**Description:**

siegert_neuron is an implementation of a rate model with the

non-linearity given by the gain function of the

leaky-integrate-and-fire neuron with delta or exponentially decaying

synapses [2] and [3, their eq. 25]. The model can be used for a

mean-field analysis of spiking networks.

The model supports connections to other rate models with zero

delay, and uses the secondary_event concept introduced with the

gap-junction framework.

**Parameters:**

The following parameters can be set in the status dictionary.

rate double - Rate (1/s)

tau double - Time constant in ms.

mean double - Additional constant input

The following parameters can be set in the status directory and are

used in the evaluation of the gain function. Parameters as in

iaf_psc_exp/delta.

tau_m double - Membrane time constant in ms.

tau_syn double - Time constant of postsynaptic currents in ms.

t_ref double - Duration of refractory period in ms.

theta double - Threshold relative to resting potential in mV.

V_reset double - Reset relative to resting membrane potential in

mV.

Notes:

**Require:**

HAVE_GSL

**Receives:**

DiffusionConnectionEvent, DataLoggingRequest

**Sends:**

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

[2] Fourcaud, N and Brunel, N. (2002). Dynamics of the firing

probability of noisy integrate-and-fire neurons, Neural computation,

14:9, pp 2057--2110

[3] Schuecker, J., Diesmann, M. and Helias, M. (2015).

Modulated escape from a metastable state driven by colored noise.

Physical Review E 92:052119

[4] Hahne, J., Helias, M., Kunkel, S., Igarashi, J.,

Bolten, M., Frommer, A. and Diesmann, M. (2015).

A unified framework for spiking and gap-junction interactions

in distributed neuronal network simulations.

Front. Neuroinform. 9:22. doi: 10.3389/fninf.2015.00022

**Author:**

Jannis Schuecker, David Dahmen, Jan Hahne

**SeeAlso:**

**Source:**

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