And now it's going to take over the world, mwahahahahaa....
Well not quite, but in the last two weeks I've implemented (in Java) the model by Ruppin and Reggia (1995) which creates a non-fully-connected Hopfield network, gets it to learn a number of patterns or 'memories', in an activity-dependent Hebbian manner ("cells that fire together, wire together"), and then tries to recall them.
Up to a certain number of patterns (n / 2 log n, where n is the number of neurons in the network) it works beautifully and then, as expected, once its memory is 'full' recall performance drops dramatically. I'm yet to formally carry out any experiments along the same lines as Ruppin and Reggia, but initial results seem to indicate my implementation gives roughly the same behaviour as their model.
Ruppin and Reggia were only able to create networks up to 1600 neurons in size, due to the limited computing power available at the time. With my implementation I've already successfully run networks of 100,000 neurons in size (=10,000 memories!) in the default Java heap space of 64MB. By increasing the heap space -- and being very patient as it will take a long time to run -- I hope to be able to demonstrate networks of maybe up to half a million neurons in size. Whether that will enhance the experimental results at all remains to be seen.
Next steps are to implement network lesioning -- that is, damaging the network by deleting neurons and/or synapses, in an attempt to get it to develop symptoms similar to Alzheimer's disease, and recreate the experiments of Ruppin and Reggia (1995) on a larger scale.
After that, the model will be extended further to try to imitate symptoms of schizophrenia, as in Ruppin et al. (1996). There is also an alternative model of Alzheimer's disease introduced by Horn et al. (1996) which I'd like to implement, and no doubt I'll find some others in the literature during that time as well (including hopefully some more recent than the mid-1990s). During that time I'll also have to write up my current reading for the RSMG2 report, due in May of this year.
Horn, D., Levy, N., Ruppin, E. (1996), "Neuronal-based synaptic compensation: a computational study in Alzheimer's disease", in Neural Computation 8:1227--1243.
Horn, D., Levy, N., Ruppin, E. (1998), "Memory maintenance via neuronal regulation", in Neural Computation 10:1--18.
Ruppin, E. and Reggia J. (1995), "A neural model of memory impairment in diffuse cerebral atrophy", in British Journal of Psychiatry 166:19--28
Ruppin, E., Reggia, J., Horn, D. (1996), "Pathogenesis of schizophrenic delusions and hallucinations: a neural model", Schizophrenia Bulletin (22)1:105-123