# Model Directory¶

## Clopath Plasticity¶

## Hill-Tononi Plasticity¶

## Hodgkin-Huxley¶

## MUSIC¶

music_cont_in_proxy – A device which receives continuous data from MUSIC

music_cont_out_proxy – A device which sends continuous data from NEST to MUSIC

music_event_in_proxy – A device which receives spikes from MUSIC

music_event_out_proxy – Device to forward spikes to remote applications using MUSIC

music_message_in_proxy – A device which receives message strings from MUSIC

music_rate_in_proxy – A device which receives rate data from MUSIC

music_rate_out_proxy – Device to forward rates to remote applications using MUSIC

## Adaptive Threshold¶

aeif_cond_alpha – Conductance based exponential integrate-and-fire neuron model

aeif_cond_beta_multisynapse – Conductance based adaptive exponential integrate-and-fire neuron model

aeif_cond_exp – Conductance based exponential integrate-and-fire neuron model

aeif_psc_alpha – Current-based exponential integrate-and-fire neuron model

aeif_psc_delta_clopath – Adaptive exponential integrate-and-fire neuron

aeif_psc_exp – Current-based exponential integrate-and-fire neuron model

## Binary¶

## Compartmental Model¶

## Conductance-Based¶

aeif_cond_alpha – Conductance based exponential integrate-and-fire neuron model

aeif_cond_beta_multisynapse – Conductance based adaptive exponential integrate-and-fire neuron model

aeif_cond_exp – Conductance based exponential integrate-and-fire neuron model

gif_cond_exp – Conductance-based generalized integrate-and-fire neuron model

glif_cond – Conductance-based generalized leaky integrate and fire (GLIF) model

hh_cond_exp_traub – Hodgkin-Huxley model for Brette et al (2007) review

iaf_cond_alpha – Simple conductance based leaky integrate-and-fire neuron model

iaf_cond_alpha_mc – Multi-compartment conductance-based leaky integrate-and-fire neuron model

iaf_cond_beta – Simple conductance based leaky integrate-and-fire neuron model

iaf_cond_exp – Simple conductance based leaky integrate-and-fire neuron model

pp_cond_exp_mc_urbanczik – Two-compartment point process neuron with conductance-based synapses

## Connection With Delay¶

## Continuous Delay¶

## Current-Based¶

aeif_psc_alpha – Current-based exponential integrate-and-fire neuron model

aeif_psc_delta_clopath – Adaptive exponential integrate-and-fire neuron

aeif_psc_exp – Current-based exponential integrate-and-fire neuron model

gif_psc_exp – Current-based generalized integrate-and-fire neuron model

glif_psc – Current-based generalized leaky integrate-and-fire models

hh_psc_alpha_clopath – Hodgkin-Huxley neuron model with support for Clopath plasticity

hh_psc_alpha_gap – Hodgkin-Huxley neuron model with gap-junction support

iaf_psc_alpha_multisynapse – Leaky integrate-and-fire neuron model with multiple ports

iaf_psc_exp – Leaky integrate-and-fire neuron model with exponential PSCs

pp_pop_psc_delta – Population of point process neurons with leaky integration of delta-shaped PSCs

pp_psc_delta – Point process neuron with leaky integration of delta-shaped PSCs

## Detector¶

correlation_detector – Device for evaluating cross correlation between two spike sources

correlomatrix_detector – Device for measuring the covariance matrix from several inputs

correlospinmatrix_detector – Device for measuring the covariance matrix from several inputs

spin_detector – Device for detecting binary states in neurons

## Device¶

correlation_detector – Device for evaluating cross correlation between two spike sources

correlomatrix_detector – Device for measuring the covariance matrix from several inputs

correlospinmatrix_detector – Device for measuring the covariance matrix from several inputs

gamma_sup_generator – Simulate the superimposed spike train of a population of gamma processes

inhomogeneous_poisson_generator – Provides Poisson spike trains at a piecewise constant rate

mip_generator – Create spike trains as described by the MIP model

music_cont_in_proxy – A device which receives continuous data from MUSIC

music_cont_out_proxy – A device which sends continuous data from NEST to MUSIC

music_event_in_proxy – A device which receives spikes from MUSIC

music_event_out_proxy – Device to forward spikes to remote applications using MUSIC

music_message_in_proxy – A device which receives message strings from MUSIC

music_rate_in_proxy – A device which receives rate data from MUSIC

music_rate_out_proxy – Device to forward rates to remote applications using MUSIC

