**Name:**

diffusion_connection - Synapse type for instantaneous rate connections

between neurons of type siegert_neuron.

**Description:**

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.

**Transmits:**

DiffusionConnectionEvent

**References:**

[1] Hahne, J., Dahmen, D., Schuecker, J., Frommer, A.,

Bolten, M., Helias, M. and Diesmann, M. (2017).

Integration of Continuous-Time Dynamics in a

Spiking Neural Network Simulator.

Front. Neuroinform. 11:34. doi: 10.3389/fninf.2017.00034

**Author:**

David Dahmen, Jan Hahne, Jannis Schuecker

**SeeAlso:**

**Source:**

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