Neuron Model Reference — 121 Python / 174 Rust¶

SC-NeuroCore provides 121 neuron models in Python (114 files in models/) and 173 Rust implementations callable via PyO3 bindings. Both backends expose identical step() / reset() / get_state() interfaces.

Quick Start¶

Python

# Python backend (default)
from sc_neurocore.neurons.models import HodgkinHuxleyNeuron
hh = HodgkinHuxleyNeuron()
spike = hh.step(current=10.0)

# Rust backend (faster, identical interface)
from sc_neurocore_engine.sc_neurocore_engine import HodgkinHuxleyNeuron
hh_rs = HodgkinHuxleyNeuron()
spike = hh_rs.step(current=10.0)

Backend Selection¶

Backend	Import path	Use case
Python	`sc_neurocore.neurons.models`	Prototyping, parameter tuning, debugging
Rust	`sc_neurocore_engine.sc_neurocore_engine`	Production, benchmarks, batch simulation

Both backends use identical class names (e.g., HodgkinHuxleyNeuron). The Rust engine provides 174 neuron models with PyO3 bindings, 161 of which are wired into the NetworkRunner pipeline.

Model Catalogue¶

Trivial IF Variants (18 models)¶

Python Class	Rust Class	Reference
`QuadraticIFNeuron`	`QuadraticIFNeuron`	Latham et al. 2000
`ThetaNeuron`	`ThetaNeuron`	Ermentrout & Kopell 1986
`PerfectIntegratorNeuron`	`PerfectIntegratorNeuron`	—
`GatedLIFNeuron`	`GatedLIFNeuron`	—
`NonlinearLIFNeuron`	`NonlinearLIFNeuron`	Touboul & Brette 2008
`SFANeuron`	`SFANeuron`	Benda & Herz 2003
`MATNeuron`	`MATNeuron`	Kobayashi et al. 2009
`EscapeRateNeuron`	`EscapeRateNeuron`	Gerstner 2000
`KLIFNeuron`	`KLIFNeuron`	Eshraghian et al. 2021
`InhibitoryLIFNeuron`	`InhibitoryLIFNeuron`	—
`ComplementaryLIFNeuron`	`ComplementaryLIFNeuron`	—
`ParametricLIFNeuron`	`ParametricLIFNeuron`	Fang et al. 2021
`NonResettingLIFNeuron`	`NonResettingLIFNeuron`	Brette 2004
`AdaptiveThresholdIFNeuron`	`AdaptiveThresholdIFNeuron`	Platkiewicz & Brette 2010
`SigmaDeltaNeuron`	`SigmaDeltaNeuron`	—
`EnergyLIFNeuron`	`EnergyLIFNeuron`	Sengupta et al. 2013
`IntegerQIFNeuron`	`IntegerQIFNeuron`	—
`ClosedFormContinuousNeuron`	`ClosedFormContinuousNeuron`	Hasani et al. 2022

Simple Spiking (21 models)¶

Python Class	Rust Class	Reference
`FitzHughNagumoNeuron`	`FitzHughNagumoNeuron`	FitzHugh 1961
`MorrisLecarNeuron`	`MorrisLecarNeuron`	Morris & Lecar 1981
`HindmarshRoseNeuron`	`HindmarshRoseNeuron`	Hindmarsh & Rose 1984
`ResonateAndFireNeuron`	`ResonateAndFireNeuron`	Izhikevich 2001
`BalancedResonateAndFireNeuron`	`BalancedResonateAndFireNeuron`	Higuchi et al. 2024
`FitzHughRinzelNeuron`	`FitzHughRinzelNeuron`	Rinzel 1987
`McKeanNeuron`	`McKeanNeuron`	McKean 1970
`TermanWangOscillator`	`TermanWangOscillator`	Terman & Wang 1995
`BendaHerzNeuron`	`BendaHerzNeuron`	Benda & Herz 2003
`AlphaNeuron`	`AlphaNeuron`	—
`COBALIFNeuron`	`COBALIFNeuron`	Brette et al. 2007
`GutkinErmentroutNeuron`	`GutkinErmentroutNeuron`	Gutkin & Ermentrout 1998
`WilsonHRNeuron`	`WilsonHRNeuron`	Wilson 1999
`ChayNeuron`	`ChayNeuron`	Chay 1985
`ChayKeizerNeuron`	`ChayKeizerNeuron`	Chay & Keizer 1983
`ShermanRinzelKeizerNeuron`	`ShermanRinzelKeizerNeuron`	Sherman et al. 1988
`ButeraRespiratoryNeuron`	`ButeraRespiratoryNeuron`	Butera et al. 1999
`EPropALIFNeuron`	`EPropALIFNeuron`	Bellec et al. 2020
`SuperSpikeNeuron`	`SuperSpikeNeuron`	Zenke & Ganguli 2018
`LearnableNeuronModel`	`LearnableNeuronModel`	—
`PernarowskiNeuron`	`PernarowskiNeuron`	Pernarowski 1994

