diffusion_connection - Synapse type for instantaneous rate connections
between neurons of type siegert_neuron.
diffusion_connection is a connector to create
instantaneous connections between neurons of type siegert_neuron. The
connection type is identical to type rate_connection_instantaneous
for instantaneous rate connections except for the two parameters
drift_factor and diffusion_factor substituting the parameter weight.
These two factor origin from the mean-field reduction of networks of
leaky-integrate-and-fire neurons. In this reduction the input to the
neurons is characterized by its mean and its variance. The mean is
obtained by a sum over presynaptic activities (e.g as in eq.28 in
[1]), where each term of the sum consists of the presynaptic activity
multiplied with the drift_factor. Similarly, the variance is obtained
by a sum over presynaptic activities (e.g as in eq.29 in [1]), where
each term of the sum consists of the presynaptic activity multiplied
with the diffusion_factor. Note that in general the drift and
diffusion factors might differ from the ones given in eq. 28 and 29.,
for example in case of a reduction on the single neuron level or in
case of distributed in-degrees (see discussion in chapter 5.2 of [1])
The values of the parameters delay and weight are ignored for
connections of this type.
DiffusionConnectionEvent
\verbatim embed:rst
.. [1] Hahne J, Dahmen D, Schuecker J, Frommer A,
Bolten M, Helias M, Diesmann, M. (2017).
Integration of continuous-time dynamics in a
spiking neural network simulator.
Frontiers in Neuroinformatics, 11:34.
DOI: https://doi.org/10.3389/fninf.2017.00034
\endverbatim
David Dahmen, Jan Hahne, Jannis Schuecker
/var/www/debian/nest/nest-simulator-2.20.0/models/diffusion_connection.h