Stochastic oscillations and dragon king avalanches in self-organized quasi-critical systems View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Osame Kinouchi, Ludmila Brochini, Ariadne A. Costa, João Guilherme Ferreira Campos, Mauro Copelli

ABSTRACT

In the last decade, several models with network adaptive mechanisms (link deletion-creation, dynamic synapses, dynamic gains) have been proposed as examples of self-organized criticality (SOC) to explain neuronal avalanches. However, all these systems present stochastic oscillations hovering around the critical region that are incompatible with standard SOC. Here we make a linear stability analysis of the mean field fixed points of two self-organized quasi-critical systems: a fully connected network of discrete time stochastic spiking neurons with firing rate adaptation produced by dynamic neuronal gains and an excitable cellular automata with depressing synapses. We find that the fixed point corresponds to a stable focus that loses stability at criticality. We argue that when this focus is close to become indifferent, demographic noise can elicit stochastic oscillations that frequently fall into the absorbing state. This mechanism interrupts the oscillations, producing both power law avalanches and dragon king events, which appear as bands of synchronized firings in raster plots. Our approach differs from standard SOC models in that it predicts the coexistence of these different types of neuronal activity. More... »

PAGES

3874

References to SciGraph publications

  • 2013-12. Griffiths phases and the stretching of criticality in brain networks in NATURE COMMUNICATIONS
  • 2013-07. Temporal whitening by power-law adaptation in neocortical neurons in NATURE NEUROSCIENCE
  • 1991-05. On a forest fire model with supposed self-organized criticality in JOURNAL OF STATISTICAL PHYSICS
  • 2018-02-15. Fractal Analyses of Networks of Integrate-and-Fire Stochastic Spiking Neurons in COMPLEX NETWORKS IX
  • 2013-06. Infinite Systems of Interacting Chains with Memory of Variable Length—A Stochastic Model for Biological Neural Nets in JOURNAL OF STATISTICAL PHYSICS
  • 2011-09. Sustained oscillations for density dependent Markov processes in JOURNAL OF MATHEMATICAL BIOLOGY
  • 2014-07. The Theory of Individual Based Discrete-Time Processes in JOURNAL OF STATISTICAL PHYSICS
  • 2007-12. Dynamical synapses causing self-organized criticality in neural networks in NATURE PHYSICS
  • 2012-05. Are dragon-king neuronal avalanches dungeons for self-organized brain activity? in THE EUROPEAN PHYSICAL JOURNAL SPECIAL TOPICS
  • 2016-12. Phase transitions and self-organized criticality in networks of stochastic spiking neurons in SCIENTIFIC REPORTS
  • 2006-05. Optimal dynamical range of excitable networks at criticality in NATURE PHYSICS
  • 2000-05. Dynamics of Sparsely Connected Networks of Excitatory and Inhibitory Spiking Neurons in JOURNAL OF COMPUTATIONAL NEUROSCIENCE
  • 2013-09. Noise focusing and the emergence of coherent activity in neuronal cultures in NATURE PHYSICS
  • 2010-10. Emergent complex neural dynamics in NATURE PHYSICS
  • 2018-12. Neuronal avalanche dynamics indicates different universality classes in neuronal cultures in SCIENTIFIC REPORTS
  • 1976-09. A simple mechanism for population cycles in NATURE
  • 2007-12. Bounding the quality of stochastic oscillations in population models in THE EUROPEAN PHYSICAL JOURNAL B
  • 2016-09. Griffiths phase and long-range correlations in a biologically motivated visual cortex model in SCIENTIFIC REPORTS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41598-019-40473-1

    DOI

    http://dx.doi.org/10.1038/s41598-019-40473-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112602932

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30846773


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Statistics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Mathematical Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "University of Sao Paulo", 
              "id": "https://www.grid.ac/institutes/grid.11899.38", 
              "name": [
                "Universidade de S\u00e3o Paulo, Departamento de F\u00edsica-FFCLRP, Ribeir\u00e3o Preto, SP, Brazil"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kinouchi", 
            "givenName": "Osame", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Sao Paulo", 
              "id": "https://www.grid.ac/institutes/grid.11899.38", 
              "name": [
                "Universidade de S\u00e3o Paulo, Instituto de Matem\u00e1tica e Estat\u00edstica, S\u00e3o Paulo, SP, Brazil"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Brochini", 
            "givenName": "Ludmila", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Universidade Federal de Goi\u00e1s", 
              "id": "https://www.grid.ac/institutes/grid.411195.9", 
              "name": [
                "Universidade Federal de Goi\u00e1s, Unidade Acad\u00eamica Especial de Ci\u00eancias Exatas, Jata\u00ed, GO, Brazil"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Costa", 
            "givenName": "Ariadne A.", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Federal University of Pernambuco", 
              "id": "https://www.grid.ac/institutes/grid.411227.3", 
              "name": [
                "Universidade Federal de Pernambuco, Departamento de F\u00edsica, Recife, PE, Brazil"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Campos", 
            "givenName": "Jo\u00e3o Guilherme Ferreira", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Federal University of Pernambuco", 
              "id": "https://www.grid.ac/institutes/grid.411227.3", 
              "name": [
                "Universidade de S\u00e3o Paulo, Departamento de F\u00edsica-FFCLRP, Ribeir\u00e3o Preto, SP, Brazil", 
                "Universidade Federal de Pernambuco, Departamento de F\u00edsica, Recife, PE, Brazil"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Copelli", 
            "givenName": "Mauro", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s10955-013-0733-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000317323", 
              "https://doi.org/10.1007/s10955-013-0733-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/a:1008925309027", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001166884", 
              "https://doi.org/10.1023/a:1008925309027"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.57.6345", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002325395"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.57.6345", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002325395"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3389/fphys.2012.00062", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003161987"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nn.3431", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003982324", 
