iaf_cond_exp_sfa_rr - Simple conductance based leaky integrate-and-fire  
neuron model.
iaf_cond_exp_sfa_rr is an iaf_cond_exp_sfa_rr i.e. an implementation of a
spiking neuron using IAF dynamics with conductance-based synapses,
with additional spike-frequency adaptation and relative refractory
mechanisms as described in Dayan+Abbott, 2001, page 166.

As for the iaf_cond_exp_sfa_rr, 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 current of 1 nS.

Outgoing spike events induce a change of the adaptation and relative
refractory conductances by q_sfa and q_rr, respectively. Otherwise
these conductances decay exponentially with time constants tau_sfa
and tau_rr, respectively.

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.
q_sfa double - Outgoing spike activated quantal spike-frequency adaptation
conductance increase in nS.
q_rr double - Outgoing spike activated quantal relative refractory
conductance increase in nS.
tau_sfa double - Time constant of spike-frequency adaptation in ms.
tau_rr double - Time constant of the relative refractory mechanism in ms.
E_sfa double - spike-frequency adaptation conductance reversal potential in
E_rr double - relative refractory mechanism conductance reversal potential
in mV.
I_e double - an external stimulus current in pA.

SpikeEvent, CurrentEvent, DataLoggingRequest  



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.

Dayan, P. and Abbott, L. F. (2001). Theoretical Neuroscience, MIT Press (p166)

Sven Schrader, Eilif Muller  

SeeAlso: Source: