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