              "https://doi.org/10.1038/nn.3431"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.96.028107", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005165684"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.96.028107", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005165684"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1029/90jb02474", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005864622"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nphys758", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006733245", 
              "https://doi.org/10.1038/nphys758"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1590/s0103-97332000000100004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007956957"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.94.218102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008614183"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.94.218102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008614183"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.94.218102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008614183"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.112.138103", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008632553"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.112.138103", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008632553"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/263319a0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010091760", 
              "https://doi.org/10.1038/263319a0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/1742-5468/2010/02/p02015", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010664632"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/1742-5468/2010/02/p02015", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010664632"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nphys2686", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012303155", 
              "https://doi.org/10.1038/nphys2686"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1140/epjst/e2012-01574-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012591128", 
              "https://doi.org/10.1140/epjst/e2012-01574-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf01029205", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015803723", 
              "https://doi.org/10.1007/bf01029205"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.88.012712", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016836532"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.88.012712", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016836532"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.57.5095", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017155295"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.57.5095", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017155295"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1098/rsta.2007.2092", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017619219"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nphys289", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018095608", 
              "https://doi.org/10.1038/nphys289"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nphys289", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018095608", 
              "https://doi.org/10.1038/nphys289"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.90.032135", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018136077"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.90.032135", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018136077"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ncomms3521", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019777098", 
              "https://doi.org/10.1038/ncomms3521"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1162/089976698300017502", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020463606"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/1742-5468/2015/06/p06004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028347501"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1098/rsif.2012.0558", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028415074"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.84.6114", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028627116"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.84.6114", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028627116"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nphys1803", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028718950", 
              "https://doi.org/10.1038/nphys1803"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nphys1803", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028718950", 
              "https://doi.org/10.1038/nphys1803"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.106.058101", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029590711"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.106.058101", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029590711"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0014804", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031340107"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/hbm.20590", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032074181"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep35831", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033256506", 
              "https://doi.org/10.1038/srep35831"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/1742-5468/2009/09/p09009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036970322"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/1742-5468/2009/09/p09009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036970322"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00285-010-0376-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037971277", 
              "https://doi.org/10.1007/s00285-010-0376-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1523/jneurosci.5990-11.2012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038585845"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pcbi.1002312", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039045388"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.86.021909", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045331182"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.86.021909", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045331182"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep29561", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047596388", 
              "https://doi.org/10.1038/srep29561"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.physa.2004.05.064", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048380827"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1140/epjb/e2008-00011-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049201425", 
              "https://doi.org/10.1140/epjb/e2008-00011-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10955-014-0990-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052728885", 
