iaf_psc_alpha_neuron #################### iaf_psc_alpha - Leaky integrate-and-fire neuron model Description +++++++++++ iaf_psc_alpha is an implementation of a leaky integrate-and-fire model with alpha-function kernel synaptic currents. Thus, synaptic currents and the resulting post-synaptic potentials have a finite rise time. The threshold crossing is followed by an absolute refractory period during which the membrane potential is clamped to the resting potential. The general framework for the consistent formulation of systems with neuron like dynamics interacting by point events is described in [1]_. A flow chart can be found in [2]_. Critical tests for the formulation of the neuron model are the comparisons of simulation results for different computation step sizes. The iaf_psc_alpha is the standard model used to check the consistency of the nest simulation kernel because it is at the same time complex enough to exhibit non-trivial dynamics and simple enough compute relevant measures analytically. .. note:: If tau_m is very close to tau_syn_exc or tau_syn_inh, numerical problems may arise due to singularities in the propagator matrics. If this is the case, replace equal-valued parameters by a single parameter. For details, please see ``IAF_neurons_singularity.ipynb`` in the NEST source code (``docs/model_details``). References ++++++++++ .. [1] Rotter S, Diesmann M (1999). Exact simulation of time-invariant linear systems with applications to neuronal modeling. Biologial Cybernetics 81:381-402. DOI: https://doi.org/10.1007/s004220050570 .. [2] Diesmann M, Gewaltig M-O, Rotter S, & Aertsen A (2001). State space analysis of synchronous spiking in cortical neural networks. Neurocomputing 38-40:565-571. DOI: https://doi.org/10.1016/S0925-2312(01)00409-X .. [3] Morrison A, Straube S, Plesser H E, Diesmann M (2006). Exact subthreshold integration with continuous spike times in discrete time neural network simulations. Neural Computation, in press DOI: https://doi.org/10.1162/neco.2007.19.1.47 See also ++++++++ iaf_psc_delta, iaf_psc_exp, iaf_cond_alpha Copyright statement +++++++++++++++++++ This file is part of NEST. Copyright (C) 2004 The NEST Initiative NEST is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version. NEST is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with NEST. If not, see . Parameters ++++++++++ .. csv-table:: :header: "Name", "Physical unit", "Default value", "Description" :widths: auto "C_m", "pF", "250pF", "Capacitance of the membrane" "tau_m", "ms", "10ms", "Membrane time constant" "tau_syn_inh", "ms", "2ms", "Time constant of synaptic current" "tau_syn_exc", "ms", "2ms", "Time constant of synaptic current" "refr_T", "ms", "2ms", "Duration of refractory period" "E_L", "mV", "-70mV", "Resting potential" "V_reset", "mV", "-70mV", "Reset potential of the membrane" "V_th", "mV", "-55mV", "Spike threshold potential" "I_e", "pA", "0pA", "constant external input current" State variables +++++++++++++++ .. csv-table:: :header: "Name", "Physical unit", "Default value", "Description" :widths: auto "V_m", "mV", "E_L", "" "refr_t", "ms", "0ms", "Refractory period timer" Equations +++++++++ .. math:: \frac{ dV_{m} } { dt }= \frac{ -(V_{m} - E_{L}) } { \tau_{m} } + \frac{ I } { C_{m} } .. math:: \frac{ drefr_{t} } { dt }= \frac{ -1000.0 \cdot \mathrm{ms} } { \mathrm{s} } Source code +++++++++++ The model source code can be found in the NESTML models repository here: `iaf_psc_alpha_neuron `_. .. include:: iaf_psc_alpha_neuron_characterisation.rst .. footer:: Generated at 2026-02-04 14:40:55.096368