Week 1. Biophysical and reduced neuronal models (6/2)
Tasks: Construct Izhikevich neuron model
Week 2. Parameter search and optimization methodologies (6/8)
Tasks: Build random parameter search procedure
Week 3. Iterative simulations in series and in parallel (6/15)
Tasks: Simulate large number of Izhikevich neuron models in spiking and
bursting activity regimes
Week 4. Features of neural activity (6/22)
Tasks: Compute features of generated neural activity
Week 5. Mathematics of artifical neural network (ANN) model (6/29)
Tasks: Derive mathematical model of ANN
Week 6. Mathematics of ANN model supervised learning procedure
(7/6)
Tasks: Derive mathematical representation of supervised learning
procedure
Week 7. Computational mathematics and linear algebra (7/13)
Tasks: Implement mathematical model of ANN computationally
Week 8. Computational mathematics and linear algebra cont’d (7/20)
Tasks: Continue computational implementation of mathematical ANN model
Week 9. EXTRA TIME (7/27)
Week 10. EXTRA TIME (8/3)
Week 11. EXTRA TIME (8/10)
NOTE: Simulated data not included in repo