mip_generator


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