fLIF neurons and CAs

I have been working with Cell Assemblies (CAs) and fatiguing Leaky Integrate and Fire (fLIF) Neurons for about 8 years now.
I've given quite a few talks here on them, and I think they are Turing complete.
our fLIF neurons:
- integrate activity from attached neurons
- ours spike if they pass a threshold (sending activity)
- activity decays (or leaks) if the neuron doesn't spike and loses all activity if it does spike
- neurons fatigue when they fire (threshold is raised), and fatigue is reduced when they don't spike
- learning is done by a type of Hebbian learning
- connections are uni-directional
- individual neurons are inhibitory or excitatory but not both
CAs are attractor states and groups of neurons that are highly connected.
CAs persist after input has ceased, but can be shut off.
CAs are the basis of concepts.
We've done a lot of work with categorisation.
More recently, we've done work with variable binding and if-then rules (which fits in nicely with NL grammars).
We have a version of the simulator (CANT) that you can use on the net, but if you want to try some simulations out, it's probably best to get the current version.