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CLC number: TN710; O59

On-line Access: 2022-09-21

Received: 2021-12-07

Revision Accepted: 2022-09-21

Crosschecked: 2022-01-12

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714


Jun Ma


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Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.9 P.1407-1420


Phase synchronization and energy balance between neurons

Author(s):  Ying XIE, Zhao YAO, Jun MA

Affiliation(s):  Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China; more

Corresponding email(s):   hyperchaos@lut.edu.cn, hyperchaos@163.com

Key Words:  Hamilton energy, Coupling synchronization, Synapse enhancement, Neural circuit

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Ying XIE, Zhao YAO, Jun MA. Phase synchronization and energy balance between neurons[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(9): 1407-1420.

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author="Ying XIE, Zhao YAO, Jun MA",
journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

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%T Phase synchronization and energy balance between neurons
%A Ying XIE
%A Zhao YAO
%A Jun MA
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%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2100563

T1 - Phase synchronization and energy balance between neurons
A1 - Ying XIE
A1 - Zhao YAO
A1 - Jun MA
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 23
IS - 9
SP - 1407
EP - 1420
%@ 2095-9184
Y1 - 2022
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2100563

A functional neuron has been developed from a simple neural circuit by incorporating a phototube and a thermistor in different branch circuits. The physical field energy is controlled by the photocurrent across the phototube and the channel current across the thermistor. The firing mode of this neuron is controlled synchronously by external temperature and illumination. There is energy diversity when two functional neurons are exposed to different illumination and temperature conditions. As a result, synapse connections can be created and activated in an adaptive way when field energy is exchanged between neurons. We propose two kinds of criteria to discuss the enhancement of synapse connections to neurons. The energy diversity between neurons determines the increase of the coupling intensity and synaptic current for neurons, and the realization of synchronization is helpful in maintaining energy balance between neurons. The first criterion is similar to the saturation gain scheme in that the coupling intensity is increased with a constant step within a certain period until it reaches energy balance or complete synchronization. The second criterion is that the coupling intensity increases exponentially before reaching energy balance. When two neurons become non-identical, phase synchronization can be controlled during the activation of synapse connections to neurons. For two identical neurons, the second criterion for taming synaptic intensity is effective for reaching complete synchronization and energy balance, even in the presence of noise. This indicates that a synapse connection may prefer to enhance its coupling intensity exponentially. These results are helpful in discovering why synapses are awaken and synaptic current becomes time-varying when any neurons are excited by external stimuli. The potential biophysical mechanism is that energy balance is broken and then synapse connections are activated to maintain an adaptive energy balance between the neurons. These results provide guidance for designing and training intelligent neural networks by taming the coupling channels with gradient energy distribution.




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