Assignments: Computational Neurosceince

Computational Neuroscience, Fall 2012

The course is for 3rd year undergraduates and graduate students of CS, and is an introduction to mathematical and computational models in the area of brain research.

1. Computer Science and Computational Neuroscience – why are they related

http://www.scholarpedia.org/article/Mind-body_problem:_New_approaches

2. Introduction to the brain physiology: synapsed to centers

3. Early models of Neural Networks

4. Introduction to MATLAB

A brief vide introduction on Matlab and Digital Signal Processing:

http://www.youtube.com/watch?v=7bnVx34yQf4

5. Introduction to Image Processing in the Biological context

6. Basic models of single neurons

Formal Neuron Models:

http://icwww.epfl.ch/~gerstner//SPNM/node26.html

(From the book by Gerstner and Kistler:
Spiking Neuron Models. Single Neurons, Populations, Plasticity
Cambridge University Press, 2002)

Comparison between several models:

http://www.izhikevich.org/publications/whichmod.htm#izhikevich (Please see the full text PDF and if you like there is a nice matlab code example that reproduces the results in the figure)

Lecture notes

7. Plasticity and learning

Synaptic Plasticity (Hebbian):

http://icwww.epfl.ch/~gerstner/SPNM/node71.html

lecture notes

8. Models of stereoscopic vision

9. Machine Learning and CNS 1

Machine Learning and fMRI (tools of the trade):

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2892746/

Predicting Choices:

http://www.nature.com/neuro/journal/v11/n5/full/nn.2112.html

Lecture notes