Discrete Maps (6 models)¶

Python Class	Rust Class	Reference
`ChialvoMapNeuron`	`ChialvoMapNeuron`	Chialvo 1995
`RulkovMapNeuron`	`RulkovMapNeuron`	Rulkov 2001
`IbarzTanakaMapNeuron`	`IbarzTanakaMapNeuron`	Ibarz et al. 2011
`MedvedevMapNeuron`	`MedvedevMapNeuron`	Medvedev 2005
`CazellesMapNeuron`	`CazellesMapNeuron`	Cazelles et al. 2001
`CourageNekorkinMapNeuron`	`CourageNekorkinMapNeuron`	Courbage & Nekorkin 2010

Biophysical / Conductance-Based (20 models)¶

Python Class	Rust Class	Reference
`HodgkinHuxleyNeuron`	`HodgkinHuxleyNeuron`	Hodgkin & Huxley 1952
`TraubMilesNeuron`	`TraubMilesNeuron`	Traub & Miles 1991
`WangBuzsakiNeuron`	`WangBuzsakiNeuron`	Wang & Buzsáki 1996
`ConnorStevensNeuron`	`ConnorStevensNeuron`	Connor et al. 1977
`DestexheThalamicNeuron`	`DestexheThalamicNeuron`	Destexhe et al. 1993
`HuberBraunNeuron`	`HuberBraunNeuron`	Braun et al. 1998
`GolombFSNeuron`	`GolombFSNeuron`	Golomb et al. 2007
`PospischilNeuron`	`PospischilNeuron`	Pospischil et al. 2008
`MainenSejnowskiNeuron`	`MainenSejnowskiNeuron`	Mainen & Sejnowski 1996
`DeSchutterPurkinjeNeuron`	`DeSchutterPurkinjeNeuron`	De Schutter & Bower 1994
`PlantR15Neuron`	`PlantR15Neuron`	Plant & Kim 1976
`PrescottNeuron`	`PrescottNeuron`	Prescott et al. 2008
`MihalasNieburNeuron`	`MihalasNieburNeuron`	Mihalas & Niebur 2009
`GLIFNeuron`	`GLIFNeuron`	Allen Institute GLIF5
`GIFPopulationNeuron`	`GIFPopulationNeuron`	Mensi et al. 2012
`AvRonCardiacNeuron`	`AvRonCardiacNeuron`	Av-Ron et al. 1991
`DurstewitzDopamineNeuron`	`DurstewitzDopamineNeuron`	Durstewitz et al. 2000
`HillTononiNeuron`	`HillTononiNeuron`	Hill & Tononi 2005
`BertramPhantomBurster`	`BertramPhantomBurster`	Bertram et al. 2000
`YamadaNeuron`	`YamadaNeuron`	Yamada et al. 1989

Multi-Compartment (7 models)¶

Python Class	Rust Class	Reference
`PinskyRinzelNeuron`	`PinskyRinzelNeuron`	Pinsky & Rinzel 1994
`HayL5PyramidalNeuron`	`HayL5PyramidalNeuron`	Hay et al. 2011
`MarderSTGNeuron`	`MarderSTGNeuron`	Marder & Calabrese 1996
`RallCableNeuron`	`RallCableNeuron`	Rall 1964
`BoothRinzelNeuron`	`BoothRinzelNeuron`	Booth et al. 1997
`DendrifyNeuron`	`DendrifyNeuron`	Beniaguev et al. 2022
`TwoCompartmentLIFNeuron`	`TwoCompartmentLIFNeuron`	—

Stochastic / Population / Neural Mass (13 models)¶

Python Class	Rust Class	Reference
`PoissonNeuron`	`PoissonNeuron`	—
`InhomogeneousPoissonNeuron`	`InhomogeneousPoissonNeuron`	—
`GammaRenewalNeuron`	`GammaRenewalNeuron`	—
`StochasticIFNeuron`	`StochasticIFNeuron`	—
`GalvesLocherbachNeuron`	`GalvesLocherbachNeuron`	Galves & Löcherbach 2013
`SpikeResponseNeuron`	`SpikeResponseNeuron`	Gerstner 1995 (SRM0)
`GLMNeuron`	`GLMNeuron`	Pillow et al. 2008
`WilsonCowanUnit`	`WilsonCowanUnit`	Wilson & Cowan 1972
`JansenRitUnit`	`JansenRitUnit`	Jansen & Rit 1995
`WongWangUnit`	`WongWangUnit`	Wong & Wang 2006
`ErmentroutKopellPopulation`	`ErmentroutKopellPopulation`	Montbrió et al. 2015
`WendlingNeuron`	`WendlingNeuron`	Wendling et al. 2002
`LarterBreakspearNeuron`	`LarterBreakspearNeuron`	Breakspear et al. 2003

