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  2. Spiking neural network - Wikipedia

    en.wikipedia.org/wiki/Spiking_neural_network

    The biologically inspired Hodgkin–Huxley model of a spiking neuron was proposed in 1952. This model describes how action potentials are initiated and propagated. . Communication between neurons, which requires the exchange of chemical neurotransmitters in the synaptic gap, is described in various models, such as the integrate-and-fire model, FitzHugh–Nagumo model (1961–1962), and ...

  3. Biological neuron model - Wikipedia

    en.wikipedia.org/wiki/Biological_neuron_model

    The spiking neuron model by Nossenson & Messer [72] [73] [74] produces the probability of the neuron firing a spike as a function of either an external or pharmacological stimulus. [72] [73] [74] The model consists of a cascade of a receptor layer model and a spiking neuron model, as shown in Fig 4. The connection between the external stimulus ...

  4. Spike response model - Wikipedia

    en.wikipedia.org/wiki/Spike_Response_Model

    The spike response model (SRM) [1] is a spiking neuron model in which spikes are generated by either a deterministic [2] or a stochastic [1] threshold process. In the SRM, the membrane voltage V is described as a linear sum of the postsynaptic potentials (PSPs) caused by spike arrivals to which the effects of refractoriness and adaptation are added.

  5. Galves–Löcherbach model - Wikipedia

    en.wikipedia.org/wiki/Galves–Löcherbach_model

    3D Vizualization of the Galves–Löcherbach model simulating the spiking of 4000 neurons (4 layers with one population of inhibitory neurons and one population of excitatory neurons each) in 180 time intervals. The Galves–Löcherbach model (or GL model) is a mathematical model for a network of neurons with intrinsic stochasticity. [1] [2]

  6. Neural oscillation - Wikipedia

    en.wikipedia.org/wiki/Neural_oscillation

    A model of a biological neuron is a mathematical description of the properties of nerve cells, or neurons, that is designed to accurately describe and predict its biological processes. One of the most successful neuron models is the Hodgkin–Huxley model, for which Hodgkin and Huxley won the 1963 Nobel Prize in physiology or medicine.

  7. Nervous system network models - Wikipedia

    en.wikipedia.org/wiki/Nervous_system_network_models

    The firing neuron described above is called a spiking neuron. We will model the electrical circuit of the neuron in Section 3.6. There are two types of spiking neurons. If the stimulus remains above the threshold level and the output is a spike train, it is called the Integrate-and-Fire (IF) neuron model.

  8. FitzHugh–Nagumo model - Wikipedia

    en.wikipedia.org/wiki/FitzHugh–Nagumo_model

    The FitzHugh–Nagumo model is a simplified 2D version of the Hodgkin–Huxley model which models in a detailed manner activation and deactivation dynamics of a spiking neuron. In turn, the Van der Pol oscillator is a special case of the FitzHugh–Nagumo model, with a = b = 0 {\displaystyle a=b=0} .

  9. Exponential integrate-and-fire - Wikipedia

    en.wikipedia.org/wiki/Exponential_integrate-and-fire

    The exponential integrate-and-fire model (EIF) is a biological neuron model, a simple modification of the classical leaky integrate-and-fire model describing how neurons produce action potentials. In the EIF, the threshold for spike initiation is replaced by a depolarizing non-linearity.

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