Lecture: Richard Kempter
Tutorial: Jakob Heinzle and Jan-Hendrik Schleimer
Computer Practical: Robert Schmidt and Bartosz Telenczuk
Place: Computer Pool — BCCN building
Time: Mondays, 16:00 – 18:00 hr
Module Website:
http://itb.biologie.hu-berlin.de/~kempter/Teaching/2009_WS-Models-of-Neural-Systems/index.html
Assignments:
- Exercise Sheet 1 – basic Python
- Exercise Sheet 2
- Exercise Sheet 3 – supervised learning, McCulloch-Pits neuron, perceptron, linear separability
- Exercise Sheet 4 – visual receptive fields, Gabor filters, tuning curves
- Exercise Sheet 5 – ordinary differential equations, linear membrane, integrate-and-fire neuron
- Exercise Sheet 6 – synaptic inputs, shunting inhibition, persistent potassium channels
- Exercise Sheet 7 – sodium channel, Hodgkin-Huxley model
- Exercise Sheet 8 – channel models
Projects:
- Project 1 – phase oscillators (supervised by B. Telenczuk)
- Project 2 – synfire chains (supervised by B. Telenczuk)
- Project 3 – spike-timing-dependent plasticity (supervised by B. Telenczuk)
- Project 4 – adaptive exponential integrate-and-fire model (supervised by B. Telenczuk)
- Project 5 – reward-related learning in animals (supervised by R. Schmidt)
- Project 6 – temporal Pattern Learning (supervised by R. Schmidt)
- Project 7 – stochastic ion channels (supervised by R. Schmidt)
- Project 8 – complex cells tuned to disparity (supervised by R. Schmidt)
Additional materials:
Some tips about using pyreport to generate reports of your solutions.
A module with helper functions used for some of the exercises.
A template for preparing project reports: TeX, PDF
Papers:
Hodgkin, Huxley, J Physiol, 1952, URL
Links:
Models of Neural Systems: Teaching Materials by Robert Schmidt, Bartosz Telenczuk is licensed under a Creative Commons Attribution-Share Alike 3.0 Unported License.