iaf_cond_beta_neuron
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iaf_cond_beta - Simple conductance based leaky integrate-and-fire neuron model
Description
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iaf_cond_beta is an implementation of a spiking neuron using IAF dynamics with
conductance-based synapses. Incoming spike events induce a post-synaptic change
of conductance modelled by a beta function. The beta function
is normalised such that an event of weight 1.0 results in a peak current of
1 nS at :math:`t = \tau_\text{rise\_[ex|in]}`.
References
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.. [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
.. [2] Bernander O, Douglas RJ, Martin KAC, Koch C (1991). Synaptic background
activity influences spatiotemporal integration in single pyramidal
cells. Proceedings of the National Academy of Science USA,
88(24):11569-11573.
DOI: https://doi.org/10.1073/pnas.88.24.11569
.. [3] Kuhn A, Rotter S (2004) Neuronal integration of synaptic input in
the fluctuation- driven regime. Journal of Neuroscience,
24(10):2345-2356
DOI: https://doi.org/10.1523/JNEUROSCI.3349-03.2004
.. [4] 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
.. [5] Roth A and van Rossum M (2010). Chapter 6: Modeling synapses.
in De Schutter, Computational Modeling Methods for Neuroscientists,
MIT Press.
See also
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iaf_cond_exp, iaf_cond_alpha
Copyright statement
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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
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.. csv-table::
:header: "Name", "Physical unit", "Default value", "Description"
:widths: auto
"C_m", "pF", "250pF", "Capacitance of the membrane"
"g_L", "nS", "16.6667nS", "Leak conductance"
"E_L", "mV", "-70mV", "Leak reversal potential (a.k.a. resting potential)"
"refr_T", "ms", "2ms", "Duration of refractory period"
"V_th", "mV", "-55mV", "Threshold potential"
"V_reset", "mV", "-60mV", "Reset potential"
"E_ex", "mV", "0mV", "Excitatory reversal potential"
"E_in", "mV", "-85mV", "Inhibitory reversal potential"
"tau_syn_rise_I", "ms", "0.2ms", "Synaptic time constant excitatory synapse"
"tau_syn_decay_I", "ms", "2ms", "Synaptic time constant for inhibitory synapse"
"tau_syn_rise_E", "ms", "0.2ms", "Synaptic time constant excitatory synapse"
"tau_syn_decay_E", "ms", "2ms", "Synaptic time constant for inhibitory synapse"
"F_E", "nS", "0nS", "Constant external input conductance (excitatory)"
"F_I", "nS", "0nS", "Constant external input conductance (inhibitory)"
"I_e", "pA", "0pA", "constant external input current"
State variables
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.. csv-table::
:header: "Name", "Physical unit", "Default value", "Description"
:widths: auto
"V_m", "mV", "E_L", "Membrane potential"
"refr_t", "ms", "0ms", "Refractory period timer"
"g_in", "real", "0", "inputs from the inhibitory conductance"
"g_in$", "real", "g_I_const * (1 / tau_syn_rise_I - 1 / tau_syn_decay_I)", ""
"g_ex", "real", "0", "inputs from the excitatory conductance"
"g_ex$", "real", "g_E_const * (1 / tau_syn_rise_E - 1 / tau_syn_decay_E)", ""
Equations
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.. math::
\frac{ dV_{m} } { dt }= \frac 1 { C_{m} } \left( { (-I_{leak} - I_{syn,exc} - I_{syn,inh} + I_{e} + I_{stim}) } \right)
.. 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_cond_beta_neuron `_.
.. include:: iaf_cond_beta_neuron_characterisation.rst
.. footer::
Generated at 2026-02-04 14:40:55.550005