aeif_psc_delta – Current-based adaptive exponential integrate-and-fire neuron model with delta synapse

Description

aeif_psc_delta is the adaptive exponential integrate and fire neuron according to [1], with postsynaptic currents in the form of delta spikes.

This implementation uses the embedded 5th order Runge-Kutta solver with adaptive stepsize to integrate the differential equation.

The membrane potential is given by the following differential equation:

\[C_m \frac{dV}{dt} = -g_L(V-E_L) + g_L\Delta_T \exp\left(\frac{V-V_{th}}{\Delta_T}\right) + I(t)- w + I_e\]

and

\[\tau_w dw/dt= a(V-E_L) -w\]
\[I(t) = J \sum_k \delta(t - t^k).\]

Here delta is the Dirac delta function and k indexes incoming spikes. This is implemented such that V_m will be incremented/decremented by the value of J after a spike.

Note

The number of receptor ports must be specified at neuron creation (default value is 1) and the receptor index starts from 0 (and not from 1 as in NEST models). The time constants are supplied by an array, tau_syn. Port numbers are automatically assigned in the range 0 to n_receptors-1. During connection, the ports are selected with the synapse property receptor.

Parameters

The following parameters can be set in the status dictionary.

Dynamic state variables

V_m

mV

Membrane potential

w

pA

Spike-adaptation current

Membrane Parameters

V_th

mV

Spike initiation threshold

Delta_T

mV

Slope factor

g_L

nS

Leak conductance

E_L

mV

Leak reversal potential

C_m

pF

Capacity of the membrane

I_e

pA

Constant external input current

V_peak

mV

Spike detection threshold

V_reset

mV

Reset value for V_m after a spike

t_ref

ms

Duration of refractory period

den_delay

ms

Dendritic delay

Spike adaptation parameters

a

ns

Subthreshold adaptation

b

pA

Spike-triggered adaptation

tau_w

ms

Adaptation time constant

Integration parameters

h0_rel

real

Starting step in ODE integration relative to time resolution

h_min_rel

real

Minimum step in ODE integration relative to time resolution

References

See also

Neuron, Adaptive Threshold, Integrate-And-Fire, Current-Based