Lecture 11 - The Izhikevitch Brain

Lecture 11 covered Izhikevitch (2004) which discusses a gigantic simulation encompassing 100,000 neurons. The neurons themselves are modeled using the Izhikevich neuron model, which is a hybrid Hodgkin-Huxley/IAF neuron. The neurons were spatially distributed in a single layer across the surface of a virtual sphere and interconnected using local and projecting connections with synapses exhibiting potentiation and depression. The paper's key finding is that, as long as you provide random noise to stimulate the neurons occasionally, the neurons will cluster themselves into fairly stable functional groups that tend to fire together in sequence. Furthermore, coherent input stimuli can cause virtual receptive fields to change over time. These results are all reasonably biologically plausible and seem to bolster the theory of neural darwinism favored by co-author (and 1972 Nobel laureate) Gerald Edelman.

Amazingly, even using the lowly forward Euler with a timestep of 0.5 ms, their simulations worked at 60x realtime, meaning one second of simulated time required 60 seconds of real time to compute. They ran their simulation for 24 simulated hours, meaning the program actually required 60 days to run! Not bad for a 1GHz pentium. I wonder how long that simulation would take on a new top of the line work station these days...