Hi Alexander,
Noise is added simply by creating a random number within specified bounds, according to a user-specified rule, and then adding that number to current activation (how the random number is actually used depends on the neuron / synapse type). The source code is pretty straightforward; you can browse it here:
http://code.google.com/p/simbrain/source/browse/trunk/src/org/simbrain/network/util/RandomSource.javaWe didn't consult any theoretical neuroscience texts when we created this class. I know the topic of noise in neural networks and computational biology is a big topic, but it's not one I'm any expert in (anyone else want to chime in?). I just did a few quick google scholar searches and "neural noise" yielded quite a few hits.
If memory serves, Poisson distributions are often used to model noise in neural networks. We have not implemented this, thought the RandomSource class is pretty flexible, and could easily be extended to incorporate more types of noise.
As usual, suggestions are welcome.
Best,
- Jeff