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LifNeuron

Model

A standard leaky-integrate-and-fire neuron model is implemented where the membrane potential V_m of a neuron is given by

$$\tau_m \frac{d V_m}{dt} = -(V_m-V_{resting}) + R_m \cdot (I_{syn}(t)+I_{inject}+I_{noise})$$

where $\tau_m=C_m\cdot R_m$ is the membrane time constant, R_m is the membrane resistance, I_syn(t) is the current supplied by the synapses, I_inject is a non-specific background current and I_noise is a Gaussion random variable with zero mean and a given variance noise.

At time t=0 V_m ist set to V_init . If V_m exceeds the threshold voltage V_thresh it is reset to V_reset and hold there for the length T_refract of the absolute refractory period.

Implementation

The exponential Euler method is used for numerical integration.

Read/writable Fields

Cm (F) :

The membrane capacity C_m

Rm (Ohm) :

The membrane resistance R_m

Vthresh (V) :

If V_m exceeds V_thresh a spike is emmited.

Vresting (V) :

The resting membrane voltage.

Vreset (V) :

The voltage to reset V_m to after a spike.

Vinit (V) :

The initial condition for V_m at time t=0.

Trefract (sec) :

The length of the absolute refractory period.

Inoise (A) :

The standard deviation of the noise to be added each integration time constant.

Iinject (A) :

A constant current to be injected into the LIF neuron.

type :

Type (e.g. inhibitory or excitatory) of the neuron

Readonly Fields

Isyn :

synaptic input current

nIncoming :

Number of incoming synapses

nOutgoing :

Number of outgoing synapses

Vm (V) :

The membrane voltage V_m

(C) 2003, Thomas Natschläger

last modified 07/10/2006