Computational Modelling in Neuroscience

Module code: BS7107

You will acquire knowledge on single neuron (and compartmental) models and their integration into network models. Artificial neural networks will also be covered, including deep neural networks. You will also study different topologies associated with network connectivity and their properties (such as random, scale free and small world). Finally, you will be introduced to more abstract models used in neuroscience (such as Markov models for decision making and time-difference models for reinforcement learning).

Learning

  • 20 hours of lectures
  • 6 hours of project supervision
  • 9 hours of demonstration
  • 10 hours of practicals
  • 255 hours of independent study

Assessment

  • Essay (20%)
  • Exam, 2 hours (40%)
  • Programming project with written report (40%)