**Name:**

sigmoid_rate - rate model with sigmoidal gain function

**Description:**

sigmoid_rate is an implementation of a nonlinear rate model with input

function input(h) = g / ( 1. + exp( -beta * ( h - theta ) ) ).

Input transformation can either be applied to individual inputs

or to the sum of all inputs.

The model supports connections to other rate models with either zero or

non-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 (unitless)

tau double - Time constant of rate dynamics in ms.

mean double - Mean of Gaussian white noise.

std double - Standard deviation of Gaussian white noise.

g double - Gain parameter.

beta double - Slope parameter.

theta double - Threshold.

linear_summation bool - Specifies type of non-linearity (see above).

rectify_output bool - Switch to restrict rate to values >= 0.

Note:

The boolean parameter linear_summation determines whether the

input from different presynaptic neurons is first summed linearly and

then transformed by a nonlinearity (true), or if the input from

individual presynaptic neurons is first nonlinearly transformed and

then summed up (false). Default is true.

**Receives:**

InstantaneousRateConnectionEvent, DelayedRateConnectionEvent,

DataLoggingRequest

**Sends:**

InstantaneousRateConnectionEvent, DelayedRateConnectionEvent

**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] 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:**

Mario Senden, Jan Hahne, Jannis Schuecker

**SeeAlso:**

**Source:**

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