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Watch a demonstration of the Human Intracerebral EEG Platform.

This tutorial guides the user through the process of setting up and running RAMD simulations for estimation of the relative residence time (τ) of a protein-small molecule complex using the GROMACS software. The procedure is demonstrated for a complex of a low molecular weight compound with the N-terminal domain of the heat shock protein, HSP90.

This course contains an introduction to currently available reference atlases for mouse and rat brain. It will demonstrate how the 3D brain templates for the reference atlases are acquired, how they are used as a basis for delineating the structures of the brain, how they can be enriched by other data modalities, and how they can be used as a basis for assigning location (coordinate based or semantic) to a wide range of structural and functional data collected from the brain.

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.

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.

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).

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.

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.

This study includes 40 mice (20 at 6 months(m), 20 at 14 months(m); 2 males and 38 females). Of the mice, 29 are from 14 AD-BXD strains, 2 are the C57B1/6J founder strain, 6 are the F1 B6/DBA/2J (D2) 5XFAD founder strain, and 3 are nontransgenic (Ntg)-BXD.

We present ilastik, an easy-to-use interactive tool that brings machine-learning-based (bio)image analysis to end users without substantial computational expertise.