Connors BW, Gutnick MJ. (1990). Intrinsic firing patterns of diverse neocortical neurons. Trends in neurosciences. 13 [PubMed]

Ermentrout B. (1996). Type I membranes, phase resetting curves, and synchrony. Neural computation. 8 [PubMed]

Fitzhugh R. (1961). Impulses and Physiological States in Theoretical Models of Nerve Membrane. Biophysical journal. 1 [PubMed]

Gibson JR, Beierlein M, Connors BW. (1999). Two networks of electrically coupled inhibitory neurons in neocortex. Nature. 402 [PubMed]

Gray CM, McCormick DA. (1996). Chattering cells: superficial pyramidal neurons contributing to the generation of synchronous oscillations in the visual cortex. Science (New York, N.Y.). 274 [PubMed]

HODGKIN AL, HUXLEY AF. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of physiology. 117 [PubMed]

• Squid axon (Hodgkin, Huxley 1952) (NEURON) [Model]
• Squid axon (Hodgkin, Huxley 1952) (SNNAP) [Model]
• Squid axon (Hodgkin, Huxley 1952) (LabAXON) [Model]
• Squid axon (Hodgkin, Huxley 1952) (SBML, XPP, other) [Model]
• Squid axon (Hodgkin, Huxley 1952) used in (Chen et al 2010) (R language) [Model]

Hodgkin AL. (1948). The local electric changes associated with repetitive action in a non-medullated axon. The Journal of physiology. 107 [PubMed]

Izhikevich EM. (1999). Class 1 neural excitability, conventional synapses, weakly connected networks, and mathematical foundations of pulse-coupled models. IEEE transactions on neural networks. 10 [PubMed]

Izhikevich EM. (2000). Neural excitability, spiking and bursting Int J Bifurcat Chaos Appl Sci Eng. 10

Izhikevich EM. (2001). Resonate-and-fire neurons. Neural networks : the official journal of the International Neural Network Society. 14 [PubMed]

Izhikevich EM. (2003). Simple model of spiking neurons. IEEE transactions on neural networks. 14 [PubMed]

• Artificial neuron model (Izhikevich 2003, 2004, 2007) [Model]

Izhikevich EM. (2007). Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting.

• Artificial neuron model (Izhikevich 2003, 2004, 2007) [Model]

Izhikevich EM, Desai NS, Walcott EC, Hoppensteadt FC. (2003). Bursts as a unit of neural information: selective communication via resonance. Trends in neurosciences. 26 [PubMed]

Izhikevich EM, Gally JA, Edelman GM. (2004). Spike-timing dynamics of neuronal groups. Cerebral cortex (New York, N.Y. : 1991). 14 [PubMed]

Izhikevich EM, Hoppensteadt FC. (1997). Weakly Connected Neural Networks.

Kistler WM, Gerstner W. (2002). Spiking neuron models.

Kopell N, Ermentrout GB. (1986). Parabolic bursting in an excitable system coupled with a slow oscillation. Siam J Appl Math. 46

Latham PE, Richmond BJ, Nelson PG, Nirenberg S. (2000). Intrinsic dynamics in neuronal networks. I. Theory. Journal of neurophysiology. 83 [PubMed]

Lisman JE. (1997). Bursts as a unit of neural information: making unreliable synapses reliable. Trends in neurosciences. 20 [PubMed]

Morris C, Lecar H. (1981). Voltage oscillations in the barnacle giant muscle fiber. Biophysical journal. 35 [PubMed]

• Morris-Lecar model of the barnacle giant muscle fiber (Morris, Lecar 1981) [Model]

Rinzel J, Ermentrout GB. (1989). Analysis of neuronal excitability and oscillations Methods In Neuronal Modeling: From Synapses To Networks.

Rose RM, Hindmarsh JL. (1989). The assembly of ionic currents in a thalamic neuron. I. The three-dimensional model. Proceedings of the Royal Society of London. Series B, Biological sciences. 237 [PubMed]

Smith GD, Cox CL, Sherman SM, Rinzel J. (2000). Fourier analysis of sinusoidally driven thalamocortical relay neurons and a minimal integrate-and-fire-or-burst model. Journal of neurophysiology. 83 [PubMed]

Wilson HR. (1999). Simplified dynamics of human and mammalian neocortical neurons. Journal of theoretical biology. 200 [PubMed]

Badel L et al. (2008). Dynamic I-V curves are reliable predictors of naturalistic pyramidal-neuron voltage traces. Journal of neurophysiology. 99 [PubMed]

Baladron J, Nambu A, Hamker FH. (2019). The subthalamic nucleus-external globus pallidus loop biases exploratory decisions towards known alternatives: a neuro-computational study. The European journal of neuroscience. 49 [PubMed]

Destexhe A. (2009). Self-sustained asynchronous irregular states and Up-Down states in thalamic, cortical and thalamocortical networks of nonlinear integrate-and-fire neurons. Journal of computational neuroscience. 27 [PubMed]

• Asynchronous irregular and up/down states in excitatory and inhibitory NNs (Destexhe 2009) [Model]

