scholarly journals Stochastic resonance model of synaesthesia

2019 ◽  
Vol 374 (1787) ◽  
pp. 20190029 ◽  
Author(s):  
Poortata Lalwani ◽  
David Brang
Keyword(s):  
Stochastic Resonance ◽  
Cortical Excitability ◽  
Sensory Modality ◽  
Unified Framework ◽  
Resonance Model ◽  
Neural Noise ◽  
Sensory Experiences ◽  
Perceptual Differences ◽  
Broader Phenotype ◽  
Novel Model

In synaesthesia, stimulation of one sensory modality evokes additional experiences in another modality (e.g. sounds evoking colours). Along with these cross-sensory experiences, there are several cognitive and perceptual differences between synaesthetes and non-synaesthetes. For example, synaesthetes demonstrate enhanced imagery, increased cortical excitability and greater perceptual sensitivity in the concurrent modality. Previous models suggest that synaesthesia results from increased connectivity between corresponding sensory regions or disinhibited feedback from higher cortical areas. While these models explain how one sense can evoke qualitative experiences in another, they fail to predict the broader phenotype of differences observed in synaesthetes. Here, we propose a novel model of synaesthesia based on the principles of stochastic resonance. Specifically, we hypothesize that synaesthetes have greater neural noise in sensory regions, which allows pre-existing multisensory pathways to elicit supra-threshold activation (i.e. synaesthetic experiences). The strengths of this model are (a) it predicts the broader cognitive and perceptual differences in synaesthetes, (b) it provides a unified framework linking developmental and induced synaesthesias, and (c) it explains why synaesthetic associations are inconsistent at onset but stabilize over time. We review research consistent with this model and propose future studies to test its limits. This article is part of a discussion meeting issue ‘Bridging senses: novel insights from synaesthesia’.

A novel stochastic resonance model based on bistable stochastic pooling network and its application

2021 ◽  
Vol 145 ◽  
pp. 110800
Author(s):  
Wenyue Zhang ◽  
Peiming Shi ◽  
Mengdi Li ◽  
Dongying Han
Keyword(s):  
Stochastic Resonance ◽  
Resonance Model ◽  
Model Based ◽  
Stochastic Pooling

scholarly journals Actuator Weak Fault Diagnosis in Autonomous Underwater Vehicle Based on Tri-Stable Stochastic Resonance

2020 ◽  
Vol 10 (6) ◽  
pp. 2048 ◽  
Author(s):  
Yang Jiang ◽  
Bo He ◽  
Jia Guo ◽  
Pengfei Lv ◽  
Xiaokai Mu ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Stochastic Resonance ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Ant Colony ◽  
Resonance System ◽  
Resonance Model ◽  
Weak Fault

The autonomous underwater vehicle (AUV) is mainly used in the development and exploration of the ocean. As an important module of the AUV, the actuator plays an important role in the normal execution of the AUV. Therefore, the fault diagnosis of the actuator is particularly important. At present, the research on the strong faults, such as the winding of the actuator, has achieved good results, but the research on the weak fault diagnosis is relatively rare. In this paper, the tri-stable stochastic resonance model is analyzed, and the ant colony tri-stable stochastic resonance model is used to diagnose the weak fault. The system accurately diagnoses the fault of the actuator collision and verifies the adaptive tri-stable stochastic resonance system. This model has better diagnostic results than the bi-stable stochastic resonance system.

A Novel Adaptive Stochastic Resonance Method Based on Tristable System and its Applications

2020 ◽  
pp. 2150004
Author(s):  
Gang Zhang ◽  
Chuan Jiang ◽  
Tian Qi Zhang
Keyword(s):  
Signal Detection ◽  
Stochastic Resonance ◽  
Piecewise Linear ◽  
Correlation Coefficients ◽  
Resonance Method ◽  
Resonance System ◽  
Signal Energy ◽  
Noise Energy ◽  
Novel Model ◽  
Output Snr

Stochastic resonance systems have the advantages of converting noise energy into signal energy, and have great potential in the field of signal detection and extraction. Aiming at the problems of the performance of classical stochastic resonance system whose model is not perfect enough and the correlation coefficients between parameters is too large to be optimized by algorithm, then a novel model of the tristable potential stochastic resonance system is proposed. The output SNR formula of the model is derived and analyzed, and the influence of its parameters on the model is clarified. Compared with the piecewise linear model by numerical simulation, the correctness of the formula and the superiority of the model are verified. Finally, the model and the classical tristable model are applied to bearing fault detection in which the genetic algorithm is used to optimize the parameters of the two systems. The results show that the model has better detection effects, which prove that the model has a strong potential in the field of signal detection.

scholarly journals The Enhancement of Weak Bearing Fault Signatures by Stochastic Resonance with a Novel Potential Function

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6348
Author(s):  
Chao Zhang ◽  
Haoran Duan ◽  
Yu Xue ◽  
Biao Zhang ◽  
Bin Fan ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Stochastic Resonance ◽  
Operating Conditions ◽  
Detection Accuracy ◽  
Wind Turbine Gearbox ◽  
Resonance Model ◽  
Function Type ◽  
Vibration Signals ◽  
Fourier Decomposition ◽  
Bearing Fault