poisson_generator – Generate spikes with Poisson process statistics

pulsepacket_generator – Generate sequence of Gaussian pulse packets

sinusoidal_gamma_generator – Generates sinusoidally modulated gamma spike trains

sinusoidal_poisson_generator – Generate sinusoidally modulated Poisson spike trains

spike_dilutor – Repeat incoming spikes with a certain probability

spike_generator – Generate spikes from an array with spike-times

spin_detector – Device for detecting binary states in neurons

step_current_generator – Provide a piecewise constant DC input current

step_rate_generator – Provide a piecewise constant input rate

volume_transmitter – Support node for neuromodulated synaptic plasticity

## Gap Junction¶

## Generator¶

gamma_sup_generator – Simulate the superimposed spike train of a population of gamma processes

inhomogeneous_poisson_generator – Provides Poisson spike trains at a piecewise constant rate

mip_generator – Create spike trains as described by the MIP model

poisson_generator – Generate spikes with Poisson process statistics

pulsepacket_generator – Generate sequence of Gaussian pulse packets

sinusoidal_gamma_generator – Generates sinusoidally modulated gamma spike trains

sinusoidal_poisson_generator – Generate sinusoidally modulated Poisson spike trains

spike_dilutor – Repeat incoming spikes with a certain probability

spike_generator – Generate spikes from an array with spike-times

step_current_generator – Provide a piecewise constant DC input current

step_rate_generator – Provide a piecewise constant input rate

volume_transmitter – Support node for neuromodulated synaptic plasticity

## Instantaneous Rate¶

## Integrate-And-Fire¶

aeif_cond_alpha – Conductance based exponential integrate-and-fire neuron model

aeif_cond_beta_multisynapse – Conductance based adaptive exponential integrate-and-fire neuron model

aeif_cond_exp – Conductance based exponential integrate-and-fire neuron model

aeif_psc_alpha – Current-based exponential integrate-and-fire neuron model

aeif_psc_delta_clopath – Adaptive exponential integrate-and-fire neuron

aeif_psc_exp – Current-based exponential integrate-and-fire neuron model

gif_cond_exp – Conductance-based generalized integrate-and-fire neuron model

gif_psc_exp – Current-based generalized integrate-and-fire neuron model

glif_cond – Conductance-based generalized leaky integrate and fire (GLIF) model

glif_psc – Current-based generalized leaky integrate-and-fire models

iaf_chs_2007 – Spike-response model used in Carandini et al. 2007

iaf_cond_alpha – Simple conductance based leaky integrate-and-fire neuron model

iaf_cond_alpha_mc – Multi-compartment conductance-based leaky integrate-and-fire neuron model

iaf_cond_beta – Simple conductance based leaky integrate-and-fire neuron model

iaf_cond_exp – Simple conductance based leaky integrate-and-fire neuron model

iaf_psc_alpha_multisynapse – Leaky integrate-and-fire neuron model with multiple ports

iaf_psc_exp – Leaky integrate-and-fire neuron model with exponential PSCs

iaf_psc_exp_multisynapse – Leaky integrate-and-fire neuron model with multiple ports

## Neuron¶

aeif_cond_alpha – Conductance based exponential integrate-and-fire neuron model

aeif_cond_beta_multisynapse – Conductance based adaptive exponential integrate-and-fire neuron model

aeif_cond_exp – Conductance based exponential integrate-and-fire neuron model

aeif_psc_alpha – Current-based exponential integrate-and-fire neuron model

aeif_psc_delta_clopath – Adaptive exponential integrate-and-fire neuron

aeif_psc_exp – Current-based exponential integrate-and-fire neuron model

erfc_neuron – Binary stochastic neuron with complementary error function as activation function

gif_cond_exp – Conductance-based generalized integrate-and-fire neuron model

gif_psc_exp – Current-based generalized integrate-and-fire neuron model

ginzburg_neuron – Binary stochastic neuron with sigmoidal activation function

hh_cond_exp_traub – Hodgkin-Huxley model for Brette et al (2007) review

hh_psc_alpha_clopath – Hodgkin-Huxley neuron model with support for Clopath plasticity

hh_psc_alpha_gap – Hodgkin-Huxley neuron model with gap-junction support

iaf_chs_2007 – Spike-response model used in Carandini et al. 2007

iaf_cond_alpha – Simple conductance based leaky integrate-and-fire neuron model

iaf_cond_alpha_mc – Multi-compartment conductance-based leaky integrate-and-fire neuron model