Geminiani A et al. (2018). Complex Dynamics in Simplified Neuronal Models: Reproducing Golgi Cell Electroresponsiveness. Frontiers in neuroinformatics. 12 [PubMed]

• Complex dynamics: reproducing Golgi cell electroresponsiveness (Geminiani et al 2018, 2019ab) [Model]

Hendrickson EB, Edgerton JR, Jaeger D. (2011). The capabilities and limitations of conductance-based compartmental neuron models with reduced branched or unbranched morphologies and active dendrites. Journal of computational neuroscience. 30 [PubMed]

• Comparison of full and reduced globus pallidus models (Hendrickson 2010) [Model]

Horcholle-Bossavit G, Quenet B. (2009). Neural model of frog ventilatory rhythmogenesis. Bio Systems. 97 [PubMed]

• Neural model of frog ventilatory rhythmogenesis (Horcholle-Bossavit and Quenet 2009) [Model]

Huang C, Zeldenrust F, Celikel T. (2022). Cortical Representation of Touch in Silico Neuroinformatics. 20 [PubMed]

• Realistic barrel cortical column - Matlab (Huang et al., 2022) [Model]
• Realistic barrel cortical column - NetPyNE (Huang et al., 2022) [Model]

Humphries MD, Gurney K. (2007). Solution methods for a new class of simple model neurons. Neural computation. 19 [PubMed]

Humphries MD, Lepora N, Wood R, Gurney K. (2009). Capturing dopaminergic modulation and bimodal membrane behaviour of striatal medium spiny neurons in accurate, reduced models. Frontiers in computational neuroscience. 3 [PubMed]

• Dopamine-modulated medium spiny neuron, reduced model (Humphries et al. 2009) [Model]

Izhikevich EM. (2006). Polychronization: computation with spikes. Neural computation. 18 [PubMed]

• Polychronization: Computation With Spikes (Izhikevich 2005) [Model]

Janjic P, Solev D, Kocarev L. (2023). Non-trivial dynamics in a model of glial membrane voltage driven by open potassium pores Biophysical journal. 122 [PubMed]

• Glial voltage dynamics driven by Kir & K2P currents (Janjic et al 2023) [Model]

Jolivet R, Gerstner W. (2004). Predicting spike times of a detailed conductance-based neuron model driven by stochastic spike arrival. Journal of physiology, Paris. 98 [PubMed]

Jolivet R et al. (2008). A benchmark test for a quantitative assessment of simple neuron models. Journal of neuroscience methods. 169 [PubMed]

• Spike Response Model simulator (Jolivet et al. 2004, 2006, 2008) [Model]

Jolivet R, Rauch A, Lüscher HR, Gerstner W. (2006). Predicting spike timing of neocortical pyramidal neurons by simple threshold models. Journal of computational neuroscience. 21 [PubMed]

• Spike Response Model simulator (Jolivet et al. 2004, 2006, 2008) [Model]

Kobayashi R, Tsubo Y, Shinomoto S. (2009). Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold. Frontiers in computational neuroscience. 3 [PubMed]

• Multi-timescale adaptive threshold model (Kobayashi et al 2009) (NEURON) [Model]
• Multi-timescale adaptive threshold model (Kobayashi et al 2009) [Model]

Komarov M et al. (2018). New class of reduced computationally efficient neuronal models for large-scale simulations of brain dynamics. Journal of computational neuroscience. 44 [PubMed]

Lundqvist M, Rehn M, Djurfeldt M, Lansner A. (2006). Attractor dynamics in a modular network model of neocortex. Network (Bristol, England). 17 [PubMed]

Ly C, Tranchina D. (2007). Critical analysis of dimension reduction by a moment closure method in a population density approach to neural network modeling. Neural computation. 19 [PubMed]

Marasco A et al. (2023). An Adaptive Generalized Leaky Integrate-and-Fire Model for Hippocampal CA1 Pyramidal Neurons and Interneurons. Bulletin of mathematical biology. 85 [PubMed]

• Adaptive Generalized Leaky Integrate-and-Fire Model (AGLIF) (Marasco et al., 2023) [Model]

Matsubara T, Torikai H. (2016). An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities. IEEE transactions on neural networks and learning systems. 27 [PubMed]

Mensi S et al. (2012). Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms. Journal of neurophysiology. 107 [PubMed]

• Extraction and classification of three cortical neuron types (Mensi et al. 2012) [Model]

Mondal A, Upadhyay RK. (2018). Diverse neuronal responses of a fractional-order Izhikevich model: journey from chattering to fast spiking Nonlinear Dynamics. 91

Muresan RC, Savin C. (2007). Resonance or integration? Self-sustained dynamics and excitability of neural microcircuits. Journal of neurophysiology. 97 [PubMed]

Naundorf B, Geisel T, Wolf F. (2005). Action potential onset dynamics and the response speed of neuronal populations. Journal of computational neuroscience. 18 [PubMed]

Pernelle G, Nicola W, Clopath C. (2018). Gap junction plasticity as a mechanism to regulate network-wide oscillations. PLoS computational biology. 14 [PubMed]

