Math 6770, Fall 2017
TH 12:25-1:45 (LCB 323)
Office: LCB 303, Phone: (801) 585-1639
borisyuk at math.utah.edu
If you would like to meet, email me or come by
This will be an interdiscplinary class,
for students with a variety of backgrounds.
Some experience in MATLAB, ODEs and probability will be beneficial.
If you have any question or concerns about prerequisites
or topics to be covered, please contact me.
Besides attending lectures, students will be expected to do several (4-5)
sets, read scientific
papers and work on projects. Your grade will be based on your class partcipation(10%), homeworks(40%), and the project (50%).
The class material will be drawn from many different sources,
including books and research papers. Here is a
list of books that are a good reference,
but none of them covers the exact course contents,
and they are not required
Week 1 – 4. Phase plane and bifurcation analysis of neuronal models. Working with Matlab, Xpp, and Auto.
Week 5. Dynamical systems approach to population models
Week 6. Reduced models (integrate-and-fire and its varieties, theta model), adaptation
Week 7. Noisy synaptic input, filtering and resonance properties of neurons.
Week 8/9. Different types of noise in neural systems, their contribution to spike correlations and population oscillations
Week 10. Phase response curves, synchronization
Week 11/12. Synaptic plasticity. Spike time dependent plasticity
Week 13/14. Case-studies/Applications. Unlearning synchronization (tinnitus),
Tuning of sound localization system, Calcium-based model of synaptic plasticity
Week 12 on. Class project.
You are encouraged to work in pairs, especially with people
whose background is different from yours.
Feel free to talk to me about your idea to discuss its feasibility before
November 17 - project proposal due
Meet with me at least once before December 1 to show me your progress!
December 7 - in class presenations
December 15 at noon - written resports are due