              "https://doi.org/10.1007/s10955-014-0990-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.neuron.2012.01.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052787509"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.94.2.719", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053345568"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.80.061917", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053508347"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.80.061917", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053508347"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1063/1.882869", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058128321"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/0954-898x_3_2_004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059115903"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.102.118110", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060755033"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.102.118110", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060755033"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.116.240601", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060765729"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevlett.116.240601", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060765729"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1523/jneurosci.23-35-11167.2003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1076608034"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.95.012310", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1083844810"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.95.012310", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1083844810"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.95.042303", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084786684"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physreve.95.042303", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084786684"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3390/e19080399", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1090944759"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1017/cbo9780511622717", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1098664122"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1017/cbo9780511815706", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1098668653"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1017/cbo9780511977671", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1098682357"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1063/1.4997254", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1100203447"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1162/neco_a_01061", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1100722857"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-73198-8_14", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101045322", 
              "https://doi.org/10.1007/978-3-319-73198-8_14"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-73198-8_14", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101045322", 
              "https://doi.org/10.1007/978-3-319-73198-8_14"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41598-018-21730-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101059627", 
              "https://doi.org/10.1038/s41598-018-21730-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41598-018-21730-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101059627", 
              "https://doi.org/10.1038/s41598-018-21730-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41598-018-21730-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101059627", 
              "https://doi.org/10.1038/s41598-018-21730-1"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019-12", 
        "datePublishedReg": "2019-12-01", 
        "description": "In the last decade, several models with network adaptive mechanisms (link deletion-creation, dynamic synapses, dynamic gains) have been proposed as examples of self-organized criticality (SOC) to explain neuronal avalanches. However, all these systems present stochastic oscillations hovering around the critical region that are incompatible with standard SOC. Here we make a linear stability analysis of the mean field fixed points of two self-organized quasi-critical systems: a fully connected network of discrete time stochastic spiking neurons with firing rate adaptation produced by dynamic neuronal gains and an excitable cellular automata with depressing synapses. We find that the fixed point corresponds to a stable focus that loses stability at criticality. We argue that when this focus is close to become indifferent, demographic noise can elicit stochastic oscillations that frequently fall into the absorbing state. This mechanism interrupts the oscillations, producing both power law avalanches and dragon king events, which appear as bands of synchronized firings in raster plots. Our approach differs from standard SOC models in that it predicts the coexistence of these different types of neuronal activity.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1038/s41598-019-40473-1", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.4552898", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.4481778", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.4533507", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1045337", 
            "issn": [
              "2045-2322"
            ], 
            "name": "Scientific Reports", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "9"
          }
        ], 
        "name": "Stochastic oscillations and dragon king avalanches in self-organized quasi-critical systems", 
        "pagination": "3874", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "2353cc6c3a3feb4e8f6018c090682d543c2abb4b32308ad1d64a8566a2680694"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "30846773"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101563288"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1038/s41598-019-40473-1"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1112602932"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1038/s41598-019-40473-1", 
          "https://app.dimensions.ai/details/publication/pub.1112602932"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T13:18", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000368_0000000368/records_78944_00000001.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://www.nature.com/articles/s41598-019-40473-1"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-40473-1'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-40473-1'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-40473-1'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-40473-1'


     

    This table displays all metadata directly associated to this object as RDF triples.

