Control of coherence resonance in multiplex neural networks

被引:24
|
作者
Masoliver, Maria [1 ]
Masoller, Cristina [1 ]
Zakharova, Anna [2 ]
机构
[1] Univ Politecn Cataluna, Dept Fis, Rambla St Nebridi 22, Barcelona 08222, Spain
[2] Tech Univ Berlin, Inst Theoret Phys, Hardenbergstr 36, D-10623 Berlin, Germany
关键词
Synchronization; Multiplex network; Coherence resonance; FitzHugh?Nagumo neuron; NOISE; SYNCHRONIZATION; DELAY; NEURONS; STATES;
D O I
10.1016/j.chaos.2021.110666
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
We study the dynamics of two neuronal populations weakly and mutually coupled in a multiplexed ring configuration. We simulate the neuronal activity with the stochastic FitzHugh-Nagumo (FHN) model. The two neuronal populations perceive different levels of noise: one population exhibits spiking activity induced by supra-threshold noise (layer 1), while the other population is silent in the absence of inter-layer coupling because its own level of noise is sub-threshold (layer 2). We find that, for appropriate levels of noise in layer 1, weak inter-layer coupling can induce coherence resonance (CR), anti-coherence resonance (ACR) and inverse stochastic resonance (ISR) in layer 2. We also find that a small number of randomly distributed inter-layer links is sufficient to induce these phenomena in layer 2. Our results hold for small and large neuronal populations. (c) 2021 Published by Elsevier Ltd.
引用
收藏
页数:6
相关论文
共 50 条
  • [31] Unsupervised adaptive resonance theory neural networks for control chart pattern recognition
    Pham, DT
    Chan, AB
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2001, 215 (01) : 59 - 67
  • [32] Modular deep neural networks for automatic quality control of retinal optical coherence tomography scans
    Kauer-Bonin, Josef
    Yadav, Sunil K.
    Beckers, Ingeborg
    Gawlik, Kay
    Motamedi, Seyedamirhosein
    Zimmermann, Hanna G.
    Kadas, Ella M.
    Paul, Friedemann
    Brandt, Alexander U.
    Hausser, Frank
    COMPUTERS IN BIOLOGY AND MEDICINE, 2022, 141
  • [33] Coherence Resonance of Small World Networks with Adaptive Coupling
    Miyakawa, Kenji
    JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, 2015, 84 (06)
  • [34] Interplay between solitary states and chimeras in multiplex neural networks
    Rybalova, E. V.
    Zakharova, A.
    Strelkova, G. I.
    CHAOS SOLITONS & FRACTALS, 2021, 148
  • [35] Critical and resonance phenomena in neural networks
    Goltsev, A. V.
    Lopes, M. A.
    Lee, K. -E.
    Mendes, J. F. F.
    PHYSICS, COMPUTATION, AND THE MIND - ADVANCES AND CHALLENGES AT INTERFACES, 2013, 1510 : 28 - 35
  • [36] MANE: Organizational Network Embedding With Multiplex Attentive Neural Networks
    Ye, Yuyang
    Dong, Zheng
    Zhu, Hengshu
    Xu, Tong
    Song, Xin
    Yu, Runlong
    Xiong, Hui
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2023, 35 (04) : 4047 - 4061
  • [37] Multiplex Graph Neural Networks for Multi-behavior Recommendation
    Zhang, Weifeng
    Mao, Jingwen
    Cao, Yi
    Xu, Congfu
    CIKM '20: PROCEEDINGS OF THE 29TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT, 2020, : 2313 - 2316
  • [38] The role of coherence theory in attractor quantum neural networks
    Marconi, Carlo
    Colomer Saus, Pau
    Garcia Diaz, Maria
    Sanpera, Anna
    QUANTUM, 2022, 6
  • [39] Role of spatial coherence in diffractive optical neural networks
    Filipovich, M. atthew j.
    Malyshev, A. leksei
    Lvovsky, A. I.
    OPTICS EXPRESS, 2024, 32 (13): : 22986 - 22997
  • [40] RESOURCES ALLOCATION STRATEGIES OF DISEASE CONTROL IN MULTIPLEX NETWORKS
    Chen, Bo
    Yang, Chun
    Fu, Chuanji
    Gao, Yachun
    Yang, Hongchun
    ACTA PHYSICA POLONICA B, 2020, 51 (08): : 1785 - 1803