Command: izhikevich

Name:
izhikevich - Izhikevich neuron model

Description:
Implementation of the simple spiking neuron model introduced by Izhikevich [1]. The dynamics are given by: dv/dt = 0.04*v^2 + 5*v + 140 - u + I du/dt = a*(b*v - u) if v >= V_th: v is set to c u is incremented by d v jumps on each spike arrival by the weight of the spike. As published in [1], the numerics differs from the standard forward Euler technique in two ways: 1) the new value of u is calulated based on the new value of v, rather than the previous value 2) the variable v is updated using a time step half the size of that used to update variable u. This model offers both forms of integration, they can be selected using the boolean parameter consistent_integration. To reproduce some results published on the basis of this model, it is necessary to use the published form of the dynamics. In this case, consistent_integration must be set to false. For all other purposes, it is recommended to use the standard technique for forward Euler integration. In this case, consistent_integration must be set to true (default).

Parameters:
The following parameters can be set in the status dictionary. V_m double - Membrane potential in mV U_m double - Membrane potential recovery variable V_th double - Spike threshold in mV. I_e double - Constant input current in pA. (R=1) V_min double - Absolute lower value for the membrane potential. a double - describes time scale of recovery variable b double - sensitivity of recovery variable c double - after-spike reset value of V_m d double - after-spike reset value of U_m consistent_integration bool - use standard integration technique

References:
[1] Izhikevich, Simple Model of Spiking Neurons, IEEE Transactions on Neural Networks (2003) 14:1569-1572

Sends:
SpikeEvent

Receives:
SpikeEvent, CurrentEvent, DataLoggingRequest

FirstVersion:
2009

Author:
Hanuschkin, Morrison, Kunkel
SeeAlso: iaf_psc_delta mat2_psc_exp

Source:
/home/abuild/rpmbuild/BUILD/nest-2.4.1/models/izhikevich.h

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Name:	izhikevich - Izhikevich neuron model
Description:	Implementation of the simple spiking neuron model introduced by Izhikevich [1]. The dynamics are given by: dv/dt = 0.04v^2 + 5v + 140 - u + I du/dt = a(bv - u) if v >= V_th: v is set to c u is incremented by d v jumps on each spike arrival by the weight of the spike. As published in [1], the numerics differs from the standard forward Euler technique in two ways: 1) the new value of u is calulated based on the new value of v, rather than the previous value 2) the variable v is updated using a time step half the size of that used to update variable u. This model offers both forms of integration, they can be selected using the boolean parameter consistent_integration. To reproduce some results published on the basis of this model, it is necessary to use the published form of the dynamics. In this case, consistent_integration must be set to false. For all other purposes, it is recommended to use the standard technique for forward Euler integration. In this case, consistent_integration must be set to true (default).
Parameters:	The following parameters can be set in the status dictionary. V_m double - Membrane potential in mV U_m double - Membrane potential recovery variable V_th double - Spike threshold in mV. I_e double - Constant input current in pA. (R=1) V_min double - Absolute lower value for the membrane potential. a double - describes time scale of recovery variable b double - sensitivity of recovery variable c double - after-spike reset value of V_m d double - after-spike reset value of U_m consistent_integration bool - use standard integration technique
References:	[1] Izhikevich, Simple Model of Spiking Neurons, IEEE Transactions on Neural Networks (2003) 14:1569-1572
Sends:	SpikeEvent
Receives:	SpikeEvent, CurrentEvent, DataLoggingRequest
FirstVersion:	2009
Author:	Hanuschkin, Morrison, Kunkel
SeeAlso:	`iaf_psc_delta` `mat2_psc_exp`
Source:	/home/abuild/rpmbuild/BUILD/nest-2.4.1/models/izhikevich.h