aeif_cond_alpha_multisynapse – Conductance based adaptive exponential integrate-and-fire neuron model¶
Description¶
aeif_cond_alpha_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 an alpha function.
It allows an arbitrary number of synaptic time constants. Synaptic conductance is modeled by an alpha 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 an array, tau_syn
, and the pertaining
synaptic reversal potentials are supplied by the array E_rev
. 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, Integrate-And-Fire, Adaptive Threshold, Conductance-Based