Emergence of synchronised and amplified oscillations in neuromorphic networks with long-range interactions

NEUROCOMPUTING

卷:461

Article

Apicella, I.^1,2  Busiello, D. M.³  Scarpetta, S.²  Suweis, S.^1,4 

[1] Univ Padua, INFN, Dipartimento Fis G Galilei, LIPh Lab, Via Marzolo 8, I-35131 Padua, Italy

[2] Univ Salerno, INFN Grp Coll Salerno, Dipartimento Fis ER Caianiello, Via Giovanni Paolo II, I-84084 Salerno, Italy

[3] Ecole Polytech Fed Lausanne EPFL, Lab Stat Biophys, Inst Phys, CH-1015 Lausanne, Switzerland

[4] Univ Padua, Padova Neurosci Ctr, Via Orus 2, I-35131 Padua, Italy

关键词: Synchronisation;    Stochastic resonance;    Stochastic amplification;    Long-range connections;    Wilson-Cowan model;   

DOI  :  10.1016/j.neucom.2020.04.162

来源: Elsevier

【 摘 要 】

Neuromorphic networks can be described in terms of coarse-grained variables, where emergent sus-tained behaviours spontaneously arise if stochasticity is properly taken into account. For example it has been recently found that a directed linear chain of connected patch of neurons amplifies an input sig-nal, also tuning its characteristic frequency. Here we study a generalization of such a simple model, intro-ducing heterogeneity and variability in the parameter space and long-range interactions, breaking, in turn, the preferential direction of information transmission of a directed chain. On one hand, enlarging the region of parameters leads to a more complex state space that we analytically characterise; moreover, we explicitly link the strength distribution of the non-local interactions with the frequency distribution of the network oscillations. On the other hand, we found that adding long-range interactions can cause the onset of novel phenomena, as coherent and synchronous oscillations among all the interacting units, which can also coexist with the amplification of the signal. (c) 2021 Published by Elsevier B.V.

【 授权许可】

Free