Hardware Chip Emulators (9 models)¶

Python Class	Rust Class	Reference
`LoihiCUBANeuron`	`LoihiCUBANeuron`	Davies et al. 2018 (Intel Loihi)
`Loihi2Neuron`	`Loihi2Neuron`	Intel Loihi 2
`TrueNorthNeuron`	`TrueNorthNeuron`	Merolla et al. 2014 (IBM)
`BrainScaleSAdExNeuron`	`BrainScaleSAdExNeuron`	Schemmel et al. 2010
`SpiNNakerLIFNeuron`	`SpiNNakerLIFNeuron`	Furber et al. 2014
`SpiNNaker2Neuron`	`SpiNNaker2Neuron`	TU Dresden 2024
`DPINeuron`	`DPINeuron`	Bartolozzi & Indiveri 2007
`AkidaNeuron`	`AkidaNeuron`	BrainChip
`NeuroGridNeuron`	`NeuroGridNeuron`	Boahen 2014

Rate / Plasticity / Other (12 models)¶

Python Class	Rust Class	Reference
`McCullochPittsNeuron`	`McCullochPittsNeuron`	McCulloch & Pitts 1943
`SigmoidRateNeuron`	`SigmoidRateNeuron`	Wilson & Cowan 1972
`ThresholdLinearRateNeuron`	`ThresholdLinearRateNeuron`	—
`AstrocyteModel`	`AstrocyteModel`	Li & Rinzel 1994
`TsodyksMarkramNeuron`	`TsodyksMarkramNeuron`	Tsodyks & Markram 1997
`LiquidTimeConstantNeuron`	`LiquidTimeConstantNeuron`	Hasani et al. 2021
`CompteWMNeuron`	`CompteWMNeuron`	Compte et al. 2000
`SiegertTransferFunction`	`SiegertTransferFunction`	Siegert 1951
`FractionalLIFNeuron`	`FractionalLIFNeuron`	Teka et al. 2014
`ParallelSpikingNeuron`	`ParallelSpikingNeuron`	Fang et al. 2023
`AmariNeuralField`	`AmariNeuralField`	Amari 1977
`LeakyCompeteFireNeuron`	`LeakyCompeteFireNeuron`	—

Core IF (Rust neuron.rs) (3 models)¶

Python Class	Rust Class	Reference
`AdExNeuron`	`AdExNeuron`	Brette & Gerstner 2005
`ExpIFNeuron`	`ExpIFNeuron`	Fourcaud-Trocmé et al. 2003
`LapicqueNeuron`	`LapicqueNeuron`	Lapicque 1907

Common Interface¶

All models share:

Python

model.step(current)   # → int (spike: 1/0) or float (firing rate)
model.reset()         # → None (restore initial conditions)
model.get_state()     # → dict of current state variables

Multi-input models accept additional arguments: - AlphaNeuron.step(exc_current, inh_current) - COBALIFNeuron.step(current, delta_ge, delta_gi) - PinskyRinzelNeuron.step(current_soma, current_dend) - TsodyksMarkramNeuron.step(current, presynaptic_spike) - CompteWMNeuron.step(current, spike_in)

Neural mass models return float (firing rate or EEG potential): - WilsonCowanUnit, JansenRitUnit, WendlingNeuron - ErmentroutKopellPopulation, LarterBreakspearNeuron - SigmoidRateNeuron, SiegertTransferFunction

AI-Optimized (9 models)¶

Novel neuron models designed for AI workloads, not biological simulation. Located in neurons/models/ai_optimized.py and neurons/models/arcane_neuron.py.

Python Class	Rust Class	Key Feature
`ArcaneNeuron`	`ArcaneNeuron`	5-compartment self-referential cognition: fast (5ms), working memory (200ms), deep context (10s), attention gate, forward self-model. Identity accumulates in the deep compartment. Confidence modulates threshold and meta-learning rate. Sotek & Arcane Sapience 2026.
`MultiTimescaleNeuron`	—	Three-compartment (fast/medium/slow) with context-dependent threshold modulation
`AttentionGatedNeuron`	—	Learned sigmoid gate (key/query weights) selectively filters input
`PredictiveCodingNeuron`	—	Fires only on prediction errors (novel stimuli), silent on expected input
`SelfReferentialNeuron`	—	Introspects own spike history to auto-regulate firing dynamics
`CompositionalBindingNeuron`	—	Phase-coding for variable binding; in-phase = bound concepts
`DifferentiableSurrogateNeuron`	—	Trainable surrogate gradient parameters (alpha, beta, theta)
`ContinuousAttractorNeuron`	—	Ring attractor with Mexican-hat connectivity for continuous working memory
`MetaPlasticNeuron`	—	Self-regulating meta-learning rate based on error trace