diffusion_connection – Synapse type for instantaneous rate connections between neurons of type siegert_neuron
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Description
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``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
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DiffusionConnectionEvent
References
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.. [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
See also
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:doc:`Synapse `, :doc:`Instantaneous Rate `
Examples using this model
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.. listexamples:: diffusion_connection