Models that contain the Cell : Abstract Izhikevich neuron

("We present a model that reproduces spiking and bursting behavior of known types of cortical neurons. The model combines the biologically plausibility of Hodgkin-Huxley-type dynamics and the computational efficiency of integrate-and-fire neurons. Using this model, one can simulate tens of thousands of spiking cortical neurons in real time (1 ms resolution) using a desktop PC." (Izhikevich 2003))
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    Models
1. A spiking neural network model of the Lateral Geniculate Nucleus (Sen-Bhattacharya et al 2017)
2. Artificial neuron model (Izhikevich 2003, 2004, 2007)
3. CA1 pyramidal neuron (Ferguson et al. 2014)
4. CA1 pyramidal neuron network model (Ferguson et al 2015)
5. CA1 SOM+ (OLM) hippocampal interneuron (Ferguson et al. 2015)
6. Cortex-Basal Ganglia-Thalamus network model (Kumaravelu et al. 2016)
7. Cortico-striatal plasticity in medium spiny neurons (Gurney et al 2015)
8. Evolving simple models of diverse dynamics in hippocampal neuron types (Venkadesh et al 2018)
9. Gap junction plasticity as a mechanism to regulate network-wide oscillations (Pernelle et al 2018)
10. Hyperbolic model (Daneshzand et al 2017)
11. Input strength and time-varying oscillation peak frequency (Cohen MX 2014)
12. Mean-field systems and small scale neural networks (Ferguson et al. 2015)
13. Motor system model with reinforcement learning drives virtual arm (Dura-Bernal et al 2017)
14. Norns - Neural Network Studio (Visser & Van Gils 2014)
15. Parallelizing large networks in NEURON (Lytton et al. 2016)
16. Reproducing infra-slow oscillations with dopaminergic modulation (Kobayashi et al 2017)
17. Role for short term plasticity and OLM cells in containing spread of excitation (Hummos et al 2014)
18. Supervised learning in spiking neural networks with FORCE training (Nicola & Clopath 2017)

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