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  2. Biological neuron model - Wikipedia

    en.wikipedia.org/wiki/Biological_neuron_model

    Neurons (or nerve cells) are electrically excitable cells within the nervous system, able to fire electric signals, called action potentials, across a neural network. These mathematical models describe the role of the biophysical and geometrical characteristics of neurons on the conduction of electrical activity.

  3. Neuron (software) - Wikipedia

    en.wikipedia.org/wiki/Neuron_(software)

    Neuron allows for the generation of mixed models, populated with both artificial cells and neurons. Artificial cells essentially function as point processes, implemented into the network. Artificial cells require only a point process, with defined parameters. The user can create the structure and dynamics of network cells.

  4. Gibbs–Donnan effect - Wikipedia

    en.wikipedia.org/wiki/Gibbs–Donnan_effect

    Donnan equilibrium across a cell membrane (schematic). The Gibbs–Donnan effect (also known as the Donnan's effect, Donnan law, Donnan equilibrium, or Gibbs–Donnan equilibrium) is a name for the behaviour of charged particles near a semi-permeable membrane that sometimes fail to distribute evenly across the two sides of the membrane. [1]

  5. Compartmental neuron models - Wikipedia

    en.wikipedia.org/wiki/Compartmental_neuron_models

    This allows the development of network models in which each neuron, instead of being modelled as a full blown compartmental cell, it is modelled as a simplified two layer neural network. [4] The firing pattern of the cell might contain the temporal information about incoming signals. For example, the delay between the two simulated pathways. [4]

  6. Hodgkin–Huxley model - Wikipedia

    en.wikipedia.org/wiki/Hodgkin–Huxley_model

    The Hodgkin–Huxley model, or conductance-based model, is a mathematical model that describes how action potentials in neurons are initiated and propagated. It is a set of nonlinear differential equations that approximates the electrical engineering characteristics of excitable cells such as neurons and muscle cells.

  7. Summation (neurophysiology) - Wikipedia

    en.wikipedia.org/wiki/Summation_(neurophysiology)

    Basic ways that neurons can interact with each other when converting input to output. Summation, which includes both spatial summation and temporal summation, is the process that determines whether or not an action potential will be generated by the combined effects of excitatory and inhibitory signals, both from multiple simultaneous inputs (spatial summation), and from repeated inputs ...

  8. Rheobase - Wikipedia

    en.wikipedia.org/wiki/Rheobase

    Bursting cells. Bursting cells will produce multiple spikes once activated. For such cells, it can be very difficult to find the current that produces only a single spike within a given time frame. For such cells, finding the boundary between currents that result in bursts and no bursts could be used. Cells with Sub-threshold Oscillations

  9. Voltage clamp - Wikipedia

    en.wikipedia.org/wiki/Voltage_clamp

    It uses an electrode with a relatively large tip (> 1 micrometer) that has a smooth surface (rather than a sharp tip). This is a "patch-clamp electrode" (as distinct from a "sharp electrode" used to impale cells). This electrode is pressed against a cell membrane and suction is applied to pull the cell's membrane inside the electrode tip.