A review of methods for identifying stochastic resonance in simulations of single neuron models

The fast bearing diagnosis based on adaptive GSR of fault feature amplification in scale-transformed fractional oscillator

From the noise-assisted perspective of stochastic resonance (SR), fractional system has been adopted to enhance the diagnostic performance of mechanical faults by utilizing the previous state information in mechanical degradation process, but the computation is extremely time-consuming. To address this challenge, we develop a fast diagnosis method leveraging the mechanism of generalized SR (GSR)-based active energy conversion in fluctuating-damping fractional oscillator (FDFO). Through the analysis of system stationary response, we propose a theoretical index known as fault feature amplification (FFA), which effectively replaces the time-consuming numerical solution in multi-parameter optimization, leading to a remarkable reduction in the time complexity of the adaptive diagnosis algorithm. This improvement brings about significant benefits, notably simplifying the diagnosis flow. Based on the results of performance evaluation in diagnosing simulated bearing signals, the proposed method exhibits a comprehensive superiority in identifying ability and diagnosis efficiency. Finally, this method has been further validated in experimental diagnosis, especially for some challenging cases, providing strong support for engineering applications, particularly in the fast diagnosis of complex operating environments.

A novel memristive neuron model and its energy characteristics

The functional neurons are basic building blocks of the nervous system and are responsible for transmitting information between different parts of the body. However, it is less known about the interaction between the neuron and the field. In this work, we propose a novel functional neuron by introducing a flux-controlled memristor into the FitzHugh-Nagumo neuron model, and the field effect is estimated by the memristor. We investigate the dynamics and energy characteristics of the neuron, and the stochastic resonance is also considered by applying the additive Gaussian noise. The intrinsic energy of the neuron is enlarged after introducing the memristor. Moreover, the energy of the periodic oscillation is larger than that of the adjacent chaotic oscillation with the changing of memristor-related parameters, and same results is obtained by varying stimuli-related parameters. In addition, the energy is proved to be another effective method to estimate stochastic resonance and inverse stochastic resonance. Furthermore, the analog implementation is achieved for the physical realization of the neuron. These results shed lights on the understanding of the firing mechanism for neurons detecting electromagnetic field.

Stochastic resonance and 'gamma band' synchronization in the human visual system

Cortical synchronization in the gamma-frequency range (above ~30.0 Hz) and the signal/noise interplay described by stochastic resonance models have been proposed as basic mechanisms in neuronal synchronization and sensory information processing, particularly in vision. Here we report an observation in humans of linear and inverted-U distributions of the electrophysiological (EEG) responses to visual contrast stimulation in the gamma band and in the low frequency components of the visual evoked responses (VER), respectively. The combination of linear and inverted-U distributions is described by a stochastic resonance model (SR). The observation needs replication in larger subjects' samples. It nevertheless adds to the available evidence of a role of gamma oscillatory signals and SR mechanisms in neuronal synchronization and visual processing. Some functional adaptation in human vision appears conceivable and further investigation is warranted.

Noise induced quiescence of epileptic spike generation in patients with epilepsy

Clinical scalp electroencephalographic recordings from patients with epilepsy are distinguished by the presence of epileptic discharges i.e. spikes or sharp waves. These often occur randomly on a background of fluctuating potentials. The spike rate varies between different brain states (sleep and awake) and patients. Epileptogenic tissue and regions near these often show increased spike rates in comparison to other cortical regions. Several studies have shown a relation between spike rate and background activity although the underlying reason for this is still poorly understood. Both these processes, spike occurrence and background activity show evidence of being at least partly stochastic processes. In this study we show that epileptic discharges seen on scalp electroencephalographic recordings and background activity are driven at least partly by a common biological noise. Furthermore, our results indicate noise induced quiescence of spike generation which, in analogy with computational models of spiking, indicate spikes to be generated by transitions between semi-stable states of the brain, similar to the generation of epileptic seizure activity. The deepened physiological understanding of spike generation in epilepsy that this study provides could be useful in the electrophysiological assessment of different therapies for epilepsy including the effect of different drugs or electrical stimulation.

