热敏神经元的相干共振、参数估计和自我调节。

IF 3.1 3区 工程技术 Q2 NEUROSCIENCES
Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-05-19 DOI:10.1007/s11571-025-10258-6
Qun Guo, Ping Zhou, Xiaofeng Zhang, Zhigang Zhu
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引用次数: 0

摘要

本文利用热敏电阻连接的两个电容来研究神经元双层膜的电学性质,该双层膜的电学性质对温度变化敏感,并利用两个电容变量来测量内外膜的电势。从物理角度阐明了振荡形式的神经回路及其等效神经元模型的电路特性和能量定义。考虑到细胞膜在外界物理刺激和能量注入下的形状变形,神经元的内在参数可以在能量流下自适应生长,提出了一种自适应控制律来调节伴随能量转移的放电模式。在有噪声激励的情况下,通过控制噪声强度可以诱发和确认相干共振。变异系数CV (coefficient variability)和平均能量值H > vs.的分布。噪声强度为预测神经活动中的相干共振甚至随机共振提供了一种可行的方法。设计了自适应参数观测器来识别神经元模型中的未知参数。本研究成果为温度自适应仿生神经形态装置的设计和具有温度敏感性的多功能感知神经网络的研究奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coherence resonance, parameter estimation and self-regulation in a thermalsensitive neuron.

In this work, two capacitors connected by a thermistor are used to explore the electrical property of double-layer membrane in a neuron, which the membrane property is sensitive to changes of temperature and two capacitive variables are used to measure the potentials of inner and outer membrane. The circuit characteristics and energy definition for the neural circuit and its equivalent neuron model in oscillator form are clarified from physical aspect. Considering the shape deformation of cell membrane under external physical stimuli and energy injection, intrinsic parameters of the neuron can be controlled with adaptive growth under energy flow, an adaptive control law is proposed to regulate the firing modes accompanying with energy shift. In presence of noisy excitation, coherence resonance can be induced and confirmed by taming the noise intensity carefully. The distributions of CV (coefficient variability) and average energy value < H > vs. noise intensity provide a feasible way to predict the coherence resonance and even stochastic resonance in the neural activities. Adaptive parameter observers are designed to identify the unknown parameters in this neuron model. The research findings of this study lay a foundation for the design of temperature-adaptive biomimetic neuromorphic devices and the research on multi-functional perception neural networks with temperature sensitivity.

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来源期刊
Cognitive Neurodynamics
Cognitive Neurodynamics 医学-神经科学
CiteScore
6.90
自引率
18.90%
发文量
140
审稿时长
12 months
期刊介绍: Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models. The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome. The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged. 1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics. 2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages. 3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.
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