Next steps

After speaking with John Bullinaria today we've worked out the next steps I should be taking on the way to creating the Thesis Proposal:

1.  Continue implementing some of the older models (e.g. Ruppin and Reggia (1995)), and repeating the experiments to compare results.
1. Try other lesions, such as adding noise to the connections.
2. What symptoms appear?
3. What do these symptoms represent? (This could lead to a basic paper).
2. Identify weaknesses in the models, and gaps in what they can tell us.
1. Be analytical: are the assumptions of ~15 years ago still correct? Is a Hopfield network still the best type of model?
2. Identify possible improvements (preferably the ones involving the minimum work and the maximum impact).
3. Identify a selection of plausible hypotheses from the medical literature, and investigate how these could be modelled in existing or new model classes.
3. Investigate more recent classes of neural model which can be adapted for studying Alzheimer's disease; for example:
1. Contrastive Hebbian learning.
2. LEABRA learning.
3. Work by John Jefferys, Rolls and Loh, etc.
4. Recent and more comprehensive models of normal working memory, particularly ones involving the two stages of hippocampal and long-term memory storage (e.g. by McLelland).

This last point (3) is perhaps the most important, as the premise that I need to work from recent and comprehensive models of memory is vital. There is not much point in trying to incrementally improve basic 15-year old models of AD when neural modelling has moved on a great deal in that time. A better approach would be to take these more recent models and lesion them to study AD, using the lessons learned from the older research.

John also recommended looking into PDP++ (now called Emergent), a neural network simulator which could save some implementation time, and that for the thesis proposal I shouldn't worry too much about drawing up a specific single hypothesis, but rather focus on the experimental methodology I'll be employing (i.e. applying past work on AD modelling to recent working memory models).