Coherence resonance for neuronal bursting with spike undershoot

Although the bursting patterns with spike undershoot are involved with the achievement of physiological or cognitive functions of brain with synaptic noise, noise induced-coherence resonance (CR) from resting state or subthreshold oscillations instead of bursting has been widely identified to play positive roles in information process. Instead, in the present paper, CR characterized by the increase firstly and then decease of peak value of power spectrum of spike trains is evoked from a bursting pattern with spike undershoot, which means that the minimal membrane potential within burst is lower than that of the subthreshold oscillations between bursts, while CR cannot be evoked from the bursting pattern without spike undershoot. With bifurcations and fast-slow variable dissection method, the bursting patterns with and without spike undershoot are classified into "Sub-Hopf/Fold" bursting and "Fold/Homoclinic" bursting, respectively. For the bursting with spike undershoot, the trajectory of the subthreshold oscillations is very close to that of the spikes within burst. Therefore, noise can induce more spikes from the subthreshold oscillations and modulate the bursting regularity, which leads to the appearance of CR. For the bursting pattern without spike undershoot, the trajectory of the quiescent state is not close to that of the spikes within burst, and noise cannot induce spikes from the quiescent state between bursts, which is cause for non-CR. The result provides a novel case of CR phenomenon and extends the scopes of CR concept, presents that noise can enhance rather than suppress information of the bursting patterns with spike undershoot, which are helpful for understanding the dynamics and the potential physiological or cognitive functions of the nerve fiber or brain neurons with such bursting patterns.

Noisy Light Augments the Na+ Current in Somatosensory Pyramidal Neurons of Optogenetic Transgenic Mice

In previous reports, we developed a method to apply Brownian optogenetic noise-photostimulation (BONP, 470 nm) up to 0.67 mW on the barrel cortex of in vivo ChR2 transgenic mice. In such studies, we found that the BONP produces an increase in the evoked field potentials and the neuronal responses of pyramidal neurons induced by somatosensory mechanical stimulation. Here we extended such findings by examining whether the same type of BONP augments the Na⁺ current amplitude elicited by voltage-clamp ramps of dissociated pyramidal neurons from the somatosensory cortex of ChR2 transgenic and wild type mice. We found that in all neurons from the ChR2 transgenic mice, but none of the wild type mice, the peak amplitude of a TTX-sensitive Na⁺ current and its inverse of latency exhibited inverted U-like graphs as a function of the BONP level. It means that an intermediate level of BONP increases both the peak amplitude of the Na⁺ current and its inverse of latency. Our research suggests that the impact of BONP on the Na⁺ channels of pyramidal neurons could be associated with the observed augmentation-effects in our previous in vivo preparation. Moreover, it provides caution information for the use of an appropriate range of light intensity, <0.67 mW, which could avoid opto non-genetics (also termed “optonongenetic”) related responses due to light-induced temperature changes.

Adaptive monostable stochastic resonance for processing UV absorption spectrum of nitric oxide

When ultraviolet (UV) absorption spectroscopy technology is used for nitric oxide (NO) detection, the background noise will directly affect the accuracy of concentration inversion, especially in low concentrations. Traditional processing methods attempt to eliminate background noise, which damages the absorption spectrum characteristics. However, stochastic resonance (SR) can utilize the noise to extract a weak characteristic signal. This paper reports a monostable stochastic resonance (MSR) model for processing an UV NO absorption spectrum. By analyzing the characteristics of UV absorption spectrum of NO, the evaluation indexes were constructed, thereby an adaptive MSR method was designed for parameter optimization. The numerical simulation confirmed the absorbance peak can be amplified and spectral signal-to-noise ratio (SNR) can be in the stable range of the proposed method, when noise intensity increased. Finally, this experiment obtained a NO detection limit (3σ) of 1.456 ppm and the maximum relative deviation of concentration is 6.32% by this proposed method, which is satisfactory for processing of the UV NO absorption spectrum.

