Ahmed B, Anderson JC, Douglas RJ, Martin KA, Whitteridge D. (1998). Estimates of the net excitatory currents evoked by visual stimulation of identified neurons in cat visual cortex. Cerebral cortex (New York, N.Y. : 1991). 8 [PubMed]

Amatrudo JM et al. (2012). Influence of highly distinctive structural properties on the excitability of pyramidal neurons in monkey visual and prefrontal cortices. The Journal of neuroscience : the official journal of the Society for Neuroscience. 32 [PubMed]

• Rhesus Monkey Layer 3 Pyramidal Neurons: V1 vs PFC (Amatrudo, Weaver et al. 2012) [Model]

Avella Gonzalez OJ, van Aerde KI, Mansvelder HD, van Pelt J, van Ooyen A. (2014). Inter-network interactions: impact of connections between oscillatory neuronal networks on oscillation frequency and pattern. PloS one. 9 [PubMed]

• A two networks model of connectivity-dependent oscillatory activity (Avella OJ et al. 2014) [Model]

Avella Gonzalez OJ et al. (2012). External drive to inhibitory cells induces alternating episodes of high- and low-amplitude oscillations. PLoS computational biology. 8 [PubMed]

• Single E-I oscillating network with amplitude modulation (Avella Gonzalez et al. 2012) [Model]

Azouz R, Gray CM. (2000). Dynamic spike threshold reveals a mechanism for synaptic coincidence detection in cortical neurons in vivo. Proceedings of the National Academy of Sciences of the United States of America. 97 [PubMed]

Azouz R, Gray CM. (2008). Stimulus-selective spiking is driven by the relative timing of synchronous excitation and disinhibition in cat striate neurons in vivo. The European journal of neuroscience. 28 [PubMed]

Brunel N, Hakim V. (1999). Fast global oscillations in networks of integrate-and-fire neurons with low firing rates. Neural computation. 11 [PubMed]

• Fast global oscillations in networks of I&F neurons with low firing rates (Brunel and Hakim 1999) [Model]

Börgers C, Kopell N. (2005). Effects of noisy drive on rhythms in networks of excitatory and inhibitory neurons. Neural computation. 17 [PubMed]

Daneshzand M, Faezipour M, Barkana BD. (2017). Hyperbolic Modeling of Subthalamic Nucleus Cells to Investigate the Effect of Dopamine Depletion. Computational intelligence and neuroscience. 2017 [PubMed]

• Hyperbolic model (Daneshzand et al 2017) [Model]

Doiron B, Laing C, Longtin A, Maler L. (2002). Ghostbursting: a novel neuronal burst mechanism. Journal of computational neuroscience. 12 [PubMed]

Doiron B, Longtin A, Turner RW, Maler L. (2001). Model of gamma frequency burst discharge generated by conditional backpropagation. Journal of neurophysiology. 86 [PubMed]

Doiron B, Noonan L, Lemon N, Turner RW. (2003). Persistent Na+ current modifies burst discharge by regulating conditional backpropagation of dendritic spikes. Journal of neurophysiology. 89 [PubMed]

Gabbiani F, Cox SJ. (2010). Mathematics for Neuroscientists.

• Mathematics for Neuroscientists (Gabbiani and Cox 2010) [Model]

García-Pérez MA. (2004). A nonlinear model of the behavior of simple cells in visual cortex. Journal of computational neuroscience. 17 [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. (2004). Which model to use for cortical spiking neurons? IEEE transactions on neural networks. 15 [PubMed]

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

Kanamaru T. (2006). Analysis of synchronization between two modules of pulse neural networks with excitatory and inhibitory connections. Neural computation. 18 [PubMed]

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]

Lee J. (2007). Fast Rhythmic Bursting Cells: The Horizontal Fiber System in the Cat’s Primary Visual Cortex Penn McNair Research Journal. 1(1)

• A Fast Rhythmic Bursting Cell: in vivo cell modeling (Lee 2007) [Model]

Menschik ED, Finkel LH. (1998). Neuromodulatory control of hippocampal function: towards a model of Alzheimer's disease. Artificial intelligence in medicine. 13 [PubMed]

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

Mosher CP et al. (2020). Cellular Classes in the Human Brain Revealed In Vivo by Heartbeat-Related Modulation of the Extracellular Action Potential Waveform. Cell reports. 30 [PubMed]

• Cellular classes revealed by heartbeat-related modulation of extracellular APs (Mosher et al 2020) [Model]

Pinto DJ, Jones SR, Kaper TJ, Kopell N. (2003). Analysis of State-Dependent Transitions in Frequency and Long-Distance Coordination in a Model Oscillatory Cortical Circuit Journal of computational neuroscience. 15 [PubMed]

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]

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]

Sailamul P, Jang J, Paik SB. (2017). Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks. Journal of computational neuroscience. 43 [PubMed]

• Convergence regulates synchronization-dependent AP transfer in feedforward NNs (Sailamul et al 2017) [Model]

Salinas E, Sejnowski TJ. (2001). Correlated neuronal activity and the flow of neural information. Nature reviews. Neuroscience. 2 [PubMed]

Singer W, Stiefel KM, Wespatat V, Tennigkeit F. (2001). A computational model of the interaction of membrane potential oscillations with inhibitory synaptic input in cortical cells Neurocomputing. 38

Susin E, Destexhe A. (2021). Integration, coincidence detection and resonance in networks of spiking neurons expressing gamma oscillations and asynchronous states PLoS computational biology. 17 [PubMed]

• PING, ING and CHING network models for Gamma oscillations in cortex (Susin and Destexhe 2021) [Model]

Takekawa T, Aoyagi T, Fukai T. (2007). Synchronous and asynchronous bursting states: role of intrinsic neural dynamics. Journal of computational neuroscience. 23 [PubMed]

Tomov P, Pena RF, Roque AC, Zaks MA. (2016). Mechanisms of Self-Sustained Oscillatory States in Hierarchical Modular Networks with Mixtures of Electrophysiological Cell Types. Frontiers in computational neuroscience. 10 [PubMed]

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

Traub RD, Buhl EH, Gloveli T, Whittington MA. (2003). Fast rhythmic bursting can be induced in layer 2/3 cortical neurons by enhancing persistent Na+ conductance or by blocking BK channels. Journal of neurophysiology. 89 [PubMed]

• Mechanisms of fast rhythmic bursting in a layer 2/3 cortical neuron (Traub et al 2003) [Model]

Traub RD, Contreras D, Whittington MA. (2005). Combined experimental/simulation studies of cellular and network mechanisms of epileptogenesis in vitro and in vivo. Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society. 22 [PubMed]

• A single column thalamocortical network model (Traub et al 2005) [Model]
• Collection of simulated data from a thalamocortical network model (Glabska, Chintaluri, Wojcik 2017) [Model]

van Drongelen W et al. (2006). Role of persistent sodium current in bursting activity of mouse neocortical networks in vitro. Journal of neurophysiology. 96 [PubMed]