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:/opt/conda/conda-bld/nest_1512397208563/work/nest-2.14.0/models/iaf_cond_exp.h