scholarly journals Control of noise-induced coherent oscillations in three-neuron motifs

2021 ◽  
Author(s):  
Florian Bönsel ◽  
Patrick Krauss ◽  
Claus Metzner ◽  
Marius E. Yamakou
Keyword(s):  
Stochastic Resonance ◽  
Scaling Limit ◽  
Single Neurons ◽  
Excitable System ◽  
Degree Of Coherence ◽  
Chemical Synapses

AbstractThe phenomenon of self-induced stochastic resonance (SISR) requires a nontrivial scaling limit between the deterministic and the stochastic timescales of an excitable system, leading to the emergence of coherent oscillations which are absent without noise. In this paper, we numerically investigate SISR and its control in single neurons and three-neuron motifs made up of the Morris–Lecar model. In single neurons, we compare the effects of electrical and chemical autapses on the degree of coherence of the oscillations due to SISR. In the motifs, we compare the effects of altering the synaptic time-delayed couplings and the topologies on the degree of SISR. Finally, we provide two enhancement strategies for a particularly poor degree of SISR in motifs with chemical synapses: (1) we show that a poor SISR can be significantly enhanced by attaching an electrical or an excitatory chemical autapse on one of the neurons, and (2) we show that by multiplexing the motif with a poor SISR to another motif (with a high SISR in isolation), the degree of SISR in the former motif can be significantly enhanced. We show that the efficiency of these enhancement strategies depends on the topology of the motifs and the nature of synaptic time-delayed couplings mediating the multiplexing connections.

Stochastic resonance in small-world neuronal networks with hybrid electrical–chemical synapses

2014 ◽  
Vol 60 ◽  
pp. 40-48 ◽  
Author(s):  
Jiang Wang ◽  
Xinmeng Guo ◽  
Haitao Yu ◽  
Chen Liu ◽  
Bin Deng ◽  
...  
Keyword(s):  
Stochastic Resonance ◽  
Neuronal Networks ◽  
Small World ◽  
Chemical Synapses

STOCHASTIC RESONANCE IN BISTABLE AND EXCITABLE SYSTEMS: EFFECT OF NON-GAUSSIAN NOISES

2003 ◽  
Vol 03 (04) ◽  
pp. L365-L371 ◽  
Author(s):  
M. A. FUENTES ◽  
C. J. TESSONE ◽  
H. S. WIO ◽  
R. TORAL
Keyword(s):  
Stochastic Resonance ◽  
Gaussian Noise ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Excitable System ◽  
Ratio Curve ◽  
Bistable Systems ◽  
Excitable Systems ◽  
Noise Ratio ◽  
Non Gaussian

We analyze stochastic resonance in systems driven by non-Gaussian noises. For the bistable double well we compare the signal-to-noise ratio resulting from numerical simulations with some quasi-analytical results predicted by a consistent Markovian approximation in the case of a colored non-Gaussian noise. We also study the FitzHugh–Nagumo excitable system in the presence of the same noise. In both systems, we find that, as the noise departs from Gaussian behavior, there is a regime (different for the excitable and the bistable systems) in which there is a notable robustness against noise tuning since the signal-to-noise ratio curve broadens and becomes less sensitive to the actual value of the noise intensity. We also compare our results with some experiments in sensory systems.

scholarly journals Lévy Noise-induced Self-induced Stochastic Resonance in a Memristive Neuron

2021 ◽  
Author(s):  
Marius E. Yamakou ◽  
Tat Dat Tran
Keyword(s):  
Magnetic Flux ◽  
Stochastic Resonance ◽  
Gaussian White Noise ◽  
Scaling Limit ◽  
Lévy Noise ◽  
Feedback Gain ◽  
Neuromorphic Circuits ◽  
Gain Parameter ◽  
The Mean ◽  
Levy Noise