    297 TRIPLES      21 PREDICATES      87 URIs      21 LITERALS      9 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1038/s41598-019-40473-1 schema:about anzsrc-for:01
    2 anzsrc-for:0104
    3 schema:author N2b1aa38296254f21a6184dfd27e8e77d
    4 schema:citation sg:pub.10.1007/978-3-319-73198-8_14
    5 sg:pub.10.1007/bf01029205
    6 sg:pub.10.1007/s00285-010-0376-2
    7 sg:pub.10.1007/s10955-013-0733-9
    8 sg:pub.10.1007/s10955-014-0990-2
    9 sg:pub.10.1023/a:1008925309027
    10 sg:pub.10.1038/263319a0
    11 sg:pub.10.1038/ncomms3521
    12 sg:pub.10.1038/nn.3431
    13 sg:pub.10.1038/nphys1803
    14 sg:pub.10.1038/nphys2686
    15 sg:pub.10.1038/nphys289
    16 sg:pub.10.1038/nphys758
    17 sg:pub.10.1038/s41598-018-21730-1
    18 sg:pub.10.1038/srep29561
    19 sg:pub.10.1038/srep35831
    20 sg:pub.10.1140/epjb/e2008-00011-7
    21 sg:pub.10.1140/epjst/e2012-01574-6
    22 https://doi.org/10.1002/hbm.20590
    23 https://doi.org/10.1016/j.neuron.2012.01.007
    24 https://doi.org/10.1016/j.physa.2004.05.064
    25 https://doi.org/10.1017/cbo9780511622717
    26 https://doi.org/10.1017/cbo9780511815706
    27 https://doi.org/10.1017/cbo9780511977671
    28 https://doi.org/10.1029/90jb02474
    29 https://doi.org/10.1063/1.4997254
    30 https://doi.org/10.1063/1.882869
    31 https://doi.org/10.1073/pnas.94.2.719
    32 https://doi.org/10.1088/0954-898x_3_2_004
    33 https://doi.org/10.1088/1742-5468/2009/09/p09009
    34 https://doi.org/10.1088/1742-5468/2010/02/p02015
    35 https://doi.org/10.1088/1742-5468/2015/06/p06004
    36 https://doi.org/10.1098/rsif.2012.0558
    37 https://doi.org/10.1098/rsta.2007.2092
    38 https://doi.org/10.1103/physreve.57.5095
    39 https://doi.org/10.1103/physreve.57.6345
    40 https://doi.org/10.1103/physreve.80.061917
    41 https://doi.org/10.1103/physreve.86.021909
    42 https://doi.org/10.1103/physreve.88.012712
    43 https://doi.org/10.1103/physreve.90.032135
    44 https://doi.org/10.1103/physreve.95.012310
    45 https://doi.org/10.1103/physreve.95.042303
    46 https://doi.org/10.1103/physrevlett.102.118110
    47 https://doi.org/10.1103/physrevlett.106.058101
    48 https://doi.org/10.1103/physrevlett.112.138103
    49 https://doi.org/10.1103/physrevlett.116.240601
    50 https://doi.org/10.1103/physrevlett.84.6114
    51 https://doi.org/10.1103/physrevlett.94.218102
    52 https://doi.org/10.1103/physrevlett.96.028107
    53 https://doi.org/10.1162/089976698300017502
    54 https://doi.org/10.1162/neco_a_01061
    55 https://doi.org/10.1371/journal.pcbi.1002312
    56 https://doi.org/10.1371/journal.pone.0014804
    57 https://doi.org/10.1523/jneurosci.23-35-11167.2003
    58 https://doi.org/10.1523/jneurosci.5990-11.2012
    59 https://doi.org/10.1590/s0103-97332000000100004
    60 https://doi.org/10.3389/fphys.2012.00062
    61 https://doi.org/10.3390/e19080399
    62 schema:datePublished 2019-12
    63 schema:datePublishedReg 2019-12-01
    64 schema:description In the last decade, several models with network adaptive mechanisms (link deletion-creation, dynamic synapses, dynamic gains) have been proposed as examples of self-organized criticality (SOC) to explain neuronal avalanches. However, all these systems present stochastic oscillations hovering around the critical region that are incompatible with standard SOC. Here we make a linear stability analysis of the mean field fixed points of two self-organized quasi-critical systems: a fully connected network of discrete time stochastic spiking neurons with firing rate adaptation produced by dynamic neuronal gains and an excitable cellular automata with depressing synapses. We find that the fixed point corresponds to a stable focus that loses stability at criticality. We argue that when this focus is close to become indifferent, demographic noise can elicit stochastic oscillations that frequently fall into the absorbing state. This mechanism interrupts the oscillations, producing both power law avalanches and dragon king events, which appear as bands of synchronized firings in raster plots. Our approach differs from standard SOC models in that it predicts the coexistence of these different types of neuronal activity.
