Dr Andrew P. Paplinski Dr Lennart Gustafsson

CSE2330 Introduction to Computational Neuroscience

• W.W. Lytton, From Computer to Brain: Foundations of Computational Neuroscience, Springer-Verlag New York Inc., 2002
• E.T Rolls and A. Treves, Neural Networks and Brain Functions, Oxford University Press, 2001
• P. Dayan and L. F. Abbot, Theoretical Neuroscience. Computational and Mathematical Modeling of Neural Systems, The MIT Press, 2001

"The genetic code was cracked in the mid-20th century. The neural code will be cracked in the mid-21st. Genetic science has given way to its applications in biotechnology and bioengineering. Neuroscience is still up-and-coming, the next big thing. Furthermore, as genetic manipulations and basic neuroscience add more raw facts to the broth, the need for meaning, structure, and theory becomes greater and greater. Enough information is coming together that the next generation of computational neuroscientists will make the leap into understanding. That means grant money, prizes, and fancy dinners! (If the movies are a guide, it also means evil robots, mind control, and dystopia, but let's not ruin the moment.)"

Practicals/tutorials

24hwr/7dys access to MATLAB is available in the lab 19/G14a.
Apply for after hours access to these labs via the myFIT web site at the URL listed below:
http://www.infotech.monash.edu.au/myfit/heat/login.cfm

1. Prac1 -- Basic computational tools and concepts

2. Prac2 -- Model of Limulus Vision
   Gray-scale apple

3. Prac3 -- Learning and self-organization

4. Prac4 -- Associative Memory Networks
   Scripts A : trnglDefB.m, pltSetB.m, Alzh.m
   Scripts B : AlzhGUI.m, AlzhGUI.fig, trnglDef.m, HopfConv.m, plotSet.m

   Note: Marked prac4 reports are available from the School office.

5. Not compulsory. To be considered the next year

   Prac5 -- From Soap to Volts. Hodgkin-Huxley Simulator

Lecture Notes:

• based on Chapter 1: Introduction

• based on Chapter 2: Computational Neuroscience and You

• based on Chapters 3, 4, 5: Basic Neuroscience. Computers

• based on Chapter 6: Concept Neurons

• based on Chapter 7: Neural Coding

• based on Chapter 8: Our Friend the Limulus

• based on Chapter 9: Learning and self-organization

• Modelling autism

• Associative Memory Networks: based on Chapter 10 --- part A.
  Associative Memory Networks: based on Chapter 10 --- part B.

• based on Chapter 11: From Soap to Volts

• based on Chapter 12: Hodgkin-Huxley Model

• Notes Part IVa: Selected Notes Based on Part IV: Brains