I did take the code he mentions and play with it. Is behaviour is fascinating. I hope to be still alive when we have enough computing power for simulating a single brain, and to be able to directly cross-connect it to mine.
The guy you linked to is using a simpler two-variable model with correspondingly lower fidelity. The goal of the Blue Brain Project, which this guy seems to think he has bested, is to model all of the features of a biological neuron and, more importantly, how they wire together.
Very interesting, thanks! I know about Blue Brain, but did not touch on any code of theirs - seeing you did.
How fast is your code performance-wise ?
I think the point he is making is that his model is "good enough".
The code that I was running was able to emulate ~40000 neurons and their connections on a Lenovo T60 laptop in realtime. (the number might be off by an order of 2-4, I remember playing with different numbers, but do not remember the exact value).
Interesting thing was that the "waves" that emerged by themselves, and with a certain size of the network they were sustainable even when I removed the initial "random noise" stimuli.
I did not figure out a decent way to attach the inputs/outputs to this "soup". Since this capacity does approach the brain size of an ant, might be fun to toy with a "virtual world" "inhabited" by connected computers running the simulation.
Could be a fun project, even if a little impractical. (Though I sadly lack the knowledge in the domain to make it happen).
Yes, I did an internship for the BBP last year. This is not based in any way on their work.
That code has problems simulating multiple neurons for some reason (possibly thread safety in GSL?). But, it can simulate one neuron at 20x realtime, with dumping traces to disk. If I were to disable dumping traces, it'd be primarily limited by GSL's differential equation solver.
(Sorry, too tired to respond to the second half of your comment)
I pulled the equations from Parameter estimation in hindmarsh-rose neurons (Steur, 2006), equation 4.1.
The Hindmarsh-Rose, Hodgkin–Huxley, and other mathematical models are phenomenological models. They are meant to reproduce the observable characteristics, like the peak potential, bursting behaviour, refractory period, things like that. They can reproduce the traces of biological neurons with good accuracy (like the link in the GP), and the papers describing the model mention ion channels and whatnot, but they're very abstract. They're not made to reproduce the biology.
The mathematical model for a spiking neuron is reasonably well understood, as far as I know: http://izhikevich.org/human_brain_simulation/Blue_Brain.htm
I did take the code he mentions and play with it. Is behaviour is fascinating. I hope to be still alive when we have enough computing power for simulating a single brain, and to be able to directly cross-connect it to mine.