    65 schema:genre research_article
    66 schema:inLanguage en
    67 schema:isAccessibleForFree true
    68 schema:isPartOf N7efd25ad056b483b9bc3aa75bef029e9
    69 Nb1aee1785bd34939a15c35c8e68ae9a6
    70 sg:journal.1045337
    71 schema:name Stochastic oscillations and dragon king avalanches in self-organized quasi-critical systems
    72 schema:pagination 3874
    73 schema:productId N5447fb304eef470689e6b0e5756462c7
    74 N591578faf3f64859a20472126783fcfc
    75 N73667922f6a34f4db4b1d1a37a09a4a2
    76 Na797ede6580745918795ee0da0bd0343
    77 Nc8d540b9a7564f31b7c3d1e339765b35
    78 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112602932
    79 https://doi.org/10.1038/s41598-019-40473-1
    80 schema:sdDatePublished 2019-04-11T13:18
    81 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    82 schema:sdPublisher N40099fe3b1f0438ebb9323de8f45fb39
    83 schema:url https://www.nature.com/articles/s41598-019-40473-1
    84 sgo:license sg:explorer/license/
    85 sgo:sdDataset articles
    86 rdf:type schema:ScholarlyArticle
    87 N2b1aa38296254f21a6184dfd27e8e77d rdf:first Na433c868500045fe92cb655d563fd21c
    88 rdf:rest N9d4d0aae53564a1d9aeadda56ac9dbbd
    89 N30271e94f9c74bebac5ce9d6a24a2fd7 schema:affiliation https://www.grid.ac/institutes/grid.11899.38
    90 schema:familyName Brochini
    91 schema:givenName Ludmila
    92 rdf:type schema:Person
    93 N40099fe3b1f0438ebb9323de8f45fb39 schema:name Springer Nature - SN SciGraph project
    94 rdf:type schema:Organization
    95 N5447fb304eef470689e6b0e5756462c7 schema:name pubmed_id
    96 schema:value 30846773
    97 rdf:type schema:PropertyValue
    98 N591578faf3f64859a20472126783fcfc schema:name nlm_unique_id
    99 schema:value 101563288
    100 rdf:type schema:PropertyValue
    101 N62c65417b4a540c4b9a46ceb7277d7bf schema:affiliation https://www.grid.ac/institutes/grid.411227.3
    102 schema:familyName Copelli
    103 schema:givenName Mauro
    104 rdf:type schema:Person
    105 N6eb30c2cbde94aeeaaf3f78d40a90a0d rdf:first N91d1e71d8e954aaea3ad06cea28995ac
    106 rdf:rest N796bda29043b45efbea634a6c1439e50
    107 N73667922f6a34f4db4b1d1a37a09a4a2 schema:name dimensions_id
    108 schema:value pub.1112602932
    109 rdf:type schema:PropertyValue
    110 N796bda29043b45efbea634a6c1439e50 rdf:first Nfe1967781ea1423bb38733cbb32b667b
    111 rdf:rest Ne7cd8f2dbf7a4aef87406084fee5a67a
    112 N7efd25ad056b483b9bc3aa75bef029e9 schema:volumeNumber 9
    113 rdf:type schema:PublicationVolume
    114 N91d1e71d8e954aaea3ad06cea28995ac schema:affiliation https://www.grid.ac/institutes/grid.411195.9
    115 schema:familyName Costa
    116 schema:givenName Ariadne A.
