulation scenarios using stimulation protocols. We demonstrate how to build stimulation patterns in TVB, and use them in a simulation to induced activity dissipating into experimentally known resting-state networks in human and mouse brain, a well as to obtain EEG recordings reproducing empirical findings of other researchers.

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 lesson introduces population models and the phase plane, and is part of the The Virtual Brain (TVB) Node 10 Series, a 4-day workshop dedicated to learning about the full brain simulation platform TVB, as well as brain imaging, brain simulation, personalised brain models, and TVB use cases.

This lesson introduces TVB-multi-scale extensions and other TVB tools which facilitate modeling and analyses of multi-scale data. 

This lecture delves into cortical (i.e., surface-based) brain simulations, as well as subcortical (i.e., deep brain) stimulations, covering the definitions, motivations, and implementations of both. 

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 gives an overview of how to prepare and preprocess neuroimaging (EEG/MEG) data for use in TVB.  

In this lecture, you will learn about various neuroinformatic resources which allow for 3D reconstruction of brain models. 

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