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 See also ++++++++ :doc:`Neuron `, :doc:`Integrate-And-Fire `, :doc:`Conductance-Based `