The effects of time delay on the stochastic resonance in feed-forward-loop neuronal network motifs

Through introducing the ingredients of electromagnetic induction and coupled time delay into the original Fitzhugh–Nagumo (FHN) neuronal network, the dynamics of stochastic resonance in a model of modified FHN neuronal network in the environment of phase noise is explored by numerical simulations in this study. On one hand, we demonstrate that the phenomenon of stochastic resonance can appear when the intensity of phase noise is appropriately adjusted, which is further verified to be robust to the edge-added probability of small-world network. Moreover, under the influence of electromagnetic induction, the phase noise-induced resonance response is suppressed, meanwhile, a large noise intensity is required to induce stochastic resonance as the feedback gain of induced current increases. On the other hand, when the coupled time delay is incorporated into this model, the results indicate that the properly tuned time delay can induce multiple stochastic resonances in this neuronal network. However, the phenomenon of multiple stochastic resonances is found to be restrained upon increasing feedback gain of induced current. Surprisingly, by changing the period of phase noise, multiple stochastic resonances can still emerge when the coupled time delay is appropriately tuned to be integer multiples of the period of phase noise.

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Influence of non-Gaussian noise on the coherent feed-forward loop with time delay

Chaos Solitons & Fractals ◽

10.1016/j.chaos.2019.07.047 ◽

2019 ◽

Vol 129 ◽

pp. 46-55

Author(s):

Min Wang ◽

Yuwen Fang ◽

Yuhui Luo ◽

Fengzao Yang ◽

Chunhua Zeng ◽

...

Keyword(s):

Time Delay ◽

Gaussian Noise ◽

Feed Forward ◽

Feed Forward Loop ◽

Non Gaussian

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Organisation of feed-forward loop motifs reveals architectural principles in natural and engineered networks

10.1101/188821 ◽

2017 ◽

Cited By ~ 1

Author(s):

Thomas E. Gorochowski ◽

Claire S. Grierson ◽

Mario di Bernardo

Keyword(s):

Escherichia Coli ◽

Functional Analysis ◽

Broad Spectrum ◽

Building Blocks ◽

Networked Systems ◽

Network Motifs ◽

Feed Forward ◽

Feed Forward Loop ◽

Architectural Principles ◽

Important Nodes

AbstractNetwork motifs are significantly expressed sub-graphs that have been proposed as building blocks for natural and engineered networks. Detailed functional analysis has been performed for many types of motif in isolation, but less is known about how motifs work together to perform complex tasks. To address this issue we measure the aggregation of network motifs via methods that extract precisely how these structures are connected. Applying this approach to a broad spectrum of networked systems and focusing on the widespread feed-forward loop motif, we uncover striking differences in motif organisation. The types of connection are often highly constrained, differ between domains, and clearly capture architectural principles. We show how this information can be used to effectively predict functionally important nodes in the metabolic network ofEscherichia coli. Our findings have implications for understanding how networked systems are constructed from motif parts and elucidates constraints that guide their evolution.

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Extrinsic Noise Suppression in Micro RNA mediated Incoherent Feedforward Loops

10.1101/422394 ◽

2018 ◽

Cited By ~ 2

Author(s):

Alberto Carignano ◽

Sumit Mukherjee ◽

Abhyudai Singh ◽

Georg Seelig

Keyword(s):

Mammalian Cells ◽

Micro Rna ◽

Network Motifs ◽

Extrinsic Noise ◽

Feed Forward ◽

Feed Forward Loop ◽

Noise Rejection ◽

Feed Forward Network ◽

Translational Inhibition ◽

Special Case

AbstractMicroRNA mediated incoherent feed forward loops (IFFLs) are recurrent network motifs in mammalian cells and have been a topic of study for their noise rejection and buffering properties. Previous work showed that IFFLs can adapt to varying promoter activity and are less prone to noise than similar circuits without the feed forward loop. Furthermore, it has been shown that microRNAs are better at rejecting extrinsic noise than intrinsic noise. This work studies the biological mechanisms that lead to extrinsic noise rejection for microRNA mediated feed forward network motifs. Specifically, we compare the effects of microRNA-induced mRNA degradation and translational inhibition on extrinsic noise rejection, and identify the parameter regimes where noise is most efficiently rejected. In the case of static extrinsic noise, we find that translational inhibition can expand the regime of extrinsic noise rejection. We then analyze rejection of dynamic extrinsic noise in the case of a single-gene feed forward loop (sgFFL), a special case of the IFFL motif where the microRNA and target mRNA are co-expressed. For this special case, we demonstrate that depending on the time-scale of fluctuations in the extrinsic variable compared to the mRNA and microRNA decay rates, the feed forward loop can both buffer or amplify fluctuations in gene product copy numbers.

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