• Gap junction plasticity as a mechanism to regulate network-wide oscillations (Pernelle et al 2018) [Model]

Pospischil M et al. (2008). Minimal Hodgkin-Huxley type models for different classes of cortical and thalamic neurons. Biological cybernetics. 99 [PubMed]

• Hodgkin-Huxley models of different classes of cortical neurons (Pospischil et al. 2008) [Model]

Richert M, Nageswaran JM, Dutt N, Krichmar JL. (2011). An efficient simulation environment for modeling large-scale cortical processing. Frontiers in neuroinformatics. 5 [PubMed]

• Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011) [Model]

Rulkov NF, Timofeev I, Bazhenov M. (2004). Oscillations in large-scale cortical networks: map-based model. Journal of computational neuroscience. 17 [PubMed]

• Large cortex model with map-based neurons (Rulkov et al 2004) [Model]

Sadeh S, Clopath C, Rotter S. (2015). Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity. PLoS computational biology. 11 [PubMed]

• Functional balanced networks with synaptic plasticity (Sadeh et al, 2015) [Model]

Schmerl BA, McDonnell MD. (2013). Channel noise induced stochastic facilitation in an auditory brainstem neuron model Physical review. E, Statistical, nonlinear, and soft matter physics. 88 [PubMed]

• Simulating ion channel noise in an auditory brainstem neuron model (Schmerl & McDonnell 2013) [Model]

Sen-Bhattacharya B et al. (2017). A Spiking Neural Network Model of the Lateral Geniculate Nucleus on the SpiNNaker Machine. Frontiers in neuroscience. 11 [PubMed]

• A spiking neural network model of the Lateral Geniculate Nucleus (Sen-Bhattacharya et al 2017) [Model]

Sharma SK, Mondal A, Mondal A, Upadhyay RK, Hens C. (2020). Emergence of bursting in a network of memory dependent excitable and spiking leech-heart neurons. Journal of the Royal Society, Interface. 17 [PubMed]

• Leech Heart Interneuron model (Sharma et al 2020) [Model]

Sterratt DC, Graham B, Gillies A, Willshaw D. (2011). Principles of Computational Modelling in Neuroscience, Cambridge University Press.

• Principles of Computational Modelling in Neuroscience (Book) (Sterratt et al. 2011) [Model]

Stewart RD, Bair W. (2009). Spiking neural network simulation: numerical integration with the Parker-Sochacki method. Journal of computational neuroscience. 27 [PubMed]

• Numerical Integration of Izhikevich and HH model neurons (Stewart and Bair 2009) [Model]

Susi G et al. (2021). FNS allows efficient event-driven spiking neural network simulations based on a neuron model supporting spike latency Scientific reports. 11 [PubMed]

• FNS spiking neural simulator; LIFL neuron model, event-driven simulation (Susi et al 2021) [Model]

Swiercz W et al. (2006). A new synaptic plasticity rule for networks of spiking neurons. IEEE transactions on neural networks. 17 [PubMed]

Teka W, Marinov TM, Santamaria F. (2014). Neuronal spike timing adaptation described with a fractional leaky integrate-and-fire model. PLoS computational biology. 10 [PubMed]

• Fractional leaky integrate-and-fire model (Teka et al. 2014) [Model]

Teramae JN, Fukai T. (2007). Local cortical circuit model inferred from power-law distributed neuronal avalanches. Journal of computational neuroscience. 22 [PubMed]

Tikidji-Hamburyan RA, Martínez JJ, White JA, Canavier CC. (2015). Resonant Interneurons Can Increase Robustness of Gamma Oscillations. The Journal of neuroscience : the official journal of the Society for Neuroscience. 35 [PubMed]

• PIR gamma oscillations in network of resonators (Tikidji-Hamburyan et al. 2015) [Model]

Tomov P, Pena RF, Zaks MA, Roque AC. (2014). Sustained oscillations, irregular firing, and chaotic dynamics in hierarchical modular networks with mixtures of electrophysiological cell types. Frontiers in computational neuroscience. 8 [PubMed]

• Dynamics in random NNs with multiple neuron subtypes (Pena et al 2018, Tomov et al 2014, 2016) [Model]

Touboul J, Brette R. (2008). Dynamics and bifurcations of the adaptive exponential integrate-and-fire model. Biological cybernetics. 99 [PubMed]

• Brette-Gerstner model (Touboul and Brette 2008) [Model]

Valero MR, Hale N, Tang J, Jiang L. (2017). A comprehensive mechanotransduction model for tactile feedback based on multi-axial stresses at the fingertip-contact interface 2017 IEEE World Haptics Conference (WHC).

Versace M, Ames H, Léveillé J, Fortenberry B, Gorchetchnikov A. (2008). KInNeSS: a modular framework for computational neuroscience. Neuroinformatics. 6 [PubMed]

• KInNeSS : a modular framework for computational neuroscience (Versace et al. 2008) [Model]

Świetlik D, Białowąs J, Kusiak A, Cichońska D. (2018). Memory and forgetting processes with the firing neuron model. Folia morphologica. 77 [PubMed]