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 postsynaptic change
of conductance modelled by an exponential function. The exponential function
is normalized such that an event of weight 1.0 results in a peak conductance of
1 nS.
See also 1.
Parameters¶
The following parameters can be set in the status dictionary.
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 |
Exponential decay time constant of excitatory synaptic conductance kernel |
tau_syn_in |
ms |
Exponential decay time constant of inhibitory synaptic conductance kernel |
I_e |
pA |
Constant input current |
Sends¶
SpikeEvent
Receives¶
SpikeEvent, CurrentEvent, DataLoggingRequest
References¶
- 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