Welcome to 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.

This page is work in progress. It is incomplete for now. But it will include all of EBRAINS tutorials very soon. 

Some tutorials are also available on EBRAINS YouTube channel.

Arbor

• A simple single cell model (beginner)
• A detailed single cell model (advanced)
• A detailed single cell recipe (advanced)
• A ring network (advanced)
• A simple dendrite (advanced)
• A simple single cell recipe (advanced)
• A single cell model from the Allen Brain Atlas (advanced)
• A single cell model from the BluePyOpt Cell Optimisation Library (advanced)
• Distributed ring network (MPI) (advanced)
• Extracellular signals (LFPykit) (advanced)
• GPU and profiling (advanced)
• Spike Timing-dependent Plasticity Curve (advanced)
• Two cells connected via a gap junction (advanced)

Electrophysiology Analysis Toolkit

• Statistics of spike trains (beginner)
• ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains (advanced)
• Gaussian Process Factor Analysis (advanced)
• Parallel (advanced)
• Spike Pattern Detection and Evaluation (SPADE) (advanced)
• The Unitary Events Analysis (advanced)
• Time-domain Granger Causality (advanced)

NEST

• Introduction to NEST: Simulating a single neuron (beginner)
• Neurons and simple neural networks (beginner)
• Populations of neurons (beginner)
• Connect two NEST simulations using MUSIC (advanced)
• Connecting networks with synapses (advanced)
• Introduction to the MUSIC Interface (advanced)
• MUSIC Connections in C++ and Python (advanced)
• MUSIC with SLI (advanced)
• Practical tips (advanced)
• Spatially structured networks (advanced)
• The pymusic interface (advanced)

NESTML

• Izhikevich tutorial (beginner)
• Active dendrite tutorial (advanced)
• Dopamine-modulated STDP synapse tutorial (advanced)
• Ornstein-Uhlenbeck noise tutorial (advanced)
• STDP synapse tutorial (advanced)
• STDP windows tutorial (advanced)

Neuron

• Construction and Use of Models: Part 1. Elementary tools (beginner)
• The hoc programming language (beginner)
•  Introduction to Network Construction (advanced)
• 1. Implement and test the computational model itself (advanced)
• 2. Run a "complete" simulation and save its results (advanced)
• 3. Run a segmented simulation and save its results (advanced)
• 3D/Hybrid Intracellular Tutorial (advanced)
• 4. Reconstitute and verify the "complete" simulation results (advanced)
• A NEURON Programming Tutorial - Part A (advanced)
• A NEURON Programming Tutorial - Part B (advanced)
• A NEURON Programming Tutorial - part C (advanced)
• A NEURON Programming Tutorial - Part E (advanced)
• Ball and Stick model part 1 (advanced)
• Ball and Stick model part 2 (advanced)
• Ball and Stick model part 3 (advanced)
• Ball and Stick model part 4 (advanced)
• Creating a channel from a kinetic scheme specification (advanced)
• Creating a channel from an HH-style specification (advanced)
• Creating a model of stochastic channel gating (advanced)
• Creating a stylized ("stick figure") model cell (advanced)
• Dealing with simulations that generate a lot of data (advanced)
• Example: circadian rhythm (advanced)
• Example: restricting a reaction to part of a region (advanced)
• Exploring morphometric data and fixing problems (advanced)
• Extracellular Diffusion (advanced)
• How to generate independent random spike streams (advanced)
• Managing a model cell with complex anatomy (advanced)
• mGluR example (advanced)
• ModelView: Compact display of parameters for NEURON models. (advanced)
• Python introduction (advanced)
• Randomness in NEURON models (advanced)
• Reaction-Diffusion (advanced)
• Reaction-Diffusion: Calcium Wave (advanced)
• Reaction-Diffusion: Thresholds (advanced)
• Reaction-Diffusion: varying initial concentrations and parameters (advanced)
• Reading a morphometric data file and converting it to a NEURON model (advanced)
• RxD with MOD files (advanced)
• Scripting NEURON basics (advanced)
• Segmenting a simulation of a model cell (advanced)
• Segmenting a simulation of a model network (advanced)
• Source code that demonstrates the solution (advanced)
• Specifying parameterized variation of biophysical properties (advanced)
• The solution (advanced)
• Tutorial 1 : Fitting a function to data (advanced)
• Tutorial 1: Making Networks of Artificial Neurons (advanced)
• Tutorial 2 : Fitting a model to data (advanced)
• Tutorial 2: Making Hybrid Nets (advanced)
• Using Import3D (advanced)
• Using NEURON's Optimization Tools (advanced)

Neurorobotics Platform

• Drag and drop experiment set up with multiple robots (beginner)

PyNN

• Building and simulating a simple model (beginner)
• Installing PyNN on a Linux system (beginner)

The Virtual Brain

• Building Your Own Brain Network Model (beginner)
• Getting Started (beginner)
• My first simulation with The Virtual Brain (beginner)
• Population Models in The Virtual Brain (TVB) and the Phase Plane (beginner)
• Brain stimulation in The Virtual Brain (advanced)
• Clinical Applications - Stroke Recovery & Dementia (advanced)
• Evoked Responses in the Visual Cortex (advanced)
• Exploring a model (advanced)
• Hands-On: Modeling stroke brain (advanced)
• Human Brain Project (HBP) TVB-NEST co-simulation (advanced)
• Import Virtual Brain ready data into TVB and create a brain model (advanced)
• Integrated workflows: Image processing pipeline (advanced)
• Modeling brain dynamics in brain tumor patients using The Virtual Brain (advanced)
• Modeling Epilepsy (advanced)
• Modelling Epilepsy with The Virtual Brain (advanced)
• Region simulation tutorial (advanced)
• Resting State Networks (advanced)
• Simulating The Virtual Mouse Brain (TVMB) (advanced)
• Simulating The Virtual Mouse Brain (TVMB) (Copy) (advanced)
• Surface simulation tutorial (advanced)
• Surface-based simulations and deep brain stimulations (advanced)
• The Bayesian Virtual Epileptic Patient (BVEP) (advanced)
• TVB to NEST multi-scale simulation (advanced)

VoluBA

• Anchoring partial volumetric data to BigBrain using VoluBA (-)

ilastik

• Boundary-based segmentation with Multicut (advanced)
• Carving Workflow (advanced)
• Cell Density Counting Workflow (advanced)
• EBRAINS Atlases - QUINT workflow Tutorial (advanced)
• Object Classification (advanced)
• Pixel Classification workflow (advanced)
• Tracking MaMuT Export (advanced)
• Tracking workflow (advanced)