Warning

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

mip_generator – create spike trains as described by the MIP model

Description

The mip_generator generates correlated spike trains using an Multiple Interaction Process (MIP) as described in 1. Underlying principle is a Poisson mother process with rate r, the spikes of which are copied into the child processes with a certain probability p. Every node the mip_generator is connected to receives a distinct child process as input, whose rate is p*r. The value of the pairwise correlation coefficient of two child processes created by a MIP process equals p.

Remarks:

The MIP generator may emit more than one spike through a child process during a single time step, especially at high rates. If this happens, the generator does not actually send out n spikes. Instead, it emits a single spike with n-fold synaptic weight for the sake of efficiency. Furthermore, note that as with the Poisson generator, different threads have their own copy of a MIP generator. By using the same mother_seed it is ensured that the mother process is identical for each of the generators.

IMPORTANT: The mother_seed of mpi_generator must be different from any

seeds used for the global or thread-specific RNGs set in the kernel.

TODO: Better handling of private random number generator, see #143.

Most important: If RNG is changed in prototype by SetDefaults, then this is

Parameters

The following parameters appear in the element’s status dictionary:

rate

spikes/s

Mean firing rate of the mother process

p_copy

real

Copy probability

mother_rng

rng

Random number generator of mother process

mother_seed

integer

Seed of RNG of mother process

Sends

SpikeEvent

References

1

Kuhn A, Aertsen A, Rotter S (2003). Higher-order statistics of input ensembles and the response of simple model neurons. Neural Computation 15:67-101. DOI: https://doi.org/10.1162/089976603321043702