aeif_cond_beta_multisynapse – Conductance based adaptive exponential integrate-and-fire neuron model¶
Description¶
aeif_cond_beta_multisynapse
is a conductance-based adaptive exponential
integrate-and-fire neuron model, according to Brette and Gerstner (2005) with
multiple synaptic rise time and decay time constants, and synaptic conductance
modeled by a beta function.
It allows an arbitrary number of synaptic rise time and decay time constants. Synaptic conductance is modeled by a beta function, as described by A. Roth and M.C.W. van Rossum in Computational Modeling Methods for Neuroscientists, MIT Press 2013, Chapter 6.
The time constants are supplied by two arrays, tau_rise
and tau_decay
for
the synaptic rise time and decay time, respectively. The synaptic
reversal potentials are supplied by the array E_rev
. The port numbers
are automatically assigned in the range from 1 to n_receptors.
During connection, the ports are selected with the property receptor_type
.
When connecting to conductance-based multisynapse models, all synaptic weights must be non-negative.
The membrane potential is given by the following differential equation:
where:
the synapse i is excitatory or inhibitory depending on the value of \(E_{rev,i}\) and the differential equation for the spike-adaptation current w is:
When the neuron fires a spike, the adaptation current w <- w + b.
For implementation details see the aeif_models_implementation notebook.
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 |
||
C_m |
pF |
Capacity of the membrane |
t_ref |
ms |
Duration of refractory period |
V_reset |
mV |
Reset value for V_m after a spike |
E_L |
mV |
Leak reversal potential |
g_L |
nS |
Leak conductance |
I_e |
pA |
Constant external input current |
Delta_T |
mV |
Slope factor |
V_th |
mV |
Spike initiation threshold |
V_peak |
mV |
Spike detection threshold |
Spike adaptation parameters |
||
a |
ns |
Subthreshold adaptation |
b |
pA |
Spike-triggered adaptation |
tau_w |
ms |
Adaptation time constant |
Synaptic parameters |
||
E_rev |
list of mV |
Reversal potential |
tau_syn |
list of ms |
Time constant of synaptic conductance |
Integration parameters |
||
gsl_error_tol |
real |
This parameter controls the admissible error of the GSL integrator. Reduce it if NEST complains about numerical instabilities. |
Sends¶
SpikeEvent
Receives¶
SpikeEvent, CurrentEvent, DataLoggingRequest
See also¶
Neuron, Adaptive Threshold, Integrate-And-Fire, Conductance-Based