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Computational Neuroscience - Fall 2008

Project 1

This project involved modeling a simple neuron using the Hodgkin-Huxley equations and then use the passive membrane equations to build a compartmental model of a neruon comprising of a some and a dendrite that branches in two.

Project 1 report [PDF]
Project 1 code (python) [zip]

Project 2

This project involved using the aymptotic equipartition property to find the number of bits, on average, necessary to encode a string of length 20. Also, I built a feed forward neural network of sigmoidal nodes to learn the concept of a circle in 2D space (which turns out not to work well) as well as built a Hopfield net for image retrieval. Code for the neural network and Hopfield net are included below.

Project 2 report [PDF]
Project 2 code (MATLAB) [zip]

Project 3

This project was the construction of a dynamical system to visualize how a simple system gives rise to complex behavior.

Project 3 report [PDF]