iaf_chxk_2008 – Conductance-based leaky integrate-and-fire neuron model supporting precise spike times used in Casti et al. 2008¶
Description¶
iaf_chxk_2008 is an implementation of a spiking neuron using IAF dynamics with conductance-based synapses 1. A spike is emitted when the membrane potential is crossed from below. After a spike, an afterhyperpolarizing (AHP) conductance is activated which repolarizes the neuron over time. Membrane potential is not reset explicitly and the model also has no explicit refractory time.
The AHP conductance and excitatory and inhibitory synaptic input conductances follow alpha-function time courses as in the iaf_cond_alpha model.
Note
In accordance with the original Fortran implementation of the model used in 1, the activation time point for the AHP following a spike is determined by linear interpolation within the time step during which the threshold was crossed.
iaf_chxk_2008 neurons therefore emit spikes with precise spike time information, but they ignore precise spike times when handling synaptic input.
Note
In the original Fortran implementation underlying 1, all previous AHP
activation was discarded when a new spike occurred, leading to reduced AHP
currents in particular during periods of high spiking activity. Set
ahp_bug
to true
to obtain this behavior in the model.
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 |
V_th |
mV |
Spike threshold |
E_ex |
mV |
Excitatory reversal potential |
E_in |
mV |
Inhibitory reversal potential |
g_L |
nS |
Leak conductance |
tau_ex |
ms |
Rise time of the excitatory synaptic alpha function |
tau_in |
ms |
Rise time of the inhibitory synaptic alpha function |
I_e |
pA |
Constant input current |
tau_ahp |
ms |
Afterhyperpolarization (AHP) time constant |
E_ahp |
mV |
AHP potential |
g_ahp |
nS |
AHP conductance |
ahp_bug |
boolean |
Defaults to false. If true, behaves like original model implementation |
References¶
- 1(1,2,3)
Casti A, Hayot F, Xiao Y, Kaplan E (2008) A simple model of retina-LGN transmission. Journal of Computational Neuroscience 24:235-252. DOI: https://doi.org/10.1007/s10827-007-0053-7
Sends¶
SpikeEvent
Receives¶
SpikeEvent, CurrentEvent