IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v390y2011i16p2855-2862.html
   My bibliography  Save this article

Neural signal transduction aided by noise in multisynaptic excitatory and inhibitory pathways with saturation

Author

Listed:
  • Duan, Fabing
  • Chapeau-Blondeau, François
  • Abbott, Derek

Abstract

We study the stochastic resonance phenomenon in saturating dynamical models of neural signal transduction, at the synaptic stage, wherein the noise in multipathways enhances the processing of neuronal information integrated by excitatory and inhibitory synaptic currents. For an excitatory synaptic pathway, the additive intervention of an inhibitory pathway reduces the stochastic resonance effect. However, as the number of synaptic pathways increases, the signal transduction is greatly improved for parallel multipathways that feature both excitation and inhibition. The obtained results lead us to the realization that the collective property of inhibitory synapses assists neural signal transmission, and a parallel array of neurons can enhance their responses to multiple synaptic currents by adjusting the contributions of excitatory and inhibitory currents.

Suggested Citation

  • Duan, Fabing & Chapeau-Blondeau, François & Abbott, Derek, 2011. "Neural signal transduction aided by noise in multisynaptic excitatory and inhibitory pathways with saturation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(16), pages 2855-2862.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:16:p:2855-2862
    DOI: 10.1016/j.physa.2011.03.039
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843711100272X
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2011.03.039?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tessone, Claudio J. & Wio, Horacio S., 2007. "Stochastic resonance in an extended FitzHugh–Nagumo system: The role of selective coupling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 46-54.
    2. Li, Jianlong & Xu, Bohou, 2006. "Effects of signal spectrum varying on signal processing by parameter-induced stochastic resonance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 361(1), pages 11-23.
    3. Duarte, J.R.R. & Vermelho, M.V.D. & Lyra, M.L., 2008. "Stochastic resonance of a periodically driven neuron under non-Gaussian noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(7), pages 1446-1454.
    4. Ueda, Michihito, 2010. "Improvement of signal-to-noise ratio by stochastic resonance in sigmoid function threshold systems, demonstrated using a CMOS inverter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 1978-1985.
    5. Arun V. Holden, 2004. "Neural coding by correlation?," Nature, Nature, vol. 428(6981), pages 382-382, March.
    6. Duan, Fabing & Chapeau-Blondeau, François & Abbott, Derek, 2009. "Input–output gain of collective response in an uncoupled parallel array of saturating dynamical subsystems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1345-1351.
    7. Gong, Yubing & Xie, Yanhang & Hao, Yinghang, 2009. "Coherence resonance induced by non-Gaussian noise in a deterministic Hodgkin–Huxley neuron," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(18), pages 3759-3764.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Jian & Cao, Jie & Wang, Youguo & Hu, Bing, 2019. "Asymmetric stochastic resonance in a bistable system driven by non-Gaussian colored noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 321-336.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Gang & Shu, Yichen & Zhang, Tianqi, 2022. "The study on dynamical behavior of FitzHugh–Nagumo neural model under the co-excitation of non-Gaussian and colored noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    2. Zhang, Ruiting & Hou, Zhonghuai & Xin, Houwen, 2011. "Effects of non-Gaussian noise near supercritical Hopf bifurcation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 147-153.
    3. Yu, Haitao & Galán, Roberto F. & Wang, Jiang & Cao, Yibin & Liu, Jing, 2017. "Stochastic resonance, coherence resonance, and spike timing reliability of Hodgkin–Huxley neurons with ion-channel noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 263-275.
    4. Wu, Jian-Li & Duan, Wei-Long & Luo, Yuhui & Yang, Fengzao, 2020. "Time delay and non-Gaussian noise-enhanced stability of foraging colony system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    5. Silva, L.B.M. & Vermelho, M.V.D. & Lyra, M.L. & Viswanathan, G.M., 2009. "Multifractal detrended fluctuation analysis of analog random multiplicative processes," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2806-2811.
    6. Guo, Xinmeng & Wang, Jiang & Liu, Jing & Yu, Haitao & Galán, Roberto F. & Cao, Yibin & Deng, Bin, 2017. "Optimal time scales of input fluctuations for spiking coherence and reliability in stochastic Hodgkin–Huxley neurons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 381-390.
    7. Cheng, Chaojun & Zhou, Bingchang & Gao, Xiao & McDonnell, Mark D., 2017. "M-ary suprathreshold stochastic resonance in multilevel threshold systems with signal-dependent noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 48-56.
    8. Xu, Liyan & Duan, Fabing & Abbott, Derek & McDonnell, Mark D., 2016. "Optimal weighted suprathreshold stochastic resonance with multigroup saturating sensors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 348-355.
    9. Dong, Xiaohui & Wang, Ming & Zhong, Guang-Yan & Yang, Fengzao & Duan, Weilong & Li, Jiang-Cheng & Xiong, Kezhao & Zeng, Chunhua, 2018. "Stochastic delayed kinetics of foraging colony system under non-Gaussian noise," Chaos, Solitons & Fractals, Elsevier, vol. 112(C), pages 1-13.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:390:y:2011:i:16:p:2855-2862. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.