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About this courseSkip About this course
Simulation Neuroscience is an emerging approach to integrate the knowledge dispersed throughout the field of neuroscience.
The aim is to build a unified empirical picture of the brain, to study the biological mechanisms of brain function, behaviour and disease. This is achieved by integrating diverse data sources across the various scales of experimental neuroscience, from molecular to clinical, into computer simulations.
This is a unique, massive open online course taught by a multi-disciplinary team of world-renowned scientists.In this first course, you will gain the knowledge and skills needed to create simulations of biological neurons and synapses.
This course is part of a series of three courses, where you will learn to use
state-of-the-art modeling tools of the HBP Brain Simulation Platform to simulate neurons, build neural networks, and perform your own simulation experiments.
We invite you to join us and share in our passion to reconstruct, simulate and understand the brain!
At a glance
- Language: English
- Video Transcript: English
- Associated skills: Artificial Neural Networks, Computer Simulation, Biology, Simulations
What you'll learnSkip What you'll learn
- Discuss the different types of data for simulation neuroscience
- How to collect, annotate and register different types of neuroscience data
- Describe the simulation neuroscience strategies
- Categorize different classification features of neurons
- List different characteristics of synapses and behavioural aspects
- Model a neuron with all its parts (soma, dendrites, axon, synaps) and its behaviour
- Use experimental data on neuronal activity to constrain a model
Week 1: Simulation neuroscience: An introduction,
Understanding the brain
Approaches and Rationale of Simulation Neuroscience
The principles of simulation neuroscience
Reconstruction and simulation strategies
Summary and Caveats
Single neuron data collection techniques
Caveats and summary of experimental data techniques
Single neuron data
Summary and Caveats
Week 2: Neuroinformatics
Introduction to neuroinformatics
Data integration and knowledge graphs
Brain atlases and knowledge space
Motivation of data-integration
Fixed data approach to data integration
Blue Brain Nexus
Architecture of Blue Brain Nexus
Design a provenance entity
Creating your own domain
Acquisition of neuron electrophysiology and morphology data
Design an entity
An entity design and the provenance model
Morphological feature extraction
Understanding neuronal morphologies using NeuroM
Statistics and visualisation of morphometric data
Week 3: Modeling neurons
Introduction to the single neuron
Motivation for studying the electrical brain
A structural introduction
An electrical device
Electrical neuron model
Modeling the electrical activity
Hodgkin & Huxley
Tutorial creating single cell electrical models
Single cell electrical model: passive
Making it active
Adding a dendrite
Week 4: Modeling synapses
Modeling synaptic potential
Modeling the potential
Rall's cable model
Modeling synaptic transmission between neurons
Modeling synaptic transmission
Modeling dynamic synapses tutorial
Defining your synaps
Compiling your modifies
Hosting & testing your synaps model
Reconfigure your synaps to biological ranges
Defining a modfile for a dynamic TM synapse
Compiling and testing the modfile
Week 5: Constraining neurons models with experimental data
Constraining neuron models with experimental data
Constraining neuron model with experimental data.
Computational aspects of optimization
Tools for constraining neuron models
Tutorials for optimization
Setting up the components
Week 6: Exam week
Accessing the NMC portal
Running models on your local computer
Downloading and interacting with the single cell models
Injecting a current
Learner testimonialsSkip Learner testimonials
"I like the content and the attempt to cover difficult and interesting material at the right level."
"I like the revision of the basic concepts of the neuronal modeling and all other nomenclatures used in neuroscience study."
"The tutorials+assignments were a good combination of exposing us to the basics of both Python and Neuron."
"Also it's great to have access to the platform (HBP Neurosimulation platform)."
Frequently Asked QuestionsSkip Frequently Asked Questions
What web browser should I use?
The Open edX platform works best with current versions of Chrome, Firefox or Safari, or with Internet Explorer version 9 and above. However,the HBP platform on which you will do your weekely exercises only works with Firefox and Chrome
What tools or programs do I need?
You will learn to use the tools of the HBP brain simulation and neuroinformatics platforms. For this, you will set up a collab at the HBP platform starting week 2.
I'm an EPFL student, can I get ECTS (credits) for this MOOC?
EPFL Doctoral students may get credits for this, see EPFL Doctoral School Pages. You should apply to your program director.