As the critical parts of wind turbines, rolling bearings are prone to faults due to the extreme operating conditions. To avoid the influence of the faults on wind turbine performance and asset damages, many methods have been developed to monitor the health of bearings by accurately analyzing their vibration signals. Stochastic resonance (SR)-based signal enhancement is one of effective methods to extract the characteristic frequencies of weak fault signals. This paper constructs a new SR model, which is established based on the joint properties of both Power Function Type Single-Well and Woods-Saxon (PWS), and used to make fault frequency easy to detect. However, the collected vibration signals usually contain strong noise interference, which leads to poor effect when using the SR analysis method alone. Therefore, this paper combines the Fourier Decomposition Method (FDM) and SR to improve the detection accuracy of bearing fault signals feature. Here, the FDM is an alternative method of empirical mode decomposition (EMD), which is widely used in nonlinear signal analysis to eliminate the interference of low-frequency coupled signals. In this paper, a new stochastic resonance model (PWS) is constructed and combined with FDM to enhance the vibration signals of the input and output shaft of the wind turbine gearbox bearing, make the bearing fault signals can be easily detected. The results show that the combination of the two methods can detect the frequency of a bearing failure, thereby reminding maintenance personnel to urgently develop a maintenance plan.

scholarly journals Making up your mind: Enhanced perceptual decision-making induced by stochastic resonance during non-invasive brain stimulation: Stochastic resonance in perceptual decision-making

2017 ◽  
Author(s):  
Onno van der Groen ◽  
Matthew F. Tang ◽  
Nicole Wenderoth ◽  
Jason B. Mattingley
Keyword(s):  
Decision Making ◽  
Visual Cortex ◽  
Stochastic Resonance ◽  
Decision Process ◽  
Random Noise ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Evidence Accumulation ◽  
Neural Noise ◽  
Stimulation Of

Summary:Perceptual decision-making relies on the gradual accumulation of noisy sensory evidence until a specified boundary is reached and an appropriate response is made. It might be assumed that adding noise to a stimulus, or to the neural systems involved in its processing, would interfere with the decision process. But it has been suggested that adding an optimal amount of noise can, under appropriate conditions, enhance the quality of subthreshold signals in nonlinear systems, a phenomenon known as stochastic resonance. Here we asked whether perceptual decisions obey these stochastic resonance principles by adding noise directly to the visual cortex using transcranial random noise stimulation (tRNS) while participants judged the direction of motion in foveally presented random-dot motion arrays. Consistent with the stochastic resonance account, we found that adding tRNS bilaterally to visual cortex enhanced decision-making when stimuli were just below, but not well below or above, perceptual threshold. We modelled the data under a drift diffusion framework to isolate the specific components of the multi-stage decision process that were influenced by the addition of neural noise. This modelling showed that tRNS increased drift rate, which indexes the rate of evidence accumulation, but had no effect on bound separation or non-decision time. These results were specific to bilateral stimulation of visual cortex; control experiments involving unilateral stimulation of left and right visual areas showed no influence of random noise stimulation. Our study is the first to provide causal evidence that perceptual decision-making is susceptible to a stochastic resonance effect induced by tRNS, and that this effect arises from selective enhancement of the rate of evidence accumulation for sub-threshold sensory events.

scholarly journals Topic Relevance of Public Health Emergencies Influence on Internet Public Opinion Resonance: Simulation Based on Langevin’s Equation

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Quan Cheng ◽  
Yan-gang Zhang ◽  
Yi-quan Li
Keyword(s):  
Public Health ◽  
Public Opinion ◽  
Stochastic Resonance ◽  
Resonance Phenomenon ◽  
The Internet ◽  
Resonance Model ◽  
Mutual Correlation ◽  
The Public ◽  
Public Health Emergencies ◽  
Topic Relevance

Public health emergencies occurred frequently, which usually result in the negative Internet public opinion events. In the complex network information ecological environment, multiple public opinion events may be aggregated to generate public opinion resonance due to the topic category, the mutual correlation of the subject involved, and the compound accumulation of specific emotions. In order to reveal the phenomenon and regulations of the public opinion resonance, we firstly analyze the influence factors of the Internet public opinion events in the public health emergencies. Then, based on Langevin’s equation, we propose the Internet public opinion stochastic resonance model considering the topic relevance. Furthermore, three exact public health emergencies in China are provided to reveal the regulations of evoked events “revival” caused by original events. We observe that the Langevin stochastic resonance model considering topic relevance can effectively reveal the resonance phenomenon of Internet public opinion caused by public health emergencies. For the original model without considering the topic relevance, the new model is more sensitive. Meanwhile, it is found that the degree of topic relevance between public health emergencies has a significant positive correlation with the intensity of Internet public opinion resonance.

scholarly journals The Stochastic Resonance model of auditory perception: A unified explanation of tinnitus development, Zwicker tone illusion, and residual inhibition

2020 ◽  
Author(s):  
Achim Schilling ◽  
Konstantin Tziridis ◽  
Holger Schulze ◽  
Patrick Krauss
Keyword(s):  
Information Transmission ◽  
Stochastic Resonance ◽  
Auditory System ◽  
Auditory Perception ◽  
Acoustic Noise ◽  
Dorsal Cochlear Nucleus ◽  
Auditory Input ◽  
Resonance Model ◽  
Zwicker Tone ◽  
Residual Inhibition

AbstractStochastic Resonance (SR) has been proposed to play a major role in auditory perception, and to maintain optimal information transmission from the cochlea to the auditory system. By this, the auditory system could adapt to changes of the auditory input at second or even sub-second timescales. In case of reduced auditory input, somatosensory projections to the dorsal cochlear nucleus would be disinhibited in order to improve hearing thresholds by means of SR. As a side effect, the increased somatosensory input corresponding to the observed tinnitus-associated neuronal hyperactivity is then perceived as tinnitus. In addition, the model can also explain transient phantom tone perceptions occurring after ear plugging, or the Zwicker tone illusion. Vice versa, the model predicts that via stimulation with acoustic noise, SR would not be needed to optimize information transmission, and hence somatosensory noise would be tuned down, resulting in a transient vanishing of tinnitus, an effect referred to as residual inhibition.

Sign in / Sign up

Export Citation Format

Share Document