lin_rate – Linear rate model

Description

lin_rate is an implementation of a rate model with linear input function \(input(h) = g * h\). It either models a rate neuron with input noise (see rate_neuron_ipn), a rate neuron with output noise (see rate_neuron_opn) or a rate transformer (see rate_transformer_node).

Linear rate neurons support multiplicative coupling which can be switched on and off via the boolean parameter mult_coupling (default=false). In case multiplicative coupling is active, the excitatory input of the model is multiplied with the function \(mult\_coupling\_ex(rate) = g_{ex} * ( \theta_{ex} - rate )\) and the inhibitory input is multiplied with the function \(mult\_coupling\_in(rate) = g_{in} * ( \theta_{in} + rate )\).

The model supports connections to other rate models with either zero or non-zero delay, and it uses the secondary_event concept introduced with the gap-junction framework.

Linear rate neurons can be created by typing nest.Create(‘lin_rate_ipn’) or nest.Create(‘lin_rate_opn’) for input noise or output noise, respectively. Linear rate transformers can be created by typing nest.Create(‘rate_transformer_lin’).

Parameters

The following parameters can be set in the status dictionary. Note that some of the parameters only apply to rate neurons and not to rate transformers. =============== ======= ==================================================

rate real Rate (unitless) tau ms Time constant of rate dynamics lambda real Passive decay rate mu real Mean input sigma real Noise parameter g real Gain parameter mult_coupling boolean Switch to enable/disable multiplicative coupling g_ex real Linear factor in multiplicative coupling g_in real Linear factor in multiplicative coupling theta_ex real Shift in multiplicative coupling theta_in real Shift in multiplicative coupling rectify_rate real Rectifying rate rectify_output boolean Switch to restrict rate to values >= rectify_rate