iaf_cond_exp - Simple conductance based leaky integrate-and-fire neuron
model.
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.
The following parameters can be set in the status dictionary.
\verbatim embed:rst
=========== ====== =======================================================
V_m mV Membrane potential
E_L mV Leak reversal potential
C_m pF Capacity of the membrane
t_ref ms Duration of refractory period
V_th mV Spike threshold
V_reset mV Reset potential of the membrane
E_ex mV Excitatory reversal potential
E_in mV Inhibitory reversal potential
g_L nS Leak conductance
tau_syn_ex ms Rise time of the excitatory synaptic alpha function
tau_syn_in ms Rise time of the inhibitory synaptic alpha function
I_e pA Constant input current
=========== ====== =======================================================
\endverbatim
SpikeEvent, CurrentEvent, DataLoggingRequest
SpikeEvent
\verbatim embed:rst
.. [1] Meffin H, Burkitt AN, Grayden DB (2004). An analytical
model for the large, fluctuating synaptic conductance state typical of
neocortical neurons in vivo. Journal of Computational Neuroscience,
16:159-175.
DOI: https://doi.org/10.1023/B:JCNS.0000014108.03012.81
\endverbatim
Sven Schrader
/var/www/debian/nest/nest-simulator-2.20.0/models/iaf_cond_exp.h