{"title":"热敏神经元的相干共振、参数估计和自我调节。","authors":"Qun Guo, Ping Zhou, Xiaofeng Zhang, Zhigang Zhu","doi":"10.1007/s11571-025-10258-6","DOIUrl":null,"url":null,"abstract":"<p><p>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 <i>CV</i> (coefficient variability) and average energy value < <i>H</i> > 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.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"75"},"PeriodicalIF":3.1000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12089602/pdf/","citationCount":"0","resultStr":"{\"title\":\"Coherence resonance, parameter estimation and self-regulation in a thermalsensitive neuron.\",\"authors\":\"Qun Guo, Ping Zhou, Xiaofeng Zhang, Zhigang Zhu\",\"doi\":\"10.1007/s11571-025-10258-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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 <i>CV</i> (coefficient variability) and average energy value < <i>H</i> > 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.</p>\",\"PeriodicalId\":10500,\"journal\":{\"name\":\"Cognitive Neurodynamics\",\"volume\":\"19 1\",\"pages\":\"75\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12089602/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Neurodynamics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s11571-025-10258-6\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/5/19 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Neurodynamics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s11571-025-10258-6","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/19 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
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.
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.