- There are two main things needed for the project
- build a simulation of a neurobiological system
- evaluate its behaviour
You will produce a written report on your system (due at the end of exams). This should be 10-20 pages, with lots of diagrams, graphs, and code.
To design the system, follow the steps outlined in Chapter 1 of the book:
- 1) System Description: Indicate the variable $x$ being represented by each group of neurons, and what function $f(x)$ is being computed by each connection between groups of neurons
- 2) Design Specification: List the known neural details for the system. This includes things like maximum firing rates, tuning curves, neuron models, post-synaptic time constants, and so on. This will generally require turning to the literature and finding data on the system you are modelling.
- 3) Implementation: Given these constraints, build the model. You can either use the code you have written during the assignments, or you can use Nengo.
To evaluate the behaviour of the system, the idea is to vary some aspect of the model and see how that affects its behaviour. To do this, you must
- 1) Define some measurable aspect of the system's behaviour (e.g. accuracy of representation, or number of errors, or speed of response)
- 2) Change an aspect of the model (e.g. number of neurons, or neuron model, or maximum firing rates, or post-synaptic time constants, etc., etc.), and see how that affects the measurement. Note that because there is randomness in the creation of a neuron model, you will generally have to measure a model multiple times.