fLIF Neurons
- One tricky thing is to figure out the right model for
the neuron.
- The one that we are using is the fatiguing Leaky Integrate
and Fire (fLIF) neuron.
- There are more accurate models (like compartmental models),
but fLIF neurons are really efficient to simulate.
- Neurons integrate activity (energy) from other neurons.
- If they get enough, they fire.
- They lose all their activity when they fire.
- If they don't get enough activity, some leaks away, but some is
retained. This makes it easier to fire later.
- Each time they fire, the threshold is raised making it
more difficult to fire. That is they get tired or fatigue,
though the fatigue goes away after awhile.
- These are all biologically acurate, though we don't always use
biologically acurate parameters.
- We simulate with cyles that are equivalent to 10 ms. So the
simulated neurons can fire up to 100 times a second.
- We currently have two classes of neurons, inhibitory and excitatory.
