This course is directed at Bachelor, Master, and Diploma students and to PhD
Students of the BCCN. The practical course "Scientific Programming - an
Introduction to Python" is an excellent preparation for this course, however
no prior knowledge of programming languages or computers is
necessary. It is helpful to have covered this material before starting a
Diploma or Master's project with a theoretical focus.
This course covers the fundamentals of simulating networks of
single-compartment spiking neuron models. We start from the concept of a
point neuron and then introduce more complex topics such as phenomenological
models of synaptic plasticity, connectivity patterns and network dynamics.
Along the way we examine a variety of modeling studies from the field of
theoretical neuroscience and reproduce some key results. At the end of the
course a student will have the ability to develop his or her own biological
neural network models and to re-create models from neuroscientific
literature.
The format of the course consists of a lecture in the morning followed by
hands-on activity to put the concepts learned in the lecture into practice.
For the practical activities we use the simulator NEST
(www.nest-initiative.org). The course ends with a colloquium; there will be
no written protocols after the course.
The course material (handouts, exercises) and lectures will be in English.