    117 rdf:type schema:Person
    118 N9d4d0aae53564a1d9aeadda56ac9dbbd rdf:first N30271e94f9c74bebac5ce9d6a24a2fd7
    119 rdf:rest N6eb30c2cbde94aeeaaf3f78d40a90a0d
    120 Na433c868500045fe92cb655d563fd21c schema:affiliation https://www.grid.ac/institutes/grid.11899.38
    121 schema:familyName Kinouchi
    122 schema:givenName Osame
    123 rdf:type schema:Person
    124 Na797ede6580745918795ee0da0bd0343 schema:name doi
    125 schema:value 10.1038/s41598-019-40473-1
    126 rdf:type schema:PropertyValue
    127 Nb1aee1785bd34939a15c35c8e68ae9a6 schema:issueNumber 1
    128 rdf:type schema:PublicationIssue
    129 Nc8d540b9a7564f31b7c3d1e339765b35 schema:name readcube_id
    130 schema:value 2353cc6c3a3feb4e8f6018c090682d543c2abb4b32308ad1d64a8566a2680694
    131 rdf:type schema:PropertyValue
    132 Ne7cd8f2dbf7a4aef87406084fee5a67a rdf:first N62c65417b4a540c4b9a46ceb7277d7bf
    133 rdf:rest rdf:nil
    134 Nfe1967781ea1423bb38733cbb32b667b schema:affiliation https://www.grid.ac/institutes/grid.411227.3
    135 schema:familyName Campos
    136 schema:givenName João Guilherme Ferreira
    137 rdf:type schema:Person
    138 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
    139 schema:name Mathematical Sciences
    140 rdf:type schema:DefinedTerm
    141 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
    142 schema:name Statistics
    143 rdf:type schema:DefinedTerm
    144 sg:grant.4481778 http://pending.schema.org/fundedItem sg:pub.10.1038/s41598-019-40473-1
    145 rdf:type schema:MonetaryGrant
    146 sg:grant.4533507 http://pending.schema.org/fundedItem sg:pub.10.1038/s41598-019-40473-1
    147 rdf:type schema:MonetaryGrant
    148 sg:grant.4552898 http://pending.schema.org/fundedItem sg:pub.10.1038/s41598-019-40473-1
    149 rdf:type schema:MonetaryGrant
    150 sg:journal.1045337 schema:issn 2045-2322
    151 schema:name Scientific Reports
    152 rdf:type schema:Periodical
    153 sg:pub.10.1007/978-3-319-73198-8_14 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101045322
    154 https://doi.org/10.1007/978-3-319-73198-8_14
    155 rdf:type schema:CreativeWork
    156 sg:pub.10.1007/bf01029205 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015803723
    157 https://doi.org/10.1007/bf01029205
    158 rdf:type schema:CreativeWork
    159 sg:pub.10.1007/s00285-010-0376-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037971277
    160 https://doi.org/10.1007/s00285-010-0376-2
    161 rdf:type schema:CreativeWork
    162 sg:pub.10.1007/s10955-013-0733-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000317323
    163 https://doi.org/10.1007/s10955-013-0733-9
    164 rdf:type schema:CreativeWork
    165 sg:pub.10.1007/s10955-014-0990-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052728885
    166 https://doi.org/10.1007/s10955-014-0990-2
    167 rdf:type schema:CreativeWork
    168 sg:pub.10.1023/a:1008925309027 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001166884
    169 https://doi.org/10.1023/a:1008925309027
    170 rdf:type schema:CreativeWork
    171 sg:pub.10.1038/263319a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010091760
    172 https://doi.org/10.1038/263319a0
    173 rdf:type schema:CreativeWork
    174 sg:pub.10.1038/ncomms3521 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019777098
    175 https://doi.org/10.1038/ncomms3521
    176 rdf:type schema:CreativeWork
    177 sg:pub.10.1038/nn.3431 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003982324
    178 https://doi.org/10.1038/nn.3431
    179 rdf:type schema:CreativeWork
    180 sg:pub.10.1038/nphys1803 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028718950
    181 https://doi.org/10.1038/nphys1803
    182 rdf:type schema:CreativeWork
    183 sg:pub.10.1038/nphys2686 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012303155
    184 https://doi.org/10.1038/nphys2686
    185 rdf:type schema:CreativeWork
    186 sg:pub.10.1038/nphys289 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018095608
    187 https://doi.org/10.1038/nphys289
