Effects of magnetic fields on stochastic resonance in Hodgkin-Huxley neuronal network driven by Gaussian noise and non-Gaussian noise

Yang, Huilan; Xu, Guizhi; Wang, Hongbin

doi:10.1007/s11571-021-09734-6

Cited by 8 publications

(5 citation statements)

References 42 publications

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“…In this case, ISF loses bulk fluidity [71] and the diffusion of water, ions, and molecules decreases by a factor of 3-5 compared to diffusion in free water [73,74]. The structure and dynamics of ISF, by blocking the leakage of Ca 2+ and neurotransmitters from synapse clefts [74], contributes to the propagation of white noise in resonant mechanisms of information transmission and detection in neural networks [28,44,[75][76][77][78][79].…”

Section: Electrophysics Of the Parenchyma Of The Cortexmentioning

confidence: 99%

Connection of brain glymphatic system with circadian rhythm

Kholmanskiy

2023

Preprint

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To establish the relationship between the glymphatic system of the brain and the circadian rhythm, we analyzed the effect of anomalies in water thermodynamics on the dependence of the dynamic, electrical, and optical characteristics of physiological fluids on temperature. The dynamics of hydrogen bonds in bulk and hydrated water affected the activation energies of ion currents of voltage-dependent channels that regulate signaling and trophic bonds in the neuropil of the cortical parenchyma. The physics of minimizing the of the isobaric heat capacity of water made it possible to explain the stabilization and functional optimization of the thermodynamics of eyeball fluids at 34.5 C and the human brain during sleep at 36.5 C. At these temperatures, the thermoreceptors of the cornea and the cells of the ganglionic layer of the retina, through connections with the suprachiasmatic nucleus and the pineal gland, switch the circadian rhythm from daytime to nighttime. The phylogenesis of the circadian rhythm was reflected in the dependence of the duration of the nighttime sleep of mammals on the diameter of the eyeball and the mass of the pineal gland. The activity of all the nerves of the eyeball led to the division of the nocturnal brain metabolism into NREM and REM phases. These phases correspond to two modes of the glymphatic system - electrochemical and dynamic. The first is responsible for the relaxation processes of synaptic plasticity and chemical neutralization of toxins with the participation of water and melatonin. Rapid eye movement and an increase in cerebral blood flow in the second mode increase water exchange in the parenchyma and flush out toxins into the venous system. Electrophysics of clearance and conductivity of ionic and water channels of membranes of blood vessels and astrocytes modulate oscillations of polarization potentials of water dipole domains in parietal plasma layers of arterioles and capillaries.

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Section: Electrophysics Of the Parenchyma Of The Cortexmentioning

confidence: 99%

Connection of brain glymphatic system with circadian rhythm

Kholmanskiy

2023

Preprint

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“…It is widely acknowledged that there are several traditional indicators, such as the signal-to-noise ratio (SNR) 30 , spectral power amplification 31 , Fourier coefficients 32 , and others 33 , which are employed to measure SR in neural networks. These indicators assist in the detection of weak signals and enhance our understanding of information transmission.…”

Section: Introductionmentioning

confidence: 99%

Detecting stochastic multiresonance in neural networks via statistical complexity measure

Wu,

Sun

2024

Sci Rep

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This paper employs statistical complexity measure (SCM) to investigate the occurrence of stochastic multiresonance (SMR) induced by noise and time delay in small-world neural networks coupled with FitzHugh-Nagumo (FHN) neurons. Our findings reveal that SCM exhibits four local maxima at four optimal noise levels, providing evidence for the occurrence of quadruple stochastic resonances. When time delay $$\tau$$ τ is taken into account in the information transmission, under moderate noise levels, SCM shows several local maxima when $$\tau = nT_{e}$$ τ = n T e with $$n$$ n being a positive integer and $$T_{e}$$ T e being the period of subthreshold signal. This indicates the appearance of delay-induced SMR at the multiples of the period of subthreshold signal. Intriguingly, at low noise levels, a strong coherence between time delay and neuronal firing dynamics emerges at $$\tau = nT_{e} - 2$$ τ = n T e - 2 , as confirmed by a series of SCM maxima at these time delays. Furthermore, the study demonstrates that by adjusting the degrees and sizes of small-world networks, as well as the coupling strength, it is possible to optimize the strength of delay-induced SMR, thus maximizing the detection capability of subthreshold signal. The research results may provide us with an effective approach for understanding the role of time delay in signal detection and information transmission.

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“…If there is no contribution, how to explain the negative power component of neurons (Wang et al 2015a; , and how to explain the equivalence between Wang-Zhang's (W-Z) neuron model and Hodgkin-Huxley's (H-H) model . A further question is whether neurons in the brain, or even without synaptic connections and nerve fiber connections between brain regions, can still transmit neural signals in the case of electromagnetic field coupling to achieve communication between neurons and various brain regions (Yang et al 2022;Ma and Tang 2017).…”

Section: Introductionmentioning

confidence: 99%

Brain works principle followed by neural information processing: a review of novel brain theory

Wang

et al. 2023

Artif Intell Rev

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The way the brain work and its principle of work has long been a big scientific question that scientists have dreamed of solving. However, as is known to all, the brain works at different levels, and the operation at different levels is interactional and mutually coupled. Unfortunately, until now, we still do not know how the nervous system at different levels is interacting and coupling with each other. This review provides some preliminary discussions on how to address these scientific questions, for which we propose a novel theory of the brain called neural energy. Such a theoretical and research approach can couple neural information with neural energy to address the interactions of the nervous system at various levels. Therefore, this review systematically summarizes the neural energy theories and methods proposed by our research in the field of brain science, as well as the internal relationship between mechanics and neural energy theory. Focuses on how to construct a Wang–Zhang (W–Z) neuron model equivalent to Hodgkin–Huxley (H–H) model by using the idea of analytical dynamics. Then, based on this model, we proposed a large-scale neural model and a theoretical framework of global neural coding of the brain in the field of neuroscience. It includes information processing of multiple sensory and perceptual nervous systems such as visual perception, neural mechanism of coupling between default mode network and functional network of brain, memory switching and brain state switching, brain navigation, prediction of new working mechanism of neurons, and interpretation of experimental phenomena that are difficult to be explained by neuroscience. It is proved that the new W–Z neuron model and neural energy theory have unique functions and advantages in neural modeling, neural information processing and methodology. The idea of large-scale neuroscience research with neural energy as the core will provide a potentially powerful research method for promoting the fusion of experimental neuroscience and theoretical neuroscience in the future, and propose a widely accepted brain theory system between experimental neuroscience and theoretical neuroscience. It is of great scientific significance to abandon the shortcomings of reductive and holism research methods in the field of neuroscience, and effectively integrate their respective advantages in methodology.

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Effects of magnetic fields on stochastic resonance in Hodgkin-Huxley neuronal network driven by Gaussian noise and non-Gaussian noise

Cited by 8 publications

References 42 publications

Connection of brain glymphatic system with circadian rhythm

Connection of brain glymphatic system with circadian rhythm

Detecting stochastic multiresonance in neural networks via statistical complexity measure

Brain works principle followed by neural information processing: a review of novel brain theory

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