Astrocytic modulation on neuronal electric mode selection induced by magnetic field effect

Yuan, Zhixuan; Feng, Peihua; Fan, Yongchen; Yu, Yangyang; Wu, Ying

doi:10.1007/s11571-021-09709-7

Cited by 7 publications

(4 citation statements)

References 31 publications

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“…Only the neural energy theory is possible to study interactions among the microscopic, mesoscopic and macroscopic neural activities in a theoretical system from the perspective of global neural coding. Therefore, it is able to draw out the global information of how the brain works through comprehensive research and comparison of experimental data obtained at various levels (Wouapi et al 2021;Navarro-López et al 2021;Churchland et al 2002Churchland et al , 2012Tsuda et al 1987Tsuda et al , 2004Tsuda 1991Tsuda , 1992Tsuda , 1984Tsuda , 2001Tsuda , 2013Tsuda , 2015Ebrahimzadeh et al 2021;Yang et al 2021a Yang et al , b, 2022Jiang et al 2020;Sharma and Acharya 2021;Wang et al , 2008Wang et al , 2009Wang et al , 2015a Wang et al , b, 2017a Wang et al , b, 2018a Wang et al , b, 2019b Wang et al , c, 2020Wang et al , 2021aClancy et al 2017;Videbech 2010;Zhang et al 2019Zhang et al , 2020Yuan et al 2022Yuan et al , 2021Yao and Wang 2019;Maltba et al 2022;Zhou et al 2020Zhou et al , 2007Li et al 2020Li et al , 2022aKim and Lim 2020;Pfaff and Volkow 2022;Tsukada et al 1975Tsukada et al , 2015Kaneko and Tsuda 2001;…”

Section: Conclusion Remarksmentioning

confidence: 99%

“…Although theoretical neuroscience was born 20 years ago, it is not widely accepted by the academic community to have only one theory. Although theoretical neuroscientists have made a series of excellent research achievements today (Wouapi et al 2021;Wang et al , 2021aClancy et al 2017;Videbech 2010;Zhang et al 2019Zhang et al , 2020Yuan et al 2021Yuan et al , 2022Yao and Wang 2019;Maltba et al 2022;Zhou et al 2020;Li et al 2020;Kim and Lim 2020;Yang et al 2021b), it is still difficult to widely and effectively cooperate with experimental neuroscientists to promote each other and integrate development. One of the efforts for the integration of development has been performed is to publish a textbook of comprehensive neuroscience such as "Neuroscience in the 21st Century", 3rd Edition (Pfaff and Volkow 2022).…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Conclusion Remarksmentioning

confidence: 99%

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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“…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. Therefore, electromagnetic induction effect becomes non-ignorable and memristive term is often used to describe the equivalent induction current [11][12][13][14][15], which controls the membrane potential and energy values (and energy level) effectively. For example, Xu et al [16] claimed that most of the neurons have four main firing modes and their average energy values present four distinct levels, and a shift of energy level is accompanied with mode transition.…”

Section: Introductionmentioning

confidence: 99%

Dynamics in a light-sensitive neuron with two capacitive variables

Wang,

Lv,

Zhang

et al. 2024

Phys. Scr.

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Involvement of two capacitive variables into neuron models provides better description of the cell membrane property and then the diversity effect of electromagnetic field inner and outer of the cell membrane can be estimated in clear way. Specific electric components can be combined to build equivalent neural circuits for reproducing similar neural activities under some self-adaptive control schemes. A phototube converts external light into electric stimuli and the injected energy is encoded to excite the cell membranes for presenting suitable firing patterns. Two capacitors are connected via a linear resistor for mimicking the energy exchange and changes of membrane potentials. Combination of memristor into an additive branch circuit of the neural circuit can estimate the effect of electromagnetic induction and energy absorption. The energy function H for this light-sensitive and memristive neuron is calculated in theoretical way, and the average energy function <H> can predict the occurrence of stochastic resonance, which can be confirmed by estimating the distribution of signal to noise ratios. The firing mode is relative to the energy value of the neuron, and a control law is suggested to control the mode transition in neural activities in an adaptive way.

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“…In the literature, flux-controlled memristors were used in various neuron models to depict the dynamic relation between the membrane potential and magnetic flux [21]. In other words, the flux-controlled memristors were used in the Hodgkin-Huxley neuron model [22][23][24], Izhikevich neuron model [25], FitzHugh-Nagumo neuron model [26], and threedimensional (3D) [27][28][29][30][31]/two dimensional (2D) [32][33][34] Hindmarsh-Rose neuron model to depict the electromagnetic induction effect. These memristive neuron models can generate abundant firing patterns since the involvement of the flux-controlled memristor.…”

Section: Introductionmentioning

confidence: 99%

Hidden firing patterns and memristor initial condition-offset boosting behavior in a memristive Hindmarsh-Rose neuron model

et al. 2023

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Electromagnetic induction can effectively induce abundant firing patterns in neurons. In modeling a neuron model with the electromagnetic induction effect, an electromagnetic induction current is frequently added to the state equation of membrane potential. To more properly reflect the non-uniform distribution of the ions inside and outside the neuron membrane, an ideal flux-controlled memristor with sinusoidal memductance function and non-linearly modulated input is raised to depict an electromagnetic induction effect on a Hindmarsh–Rose neuron model, and thereby, a three-dimensional (3D) memristive Hindmarsh–Rose (mHR) neuron model is built in this paper. The proposed mHR neuron model possesses no equilibrium point since the involvement of the ideal flux-controlled memristor, which induces the generation of hidden dynamics. Numerical results declare that the mHR neuron model can generate abundant hidden dynamics, i.e., periodic spiking, chaotic spiking, period-doubling bifurcation route, tangent bifurcation, and chaos crisis. These hidden dynamics are much related to the memristor coupling strength and externally applied stimulus. Afterward, the memristor initial condition-offset boosting behavior is revealed. This can trigger the generation of infinite multiple coexisting firing patterns along the memristor variable coordinate. These coexisting firing patterns have identical attractor topology but different locations in the phase plane. Finally, an analog circuit is designed for implementing the mHR neuron model, and PSIM-based circuit simulation is executed. The circuit-simulated results perfectly verify the generation of hidden infinite multiple coexisting initial condition-offset boosting firing patterns in the proposed mHR neuron model.

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Astrocytic modulation on neuronal electric mode selection induced by magnetic field effect

Cited by 7 publications

References 31 publications

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

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

Dynamics in a light-sensitive neuron with two capacitive variables

Hidden firing patterns and memristor initial condition-offset boosting behavior in a memristive Hindmarsh-Rose neuron model

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