1. Spiking Neural Networks and Mathematical Models.
- Author
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Gasparinatou MM, Matzakos N, and Vlamos P
- Subjects
- Action Potentials physiology, Neurons physiology, Brain, Models, Neurological, Neural Networks, Computer
- Abstract
Neural networks are applied in various scientific fields such as medicine, engineering, pharmacology, etc. Investigating operations of neural networks refers to estimating the relationship among single neurons and their contributions to the network as well. Hence, studying a single neuron is an essential process to solve complex brain problems. Mathematical models that simulate neurons and the way they transmit information are proven to be an indispensable tool for neuroscientists. Constructing appropriate mathematical models to simulate information transmission of a biological neural network is a challenge for researchers, as in the real world, identical neurons in terms of their electrophysiological characteristics in different brain regions do not contribute in the same way to information transmission within a neural network due to the intrinsic characteristics. This review highlights four mathematical, single-compartment models: Hodgkin-Huxley, Izhikevich, Leaky Integrate, and Fire and Morris-Lecar, and discusses comparison among them in terms of their biological plausibility, computational complexity, and applications, according to modern literature., (© 2023. The Author(s), under exclusive license to Springer Nature Switzerland AG.)
- Published
- 2023
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