**Name:**

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.

**Parameters:**

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

rate double - Mean firing rate of the mother process in Hz

p_copy double - Copy probability

mother_rng rng - Random number generator of mother process

mother_seed long - Seed of RNG of mother process

**Sends:**

SpikeEvent

**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.

**References:**

[1] Alexandre Kuhn, Ad Aertsen, Stefan Rotter

Higher-Order Statistics of Input Ensembles and the Response of Simple

Model Neurons

Neural Computation 15, 67-101 (2003)

**Author:**

May 2006, Helias

**SeeAlso:**

**Source:**

/home/graber/work-nest/nest-git/nest-simulator/models/mip_generator.h