Course description
Simulation Neuroscience
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!
Who should attend?
Prerequisites:
- Knowledge of ordinary differential equations, and their numerical solution
- Knowledge of programming in one of Python (preferred), C/C++, Java, MATLAB, R.
Training content
- Simulation neuroscience: An introduction,
- Neuroinformatics
- Modeling neurons
- Modeling synapses
- Constraining neurons models with experimental data
- Exam week
Course delivery details
This course is offered through Swiss Federal Institute of Technology Lausanne, a partner institute of EdX.
5-8 hours per week
Costs
- Verified Track -$169
- Audit Track - Free
Certification / Credits
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
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