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Those parrot neurons, or why you never connect devices to each other

In receive.py in Part 2 of the MUSIC tutorial, we used parrot neurons as target for the input proxies, then connected the spike recorder to those neurons. Couldn’t we have connected the spike recorder directly to the proxies?

No, we could not. NEST devices are not generally implemented the same way as neuron models, and are not designed to be connected directly to each other. Normal neurons exist only on one node in a distributed simulation, but devices such as the spike recorder and the MUSIC event handler are usually duplicated aross all nodes.

When you connect a set of neurons to a spike recorder, you normally don’t want all that spike data to travel across the network to a single computing node where it gets saved. It would be very inefficient. Instead, the spike recorder is duplicated on each node and each clone saves the data from its local neurons. In the same way, the MUSIC event handler is duplicated on all nodes, and each clone forwards only the channels that its local targets request.

But if you connect the input proxies directly to the spike recorder, all channels have a local spike recorder target on every computing node. We would get duplicate spike traces, one for each MPI process on the receiving side. To test this, replace line 18 in receive.py with

nest.Connect(music_in, srecorder)

Run this simulation and you will notice that receive-N-0.spikes and receive-N-1.spikes are now identical and about twice as big as before. Collate the input files and compare again:

send.spikes                receive.spikes

2    26.100                2       26.100
1    27.800                2       26.100
2    54.200                1       27.800
1    57.600                1       27.800
2    82.300                2       54.200
1    87.400                2       54.200
2    110.40                1       57.600
1    117.20                1       57.600

Before, each output file would contain the spike events from just one of the two channels. Now both output files contain spikes from all channels, so all our input events are duplicated. Also, as you can see the input and output times are now identical, since a delay is never applied anywhere along the path from the inputs to the outputs.

The lesson is that you don’t connect two NEST devices to each other unless the documentation specifically tells you that you can. Always add a layer of neuron models, such as parrot neurons, in between. This is true for devices in general of course, but this connection pattern, where you want to record the MUSIC input from another simulation, is so common that it’s worth warning about this.