    188 rdf:type schema:CreativeWork
    189 sg:pub.10.1038/nphys758 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006733245
    190 https://doi.org/10.1038/nphys758
    191 rdf:type schema:CreativeWork
    192 sg:pub.10.1038/s41598-018-21730-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101059627
    193 https://doi.org/10.1038/s41598-018-21730-1
    194 rdf:type schema:CreativeWork
    195 sg:pub.10.1038/srep29561 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047596388
    196 https://doi.org/10.1038/srep29561
    197 rdf:type schema:CreativeWork
    198 sg:pub.10.1038/srep35831 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033256506
    199 https://doi.org/10.1038/srep35831
    200 rdf:type schema:CreativeWork
    201 sg:pub.10.1140/epjb/e2008-00011-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049201425
    202 https://doi.org/10.1140/epjb/e2008-00011-7
    203 rdf:type schema:CreativeWork
    204 sg:pub.10.1140/epjst/e2012-01574-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012591128
    205 https://doi.org/10.1140/epjst/e2012-01574-6
    206 rdf:type schema:CreativeWork
    207 https://doi.org/10.1002/hbm.20590 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032074181
    208 rdf:type schema:CreativeWork
    209 https://doi.org/10.1016/j.neuron.2012.01.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052787509
    210 rdf:type schema:CreativeWork
    211 https://doi.org/10.1016/j.physa.2004.05.064 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048380827
    212 rdf:type schema:CreativeWork
    213 https://doi.org/10.1017/cbo9780511622717 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098664122
    214 rdf:type schema:CreativeWork
    215 https://doi.org/10.1017/cbo9780511815706 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098668653
    216 rdf:type schema:CreativeWork
    217 https://doi.org/10.1017/cbo9780511977671 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098682357
    218 rdf:type schema:CreativeWork
    219 https://doi.org/10.1029/90jb02474 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005864622
    220 rdf:type schema:CreativeWork
    221 https://doi.org/10.1063/1.4997254 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100203447
    222 rdf:type schema:CreativeWork
    223 https://doi.org/10.1063/1.882869 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058128321
    224 rdf:type schema:CreativeWork
    225 https://doi.org/10.1073/pnas.94.2.719 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053345568
    226 rdf:type schema:CreativeWork
    227 https://doi.org/10.1088/0954-898x_3_2_004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059115903
    228 rdf:type schema:CreativeWork
    229 https://doi.org/10.1088/1742-5468/2009/09/p09009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036970322
    230 rdf:type schema:CreativeWork
    231 https://doi.org/10.1088/1742-5468/2010/02/p02015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010664632
    232 rdf:type schema:CreativeWork
    233 https://doi.org/10.1088/1742-5468/2015/06/p06004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028347501
    234 rdf:type schema:CreativeWork
    235 https://doi.org/10.1098/rsif.2012.0558 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028415074
    236 rdf:type schema:CreativeWork
    237 https://doi.org/10.1098/rsta.2007.2092 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017619219
    238 rdf:type schema:CreativeWork
    239 https://doi.org/10.1103/physreve.57.5095 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017155295
    240 rdf:type schema:CreativeWork
    241 https://doi.org/10.1103/physreve.57.6345 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002325395
    242 rdf:type schema:CreativeWork
    243 https://doi.org/10.1103/physreve.80.061917 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053508347
    244 rdf:type schema:CreativeWork
    245 https://doi.org/10.1103/physreve.86.021909 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045331182