Modeling electrical stimulation of retinal ganglion cell with optimizing additive noises for reducing threshold and energy consumption

BACKGROUND

Epiretinal prosthesis is one device for the treatment of blindness, which target retinal ganglion cells (RGCs) by electrodes on retinal surface. The stimulating current of epiretinal prosthesis is an important factor that influences the safety threshold and visual perception. Stochastic resonance (SR) can be used to enhance the detection and transmission of subthreshold stimuli in neurons. Here, it was assumed that SR was a potential way to improve the performance of epiretinal prosthesis. The effect of noises on the response of RGCs to electrical stimulation and the energy of stimulating current was studied based on a RGC model.

METHODS

The RGC was modeled as a multi-compartment model consisting of dendrites and its branches, soma and axon. To evoke SR, a subthreshold signal, a series of bipolar rectangular pulse sequences, plus stochastic biphasic pulse sequences as noises, were used as a stimulus to the model. The SR-type behavior in the model was characterized by a "power norm" measure. To decrease energy consumption of the stimulation waveform, the stochastic biphasic pulse sequences were only added to the cathode and anode phase of the subthreshold pulse and the noise parameters were optimized by using a genetic algorithm (GA).

RESULTS

When certain intensity of noise is added to the subthreshold signal, RGC model can fire. With the noise's RMS amplitudes increased, more spikes were elicited and the curve of power norm presents the inverted U-like graph. The larger pulse width of stochastic biphasic pulse sequences resulted in higher power norm. The energy consumption and charges of the single bipolar rectangular pulse without noise in threshold level are 468.18 pJ, 15.30 nC, and after adding optimized parameters's noise to the subthreshold signal, they became 314.8174 pJ, 11.9281 nC and were reduced by 32.8 and 22.0%, respectively.

CONCLUSIONS

The SR exists in the RGC model and can enhance the representation of RGC model to the subthreshold signal. Adding the stochastic biphasic pulse sequences to the cathode and anode phase of the subthreshold signal helps to reduce stimulation threshold, energy consumption and charge of RGC stimulation. These may be helpful for improving the performance of epiretinal prosthesis.

Emergence of spike correlations in periodically forced excitable systems

In sensory neurons the presence of noise can facilitate the detection of weak information-carrying signals, which are encoded and transmitted via correlated sequences of spikes. Here we investigate the relative temporal order in spike sequences induced by a subthreshold periodic input in the presence of white Gaussian noise. To simulate the spikes, we use the FitzHugh-Nagumo model and to investigate the output sequence of interspike intervals (ISIs), we use the symbolic method of ordinal analysis. We find different types of relative temporal order in the form of preferred ordinal patterns that depend on both the strength of the noise and the period of the input signal. We also demonstrate a resonancelike behavior, as certain periods and noise levels enhance temporal ordering in the ISI sequence, maximizing the probability of the preferred patterns. Our findings could be relevant for understanding the mechanisms underlying temporal coding, by which single sensory neurons represent in spike sequences the information about weak periodic stimuli.

Stochastic resonance in the synaptic transmission between hair cells and vestibular primary afferents in development

The stochastic resonance (SR) is a phenomenon of nonlinear systems in which the addition of an intermediate level of noise improves the response of such system. Although SR has been studied in isolated hair cells and in the bullfrog sacculus, the occurrence of this phenomenon in the vestibular system in development is unknown. The purpose of the present study was to explore for the existence of SR via natural mechanical-stimulation in the hair cell-vestibular primary afferent transmission. In vitro experiments were performed on the posterior semicircular canal of the chicken inner ear during development. Our experiments showed that the signal-to-noise ratio of the afferent multiunit activity from E15 to P5 stages of development exhibited the SR phenomenon, which was characterized by an inverted U-like response as a function of the input noise level. The inverted U-like graphs of SR acquired their higher amplitude after the post-hatching stage of development. Blockage of the synaptic transmission with selective antagonists of the NMDA and AMPA/Kainate receptors abolished the SR of the afferent multiunit activity. Furthermore, computer simulations on a model of the hair cell - primary afferent synapse qualitatively reproduced this SR behavior and provided a possible explanation of how and where the SR could occur. These results demonstrate that a particular level of mechanical noise on the semicircular canals can improve the performance of the vestibular system in their peripheral sensory processing even during embryonic stages of development.