Time and Input
- The model (unlike real neurons) is discrete, so it has cycles.
- We've equated a cycle with 10ms of real time.
- This is somewhat arbitrary, but it enables us to avoid
properties like absolute and relative refractory periods
and synaptic delay as they occur in less than 10ms.
- Also neurons usually don't spike more than once every 10ms.
- Input is either from the environment (the simulation just adds
activity) or from other neurons. When a neuron spikes the
activity arrives at the post-synaptic neurons in the next
cycle.
- In the biological data and in this model, activation comes
directly from the environment.
- So, now we're going to get some data on neural spikes, and
see how well the FLIF model can fit the data.