University of Washington - coursera: Computational Neuroscience


This coursera course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. Computational Neuroscience has three main puposes:

  1. Create descriptive model of the brain: how do neurons respond to external stimuli ? How can we extract informations from neurons ?
  2. Create mechanistic models of brain cells and networks: how can we simulate the behaviour of the single neuron ? How do we simulate a whole network of neurons ?
  3. Create interpretive models of the brain: Why neurons / networks operate the way they do ?

The reason I took this course is both because I am interested on how the brain works and because of my related interest in Artificial Intelligence.


This is a 8 weeks course. As most coursera classes, it is composed of videos, quizzes and programming assignments (automatically checked online). Completing all this takes me around 4 hours a week ; about 1 hour and a half watching videos, and 2 hours and half answering quizzes and programming assignments.

  • Week 1: Course Introduction and Basic Neurobiology
  • Week 2: What do Neurons Encode? Neural Encoding Models
  • Week 3: Extracting Information from Neurons: Neural Decoding
  • Week 4: Information and Coding Principles
  • Week 5: Simulating the Brain from the Ground Up: Models of Single Neurons
  • Week 6: Modeling Synapses and Networks of Neurons
  • Week 7: How do Brains Learn? Modeling Synaptic Plasticity and Learning
  • Week 8: Learning to Act: Reinforcement Learning


The quality of the videos were great, I found the course content a little bit difficult to understand because of the very high mathematical level.


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