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Algorithm for Describing Neuronal Electric Operation
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DOI：10.3390/a19010006.png)
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Abstract
En 中文
The development of neuroanatomy and neurophysiology has revealed many new details about neurons' operation over the past few decades, requiring modifications to their theoretical models. The development of computing technology enables us to consider the fine details the new model requires, but it necessitates a different approach. To achieve that goal, the disciplinarity of science must be revisited for living matter, the theoretical model must be updated, and a series of processes instead of states must be considered; furthermore, new mathematics, algorithms, and computing technologies for the new view are also needed. We provide an algorithm implementing the mathematics of the updated theoretical model that considers the neuronal current to consist of charged ions (and so considers thermodynamic effects) and opens the way for explaining the mechanical, optical, etc., consequence phenomena of the electrical operation. We use a new technology in this effort: a tool designed to achieve extreme accuracy in simulating high-speed electronic circuits. The algorithm applies the cross-disciplinary unified electrical/thermodynamic model, along with an unusual programming method, to provide new insights into neuronal operations, describe the processes that take place in living matter, and determine their computing implementation. As has long been suspected, the faithful simulation of biological processes requires accurately mapping biological time to technical computing time. Therefore, the paper focuses on time handling in biology-targeting computations, especially in large-scale tasks. We also touch on the question of simulating the operation of their network, which is contrasted with that of Spiking Neural Networks. The way technical computing works inhibits efforts to achieve the required accuracy in reproducing the temporal behavior of biological operations using conventional computer programs.
Keywords:
neuronal operation
neural event
simulating neuronal operation
thermodynamics of neurons
event-driven programming
spiking neural networks
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