    246 rdf:type schema:CreativeWork
    247 https://doi.org/10.1103/physreve.88.012712 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016836532
    248 rdf:type schema:CreativeWork
    249 https://doi.org/10.1103/physreve.90.032135 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018136077
    250 rdf:type schema:CreativeWork
    251 https://doi.org/10.1103/physreve.95.012310 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083844810
    252 rdf:type schema:CreativeWork
    253 https://doi.org/10.1103/physreve.95.042303 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084786684
    254 rdf:type schema:CreativeWork
    255 https://doi.org/10.1103/physrevlett.102.118110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060755033
    256 rdf:type schema:CreativeWork
    257 https://doi.org/10.1103/physrevlett.106.058101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029590711
    258 rdf:type schema:CreativeWork
    259 https://doi.org/10.1103/physrevlett.112.138103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008632553
    260 rdf:type schema:CreativeWork
    261 https://doi.org/10.1103/physrevlett.116.240601 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060765729
    262 rdf:type schema:CreativeWork
    263 https://doi.org/10.1103/physrevlett.84.6114 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028627116
    264 rdf:type schema:CreativeWork
    265 https://doi.org/10.1103/physrevlett.94.218102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008614183
    266 rdf:type schema:CreativeWork
    267 https://doi.org/10.1103/physrevlett.96.028107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005165684
    268 rdf:type schema:CreativeWork
    269 https://doi.org/10.1162/089976698300017502 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020463606
    270 rdf:type schema:CreativeWork
    271 https://doi.org/10.1162/neco_a_01061 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100722857
    272 rdf:type schema:CreativeWork
    273 https://doi.org/10.1371/journal.pcbi.1002312 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039045388
    274 rdf:type schema:CreativeWork
    275 https://doi.org/10.1371/journal.pone.0014804 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031340107
    276 rdf:type schema:CreativeWork
    277 https://doi.org/10.1523/jneurosci.23-35-11167.2003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1076608034
    278 rdf:type schema:CreativeWork
    279 https://doi.org/10.1523/jneurosci.5990-11.2012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038585845
    280 rdf:type schema:CreativeWork
    281 https://doi.org/10.1590/s0103-97332000000100004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007956957
    282 rdf:type schema:CreativeWork
    283 https://doi.org/10.3389/fphys.2012.00062 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003161987
    284 rdf:type schema:CreativeWork
    285 https://doi.org/10.3390/e19080399 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090944759
    286 rdf:type schema:CreativeWork
    287 https://www.grid.ac/institutes/grid.11899.38 schema:alternateName University of Sao Paulo
    288 schema:name Universidade de São Paulo, Departamento de Física-FFCLRP, Ribeirão Preto, SP, Brazil
    289 Universidade de São Paulo, Instituto de Matemática e Estatística, São Paulo, SP, Brazil
    290 rdf:type schema:Organization
    291 https://www.grid.ac/institutes/grid.411195.9 schema:alternateName Universidade Federal de Goiás
    292 schema:name Universidade Federal de Goiás, Unidade Acadêmica Especial de Ciências Exatas, Jataí, GO, Brazil
    293 rdf:type schema:Organization
    294 https://www.grid.ac/institutes/grid.411227.3 schema:alternateName Federal University of Pernambuco
    295 schema:name Universidade Federal de Pernambuco, Departamento de Física, Recife, PE, Brazil
    296 Universidade de São Paulo, Departamento de Física-FFCLRP, Ribeirão Preto, SP, Brazil
    297 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...