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Another may be a conductance-based neuron model that views neurons as points and describes the membrane voltage dynamics as a function of trans-membrane currents. A mathematically simpler "integrate-and-fire" model significantly simplifies the description of ion channel and membrane potential dynamics (initially studied by Lapique in 1907). [5] [6]
The focus of this article is a comprehensive view of modeling a neural network (technically neuronal network based on neuron model). Once an approach based on the perspective and connectivity is chosen, the models are developed at microscopic (ion and neuron), mesoscopic (functional or population), or macroscopic (system) levels.
For example (Fig. 1), in a basic neural circuit with two input neurons—A and B—that have excitatory synaptic terminals converging on a single output neuron (C), if each input neuron's EPSP is sub-threshold for an action potential at C, then C cannot fire unless the two inputs from A and B are temporally close.
Cells can be managed. The user creates the basic grid of network cells, taking previously completed network cells as archetypes. Connections can be defined between source cells and target synapses on other cells. The cell containing the target synapse becomes the post-synaptic element, whereas the source cells function as pre-synaptic elements.
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]
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 ...
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
A common use of the phrase "ANN model" is really the definition of a class of such functions (where members of the class are obtained by varying parameters, connection weights, or specifics of the architecture such as the number of neurons, number of layers or their connectivity).