iaf_cond_beta – Simple conductance based leaky integrate-and-fire neuron model

iaf_cond_exp – Simple conductance based leaky integrate-and-fire neuron model

iaf_psc_alpha_multisynapse – Leaky integrate-and-fire neuron model with multiple ports

iaf_psc_exp – Leaky integrate-and-fire neuron model with exponential PSCs

iaf_psc_exp_multisynapse – Leaky integrate-and-fire neuron model with multiple ports

mcculloch_pitts_neuron – Binary deterministic neuron with Heaviside activation function

parrot_neuron_ps – Neuron that repeats incoming spikes - precise spike timing version

pp_cond_exp_mc_urbanczik – Two-compartment point process neuron with conductance-based synapses

pp_pop_psc_delta – Population of point process neurons with leaky integration of delta-shaped PSCs

pp_psc_delta – Point process neuron with leaky integration of delta-shaped PSCs

rate_neuron_ipn – Base class for rate model with input noise

rate_neuron_opn – Base class for rate model with output noise

siegert_neuron – model for mean-field analysis of spiking networks

sigmoid_rate – Rate neuron model with sigmoidal gain function

sigmoid_rate_gg_1998 – rate model with sigmoidal gain function

tanh_rate – rate model with hyperbolic tangent non-linearity

threshold_lin_rate – Rate model with threshold-linear gain function

## Parrot¶

## Point Process¶

## Precise¶

## Rate¶

music_rate_in_proxy – A device which receives rate data from MUSIC

music_rate_out_proxy – Device to forward rates to remote applications using MUSIC

rate_connection_delayed – Synapse type for rate connections with delay

rate_connection_instantaneous – Synapse type for instantaneous rate connections

rate_neuron_ipn – Base class for rate model with input noise

rate_neuron_opn – Base class for rate model with output noise

siegert_neuron – model for mean-field analysis of spiking networks

sigmoid_rate – Rate neuron model with sigmoidal gain function

sigmoid_rate_gg_1998 – rate model with sigmoidal gain function

step_rate_generator – Provide a piecewise constant input rate

tanh_rate – rate model with hyperbolic tangent non-linearity

threshold_lin_rate – Rate model with threshold-linear gain function

## Recorder¶

## Short-Term Plasticity¶

## Spike¶

## Spike-Timing-Dependent Plasticity¶

clopath_synapse – Synapse type for voltage-based STDP after Clopath

jonke_synapse – Synapse type for spike-timing dependent plasticity with additional additive factors.

stdp_dopamine_synapse – Synapse type for dopamine-modulated spike-timing dependent plasticity

stdp_pl_synapse_hom – Synapse type for spike-timing dependent plasticity with power law

stdp_synapse – Synapse type for spike-timing dependent plasticity

stdp_synapse_hom – Synapse type for spike-timing dependent plasticity using homogeneous parameters

stdp_triplet_synapse – Synapse type with spike-timing dependent plasticity (triplets)

urbanczik_synapse – Synapse type for a plastic synapse after Urbanczik and Senn

## Static¶

## Stimulation Backend¶

## Synapse¶

bernoulli_synapse – Static synapse with stochastic transmission

clopath_synapse – Synapse type for voltage-based STDP after Clopath

ht_synapse – Synapse with depression after Hill & Tononi (2005)

jonke_synapse – Synapse type for spike-timing dependent plasticity with additional additive factors.

quantal_stp_synapse – Probabilistic synapse model with short term plasticity

rate_connection_delayed – Synapse type for rate connections with delay

rate_connection_instantaneous – Synapse type for instantaneous rate connections

static_synapse_hom_w – Synapse type for static connections with homogeneous weight

stdp_dopamine_synapse – Synapse type for dopamine-modulated spike-timing dependent plasticity

stdp_pl_synapse_hom – Synapse type for spike-timing dependent plasticity with power law

stdp_synapse – Synapse type for spike-timing dependent plasticity

stdp_synapse_hom – Synapse type for spike-timing dependent plasticity using homogeneous parameters

stdp_triplet_synapse – Synapse type with spike-timing dependent plasticity (triplets)

tsodyks_synapse_hom – Synapse type with short term plasticity using homogeneous parameters

urbanczik_synapse – Synapse type for a plastic synapse after Urbanczik and Senn