Abstract Self-induced stochastic resonance (SISR) is a subtle resonance mechanism requiring a nontrivial scaling limit between the stochastic and the deterministic timescales of an excitable system, leading to the emergence of a limit cycle behavior which is absent without noise. All previous studies on SISR in neural systems have only considered the idealized Gaussian white noise. Moreover, these studies have ignored one electrophysiological aspect of the nerve cell: its memristive properties. In this paper, first, we show that in the excitable regime, the asymptotic matching of the mean escape timescale of an α-stable Lévy process (with value increasing as a power σ-α of the noise amplitude σ, unlike the mean escape timescale of a Gaussian process with the value increasing as in Kramers' law) and the deterministic timescale (controlled by the singular parameter) can also induce a strong SISR. In addition, it is shown that the degree of SISR induced by Lévy noise is not always higher than that of Gaussian noise. Second, we show that, for both types of noises, the two memristive properties of the neuron have opposite effects on the degree of SISR: the stronger the feedback gain parameter that controls the modulation of the membrane potential with the magnetic flux and the weaker the feedback gain parameter that controls the saturation of the magnetic flux, the higher the degree of SISR. Finally, we show that, for both types of noises, the degree of SISR in the memristive neuron is always higher than in the non-memristive neuron. Our results could find applications in designing neuromorphic circuits operating in noisy regimes.

Stochastic resonance and vibrational resonance in an excitable system: The golden mean barrier

2009 ◽  
Vol 41 (2) ◽  
pp. 727-734 ◽  
Author(s):  
Cristina Stan ◽  
C.P. Cristescu ◽  
D. Alexandroaei ◽  
M. Agop
Keyword(s):  
Stochastic Resonance ◽  
Vibrational Resonance ◽  
Golden Mean ◽  
Excitable System

Stochastic resonance in the peripheral auditory system

2014 ◽  
Vol 2 ◽  
pp. 417-420
Author(s):  
Florian Gomez ◽  
Stefan Martignoli ◽  
Ruedi Stoop
Keyword(s):  
Stochastic Resonance ◽  
Auditory System ◽  
Peripheral Auditory System

Information Aggregation via Stochastic Resonance in Moments

2014 ◽  
Vol 1 ◽  
pp. 13-16
Author(s):  
Akihisa Ichiki ◽  
Yukihiro Tadokoro
Keyword(s):  
Stochastic Resonance ◽  
Information Aggregation

Hybrid Vibration Energy Harvester based on Stochastic Resonance

2018 ◽  
Vol 138 (5) ◽  
pp. 185-190
Author(s):  
Meng Su ◽  
Dai Kobayashi ◽  
Nobuyuki Takama ◽  
Beomjoon Kim
Keyword(s):  
Stochastic Resonance ◽  
Energy Harvester ◽  
Vibration Energy ◽  
Vibration Energy Harvester

Improvement in Gate Dielectric Quality of Ultra Thin a: SiN:H MNS Capacitor by Hydrogen Etching of the Substrate

2002 ◽  
Vol 716 ◽  
Author(s):  
Parag C. Waghmare ◽  
Samadhan B. Patil ◽  
Rajiv O. Dusane ◽  
V.Ramgopal Rao
Keyword(s):  
Silicon Nitride ◽  
Gate Dielectric ◽  
Substrate Surface ◽  
Scaling Limit ◽  
Tunneling Current ◽  
Chemical Vapor ◽  
Poor Performance ◽  
State Density ◽  
Direct Tunneling Current

AbstractTo extend the scaling limit of thermal SiO2, in the ultra thin regime when the direct tunneling current becomes significant, members of our group embarked on a program to explore the potential of silicon nitride as an alternative gate dielectric. Silicon nitride can be deposited using several CVD methods and its properties significantly depend on the method of deposition. Although these CVD methods can give good physical properties, the electrical properties of devices made with CVD silicon nitride show very poor performance related to very poor interface, poor stability, presence of large quantity of bulk traps and high gate leakage current. We have employed the rather newly developed Hot Wire Chemical Vapor Deposition (HWCVD) technique to develop the a:SiN:H material. From the results of large number of optimization experiments we propose the atomic hydrogen of the substrate surface prior to deposition to improve the quality of gate dielectric. Our preliminary results of these efforts show a five times improvement in the fixed charges and interface state density.

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