Energy-efficient firing modes of chay neuron model in different bursting kinetics

Abstract

The firing sequence of the neuron system that transmits information consumes a significant amount of energy, but it is unclear how the firing pattern of the neuron system determines its energy efficiency. The mode transformation and energy efficiency in different firing modes are investigated using the Chay neuron model. It has been found that when system parameters are tuned, the neurons show complex bursting kinetics. The period-n bursting state of the neuron carries high amounts of information while consuming less energy per unit of information, resulting in higher energy efficiency. In particular, the mixed discharge state, where the neuron is in several bursting states simultaneously, is more energy efficient, and appropriate electromagnetic inductioncan enhance the neuron's energy efficiency. Furthermore, there are optimal system parameters that maximize the energy efficiency of firing modes, demonstrating that the neuron carries high amounts of information while consuming less energy per unit of information. The study helps to understand the energy mechanism of neural information propagation and provides an insight into the energy efficiency characteristic of neuron systems.

Dynamics in a light-sensitive neuron with two capacitive variables

“…Experimental detection is crucial for model approach and improvement for biophysical neuron models. Generic neuron models in mathematical form provide an effective dynamical analysis and prediction of mode selection under external stimuli including electromagnetic radiation and mechanical excitation [6][7][8][9][10]. Indeed, complex physical effect should be considered into the neural activities during stochastic diffusion of intracellular ions and exchange between intracellular and extracellular ions across ion channels in the cell membrane.…”