Topology: Building Nets

1. We're treating biological networks as a graph.
2. The nodes are the neurons, and the arcs are the synapses.
3. We have already created a lot of neurons (nodes) of predefined types. We have also already created a lot of synapses (arcs) of predefined types.
4. There are a lot of ways to use predefined mechanisms for connecting neurons, like all-to-all and one-to-all. However, they can all be built with list connectors, which we have been using.
5. If you want to do this right, you're going to have to write a bit of python; loops are particularly useful.
6. Make 100 nodes of "input neurons and 5 spike generators. (You can pick the neuron type including _IF_cond_exp.) Make the spike generators for (respectively) at 10,20,30,40 and 50 ms.
7. Hook it up (using list connectors) so that the every 5th neuron is associated with every 5th generator, and make them all spike.
8. Just modify your spike generator to add 1 more. Hook it up so every third neuron gets input from that and makes an extra spike.
9. Now, hook up the first 5 neurons so they all stimulate each other.
10. Can you get them to fire persistently.
11. Take the second five and connect them to the third five and see if you can have the first five fire the second (an extra time).
12. Can you get the neurons to fire (from just one spike source input) for between 500 and 1000 ms?