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Tools and services tutorials

The single entry point to tutorials for EBRAINS tools and services. Here, you can find a list of EBRAINS offerings, sorted by topic, and links to their tutorials.


Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows

Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system works or why certain phenomena are observed. Data-driven modeling, on the other hand, follows a more unbiased approach, with model construction informed by the computationally intensive use of data.

Modelling and simulation

AKAP79 enables calcineurin to directly suppress protein kinase A activity

Interplay between the second messengers cAMP and Ca2+ is a hallmark of dynamic cellular processes. A common motif is the opposition of the Ca2+-sensitive phosphatase calcineurin and the major cAMP receptor, protein kinase A (PKA). Calcineurin dephosphorylates sites primed by PKA to bring about changes including synaptic long-term depression (LTD).

Modelling and simulation

Uncertainty quantification, propagation and characterization by Bayesian analysis combined with global sensitivity analysis applied to dynamical intracellular pathway models

Dynamical models describing intracellular phenomena are increasing in size and complexity as more information is obtained from experiments. These models are often over-parameterized with respect to the quantitative data used for parameter estimation, resulting in uncertainty in the individual parameter estimates as well as in the predictions made from the model. Here we combine Bayesian analysis with global sensitivity analysis (GSA) in order to give better informed predictions; to point out weaker parts of the model that are important targets for further experiments, as well as to give guidance on parameters that are essential in distinguishing different qualitative output behaviours.

Modelling and simulation

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a variety of different software tools in the model building and analysis process. Here we focus on the scale of biochemical pathways, which is one of the main objects of study in systems biology.

Modelling and simulation

Building and simulating a simple model using PyNN

In this tutorial, you will learn how to build a simple network of integrate-and-fire neurons using PyNN, how to run simulation experiments with this network using different simulators, and how to visualize the data generated by these experiments.

Modelling and simulation

The Virtual Brain: INCF TVB Training Space

In this short series of lectures, participants look at articles using TVB in a clinical context. Specifically, participants will see how TVB can help to predict recovery after stroke and how individual epileptic seizures are simulated. The course lecturers will briefly describe the methods and results achieved in the articles. Using the graphical user interface, participants will replicate the principle ideas of the articles and see how artificial lesions introduced in the connectome alter brain dynamics and how seizures spreading through the brain network can be modelled. All videos use the default TVB dataset, so you can follow each step in your TVB GUI.

Modelling and simulation

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