This is A PREVIEW for NEST 3.0 and NOT an OFFICIAL RELEASE! Some functionality may not be available and information may be incomplete!


SLI is the built-in scripting language in NEST. It is a stack-based language loosely modelled on PostScript. It is quite cumbersome to work with, is not extensively documented, and has quite a few corner cases, design issues and unintended behaviours. But it is small, already built into NEST and is much more memory efficient than using Python. If your models are very large and memory is tight, or you are using a system where Python isn’t available, then SLI is the way to go.

We won’t discuss the code extensively as learning SLI is really outside the scope of this tutorial. The code follows the same structure as the other examples, and should be straightforward to follow. But we will give a few pointers for how to connect things with MUSIC.

The SLI version of the sending process file from Part 2 of the MUSIC tutorial, sender.sli, is outlined below. Comments are prefixed with a “%”.

% create 2 neurons, get NodeCollection representing IDs.
/iaf_psc_alpha NUM_NEURONS Create /neuron_out Set

% create output proxy.
/music_event_out_proxy << /port_name (p_out) >> Create /music_out Set

% connect the neurons to the proxy, and give them a separate channel each
    /index Set
    neuron_out [index] Take music_out << /rule /one_to_one >> << /music_channel index 1 sub >> Connect
} forall

1000.0 Simulate

On line 2-3 we create two iaf_psc_alpha in a NodeCollection and save it in neuron_out.

The difference between def on line 2 and Set on line 3 is the order of the arguments: with Set you first give the object, then the name you want to associate with it. With def you give the name first, then the object. Both are used extensively so you need to be aware of them.

On line 6 we create a MUSIC output proxy with port name p_out. Dictionaries are bracketed with “<<” and “>>”, and strings are bracketed with parenthesis.

On lines 9-13 we iterate over the range of all neurons and store the index in index. Then we connect each neuron in the NodeCollection to the output proxy with its own music channel. To get the individual node we use Take. Note that we use Set to assign the index on the stack to a variable. We’d have to rotate the top stack elements if we wanted to use def.

For the receiving SLI file, receiver.sli, we have:

% Create 2 MUSIC nodes, get NodeCollection representing IDs.
/NUM_NODES 2 def
/music_event_in_proxy NUM_NODES Create /music_in Set

% Create 2 parrot neurons.
/parrot_neuron NUM_NODES Create /parrot_in Set

% Create spike recorder
/spike_recorder Create /sr Set
sr << /record_to /ascii
             /label (output)
>> SetStatus

% set port name and channel for all music input proxies.
  /music_node Set
  /channel music_node 1 sub def
  music_node << /port_name (p_in) /music_channel channel >> SetStatus
} forall

% set acceptable latency
(p_in) 2.0 SetAcceptableLatency

% connect music proxies to parrots, one to one
music_in parrot_in << /rule /one_to_one >> << /delay 2.0 >> Connect

parrot_in sr Connect

1000.0 Simulate

SLI, like PyNEST, has a specific function for setting the acceptable latency, as we do on line 23. In line 26 we do a one-to-one connection between the input proxies and the parrot neurons, and set the desired delay.

For the MUSIC configuration file, we now need to use binary=nest to make it run with nest, and pass the correct files as arguments:



from.p_out -> to.p_in [2]

For more information on using SLI, the browser based help we mentioned in the introduction is quite helpful, but the best resource is the set of example models in the NEST source code distribution. That will show you many useful idioms and typical ways to accomplish common tasks.


Please note that MUSIC and the recording backend for Arbor are mutually exclusive and cannot be enabled at the same time.