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The most prominent two-dimensional examples are the adaptive exponential integrate-and-fire model [2] and the generalized exponential integrate-and-fire model. [3] Exponential integrate-and-fire models are widely used in the field of computational neuroscience and spiking neural networks because of (i) a solid grounding of the neuron model in ...
The theta model, or Ermentrout–Kopell canonical Type I model, is mathematically equivalent to the quadratic integrate-and-fire model which in turn is an approximation to the exponential integrate-and-fire model and the Hodgkin-Huxley model. It is called a canonical model because it is one of the generic models for constant input close to the ...
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 ...
NEST aims at high accuracy and precision of its simulations [2] Each neuron model has its appropriate solver and many models have unit tests. If possible, exact integration [3] is used. By default, spikes fall onto the grid, defined by the simulation time-step. Some models support spike-exchange in continuous time. [4]
Many models of communication include the idea that a sender encodes a message and uses a channel to transmit it to a receiver. Noise may distort the message along the way. The receiver then decodes the message and gives some form of feedback. [1] Models of communication simplify or represent the process of communication.
In Schramm's model, communication is only possible if the fields of experience of sender and receiver overlap. [24] [25] Schramm's model of communication is another significant influence on Berlo's model. It was first published by Wilbur Schramm in 1954. For Schramm, communication starts with an idea in the mind of the source.
One of his main contributions was to propose the integrate-and-fire model of the neuron in a seminal article published in 1907. [2] Today, this model of the neuron is still one of the most popular models in computational neuroscience for both cellular and neural networks studies, as well as in mathematical neuroscience because of its simplicity.
The FitzHugh–Nagumo model (FHN) describes a prototype of an excitable system (e.g., a neuron). It is an example of a relaxation oscillator because, if the external stimulus I ext {\displaystyle I_{\text{ext}}} exceeds a certain threshold value, the system will exhibit a characteristic excursion in phase space , before the variables v ...