This course consists of a series of lessons which aim to introduce the basic conceptual and experimental approaches in computational neuroscience.
Computational Neuroscience: The Basics
Course Features
Lectures
Videos
Tutorials
Lessons of this Course
1
1
Duration:
1:23:01
Speaker:
This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.
2
2
Duration:
8:23
Speaker:
This lecture describes non-spiking simple neuron models used in artificial neural networks and machine learning.
3
3
Duration:
28:29
Speaker:
This lesson covers the ionic basis of the action potential, including the Hodgkin-Huxley model.
4
4
Duration:
1:11:29
Speaker:
This lesson discuses forms of neural plasticity on many levels, including short-term, long-term, metaplasticity, and structural plasticity. During the lesson you will also be presented with examples related to the modelling of biochemical networks.
5
5
Duration:
1:00:11
Speaker:
This lesson provides an introduction to modelling of chemical computation in the brain.
6
6
Duration:
15:44
Speaker:
This lesson gives a presentation on computationally demanding studies of synaptic plasticity on the molecular level.
