Reliability of weak signals detection in neurons with noise

Chen, Yueling; Yu, Lu; Chen, Yong

doi:10.1007/s11431-015-6000-3

Cited by 15 publications

(3 citation statements)

References 52 publications

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“…As a result, bifurcation parameters and noise are changed to detect mode transition in electrical activities. On the other hand, stochastic resonance, coherence resonance, synchronization between neurons and neuronal networks have been investigated extensively 8 9 10 11 12 13 14 15 16 17 18 . It is believed that synapse 19 is important to bridge the neurons for signal exchange and communication.…”

mentioning

confidence: 99%

Autaptic regulation of electrical activities in neuron under electromagnetic induction

Huang

Jia

et al. 2017

Sci Rep

128

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Realistic neurons may hold complex anatomical structure, for example, autapse connection to some internuncial neurons, which this specific synapse can connect to its body via a close loop. Continuous exchanges of charged ions across the membrane can induce complex distribution fluctuation of intracellular and extracellular charged ions of cell, and a time-varying electromagnetic field is set to modulate the membrane potential of neuron. In this paper, an autapse-modulated neuron model is presented and the effect of electromagnetic induction is considered by using magnetic flux. Bifurcation analysis and sampled time series for membrane potentials are calculated to investigate the mode transition in electrical activities and the biological function of autapse connection is discussed. Furthermore, the Gaussian white noise and electromagnetic radiation are considered on the improved neuron model, it is found appropriate setting and selection for feedback gain and time delay in autapse can suppress the bursting in neuronal behaviors. It indicates the formation of autapse can enhance the self-adaption of neuron so that appropriate response to external forcing can be selected, this biological function is helpful for encoding and signal propagation of neurons. It can be useful for investigation about collective behaviors in neuronal networks exposed to electromagnetic radiation.

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mentioning

confidence: 99%

Autaptic regulation of electrical activities in neuron under electromagnetic induction

Huang

Jia

et al. 2017

Sci Rep

128

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“…The Hamilton energy balance based on Helmholtz's theorem by Leutcho in [25] explains the dependence of the initial conditions on the macrostability mechanism and shows how the isosurface with constant Hamiltonian energy is strongly dependent on the state variable. In the presence of noise interference [26,27], most neurons can be tamed in the form of external periodic currents to form regular discharge patterns and high neural activity regularity [28]. In the absence of periodic stimulation, a certain intensity of noise can also effectively induce nonlinear resonance [29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Response mechanism of heat-sensitive neurons under combined noise stimulation

Wang,

Huang,

Zhu

et al. 2024

Preprint

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Patients born with congenital analgesia have no ability to sense temperature, who generally have bleak chances of survival. However, the relevant pathological mechanism remains unclear. To explore how the body's heat-sensitive neurons change in response to external stimuli, based on a heat-sensitive neuron model developed from the piezoelectric neural circuit, we designed two different stimuli combined Gaussian white noise to each stimulus, triggering different firing modes (r1, r2, r3). The Hamilton energy corresponding to each emission mode is calculated to identify the contribution of the external stimulus, and further, a correlation function is defined to identify the influence of external stimuli on the firing mode selection of neurons. Simulation results revealed that the neuronal response to the external stimulus that induces the spike discharge is preferentially compared to the external stimulus that induces the r-clonic pattern. The changes in the contour of the periodic attractor confirmed that external stimuli inducing spike-and-wave and r-clonic patterns could be sensitively perceived. For external stimuli, the chaotic emission pattern caused by the Chua circuit stimulus, the contribution of spikes, r-clonic and even periodic stimuli can be detected because the contour of the chaotic attractor also changes greatly. Moreover, the neurons are more sensitive to external stimuli, which can cause a greater release of Hamilton energy and a higher level of regularity in neural activity. This study revealed the potential response mechanism of thermosensitive neurons under combined noise stimulation.

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“…Generally speaking, as a kind of system interference factor, noise breaks the original stability of the system, thus bringing adverse and harmful effects to the system. However, studies at home and abroad show that the introduction of noise in nonlinear systems improves the information processing ability of the nervous system and makes the system more stable [8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Coherence Resonance Behavior of FitzHugh‐Nagumo Neurons Induced by Electromagnetic Field Driven by Phase Noise

Zheng

2022

Discrete Dynamics in Nature and Society

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Noise exists widely in the nervous system, and plays a crucial role in the nervous system information processing. Noise can not only enhance but also weaken the ability of the nervous system to process information. Neurons are in a complex and variable electromagnetic field. Electromagnetic induction plays an important role in regulating the changes of neuronal membrane potential. Therefore, this paper simulates the electromagnetic field environment of the nervous system with a memristor and analyses the rich coherence resonance behavior of FitzHugh-Nagumo (FHN) neuron system under the drive of phase noise. By taking the amplitude, period and noise intensity of phase noise as the main parameters and the parameters of memristor as auxiliary parameters, the two-parameter changes are made from the angle of the amplitude and period of phase noise, the amplitude and intensity of phase noise, and the noise intensity and period of phase noise, respectively. The dynamic behaviors of coherent resonance of FHN neuron system are analyzed from the amplitude and period, amplitude and intensity as well as intensity and period of phase noise, respectively. When the amplitude and period of the phase noise and the intensity and period of the phase noise are used as independent variables for the two-parameter analysis, the FHN neuron system shows rich dynamic behaviors such as coherence mono-resonance, coherence bi-resonance and coherence multi-resonance. Especially when the amplitude and period of phase noise change as two-parameter, the system presents a coherence resonance of discharge pattern with period-adding cluster discharge at the valley. When the amplitude and intensity of phase noise are taken as independent variables for two-parameter analysis, FHN neuronal system presents single or dual coherence resonance at any value of noise intensity with the change of phase noise amplitude. The simulated results show that the FHN neuron system demonstrates rich coherence resonance behaviors under the drive of phase noise when the effect of electromagnetic induction in the nervous system is simulated by memristor.

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Reliability of weak signals detection in neurons with noise

Cited by 15 publications

References 52 publications

Autaptic regulation of electrical activities in neuron under electromagnetic induction

Autaptic regulation of electrical activities in neuron under electromagnetic induction

Response mechanism of heat-sensitive neurons under combined noise stimulation

Coherence Resonance Behavior of FitzHugh‐Nagumo Neurons Induced by Electromagnetic Field Driven by Phase Noise

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