**Name:**

iaf_cond_exp - Simple conductance based leaky integrate-and-fire neuron

model.

**Description:**

iaf_cond_exp is an implementation of a spiking neuron using IAF dynamics with

conductance-based synapses. Incoming spike events induce a post-synaptic change

of conductance modelled by an exponential function. The exponential function

is normalised such that an event of weight 1.0 results in a peak conductance of

1 nS.

**Parameters:**

The following parameters can be set in the status dictionary.

V_m double - Membrane potential in mV

E_L double - Leak reversal potential in mV.

C_m double - Capacity of the membrane in pF

t_ref double - Duration of refractory period in ms.

V_th double - Spike threshold in mV.

V_reset double - Reset potential of the membrane in mV.

E_ex double - Excitatory reversal potential in mV.

E_in double - Inhibitory reversal potential in mV.

g_L double - Leak conductance in nS;

tau_syn_ex double - Time constant of the excitatory synaptic exponential

function in ms.

tau_syn_in double - Time constant of the inhibitory synaptic exponential

function in ms.

I_e double - Constant external input current in pA.

**Require:**

HAVE_GSL

**Receives:**

SpikeEvent, CurrentEvent, DataLoggingRequest

**Sends:**

SpikeEvent

**References:**

Meffin, H., Burkitt, A. N., & Grayden, D. B. (2004). An analytical

model for the large, fluctuating synaptic conductance state typical of

neocortical neurons in vivo. J. Comput. Neurosci., 16, 159-175.

**Author:**

Sven Schrader

**SeeAlso:**

**Source:**

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