gauss_rate - rate model with Gaussian gain function
gauss_rate is an implementation of a nonlinear rate model with input
function
@f[ input(h) = g * \exp( -( x - \mu )^2 / ( 2 * \sigma^2 ) ) @f].
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.
The following parameters can be set in the status dictionary.
\verbatim embed:rst
================= ======= ==============================================
rate real Rate (unitless)
tau ms Time constant of rate dynamics
mu real Mean input
sigma real Noise parameter
g real Gain parameter
mu real Mean of the Gaussian gain function
sigma real Standard deviation of Gaussian gain function
linear_summation boolean Specifies type of non-linearity (see above)
rectify_output boolean Switch to restrict rate to values >= 0
================= ======= ==============================================
\endverbatim
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.
InstantaneousRateConnectionEvent, DelayedRateConnectionEvent,
DataLoggingRequest
InstantaneousRateConnectionEvent, DelayedRateConnectionEvent
\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
.. [2] Hahne J, Helias M, Kunkel S, Igarashi J, Bolten M, Frommer A, Diesmann Mi
(2015). A unified framework for spiking and gap-junction interactions
in distributed neuronal network simulations. Frontiers in
Neuroinformatics, 9:22. DOI: https://doi.org/10.3389/fninf.2015.00022
\endverbatim
Mario Senden, Jan Hahne, Jannis Schuecker
/var/www/debian/nest/nest-simulator-2.18.0/models/gauss_rate.h