# iaf_cond_alpha – Simple conductance based leaky integrate-and-fire neuron model¶

## Description¶

iaf_cond_alpha 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 alpha function. The alpha function is normalized such that an event of weight 1.0 results in a peak current of 1 nS at $$t = \tau_{syn}$$.

## 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 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

## Sends¶

SpikeEvent

SpikeEvent, CurrentEvent, DataLoggingRequest

Remarks:

@note Per 2009-04-17, this class has been revised to our newest

insights into class design. Please use THIS CLASS as a reference when designing your own models with nonlinear dynamics. One weakness of this class is that it distinguishes between inputs to the two synapses by the sign of the synaptic weight. It would be better to use receptor_types, cf iaf_cond_alpha_mc.

## 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

2

Bernander O, Douglas RJ, Martin KAC, Koch C (1991). Synaptic background activity influences spatiotemporal integration in single pyramidal cells. Proceedings of the National Academy of Science USA, 88(24):11569-11573. DOI: https://doi.org/10.1073/pnas.88.24.11569

3

Kuhn A, Rotter S (2004) Neuronal integration of synaptic input in the fluctuation- driven regime. Journal of Neuroscience, 24(10):2345-2356 DOI: https://doi.org/10.1523/JNEUROSCI.3349-03.2004