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Filtros : "Bernardi, Davide" Removidos: "Estados Unidos" "Checo" Limpar

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  • Artigo de periodico

    Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks (2018)

    Pena, Rodrigo Felipe de Oliveira; Vellmer, Sebastian; Bernardi, Davide; Roque, Antônio Carlos; Lindner, Benjamin

    Source: Frontiers in Computational Neuroscience. Unidade: FFCLRP

    Subjects: REDES COMPLEXAS, REDE NERVOSA, REDES NEURAIS, MODELOS PARA PROCESSOS ESTOCÁSTICOS

    Versão PublicadaAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      PENA, Rodrigo Felipe de Oliveira et al. Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks. Frontiers in Computational Neuroscience, v. 12, 2018Tradução . . Disponível em: https://doi.org/10.3389/fncom.2018.00009. Acesso em: 13 nov. 2024.

    • APA

      Pena, R. F. de O., Vellmer, S., Bernardi, D., Roque, A. C., & Lindner, B. (2018). Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks. Frontiers in Computational Neuroscience, 12. doi:10.3389/fncom.2018.00009

    • NLM

      Pena RF de O, Vellmer S, Bernardi D, Roque AC, Lindner B. Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks [Internet]. Frontiers in Computational Neuroscience. 2018 ; 12[citado 2024 nov. 13 ] Available from: https://doi.org/10.3389/fncom.2018.00009

    • Vancouver

      Pena RF de O, Vellmer S, Bernardi D, Roque AC, Lindner B. Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks [Internet]. Frontiers in Computational Neuroscience. 2018 ; 12[citado 2024 nov. 13 ] Available from: https://doi.org/10.3389/fncom.2018.00009

  • Trabalho de evento-resumo periodico

    Determination of the spike‑train power spectrum statistics in modular networks with mixtures of diferent excitatory and inhibitory populations (2017)

    Pena, Rodrigo Felipe de Oliveira; Bernardi, Davide; Roque, Antônio Carlos; Lindner, Benjamin

    Source: BMC Neuroscience. Conference titles: Annual Computational Neuroscience Meeting (CNS). Unidade: FFCLRP

    Subjects: REDES NEURAIS, NEUROCIÊNCIAS

    Acesso à fonteHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      PENA, Rodrigo Felipe de Oliveira et al. Determination of the spike‑train power spectrum statistics in modular networks with mixtures of diferent excitatory and inhibitory populations. BMC Neuroscience. London: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://bmcneurosci.biomedcentral.com/track/pdf/10.1186/s12868-017-0371-2. Acesso em: 13 nov. 2024. , 2017

    • APA

      Pena, R. F. de O., Bernardi, D., Roque, A. C., & Lindner, B. (2017). Determination of the spike‑train power spectrum statistics in modular networks with mixtures of diferent excitatory and inhibitory populations. BMC Neuroscience. London: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. Recuperado de https://bmcneurosci.biomedcentral.com/track/pdf/10.1186/s12868-017-0371-2

    • NLM

      Pena RF de O, Bernardi D, Roque AC, Lindner B. Determination of the spike‑train power spectrum statistics in modular networks with mixtures of diferent excitatory and inhibitory populations [Internet]. BMC Neuroscience. 2017 ; 18 59.[citado 2024 nov. 13 ] Available from: https://bmcneurosci.biomedcentral.com/track/pdf/10.1186/s12868-017-0371-2

    • Vancouver

      Pena RF de O, Bernardi D, Roque AC, Lindner B. Determination of the spike‑train power spectrum statistics in modular networks with mixtures of diferent excitatory and inhibitory populations [Internet]. BMC Neuroscience. 2017 ; 18 59.[citado 2024 nov. 13 ] Available from: https://bmcneurosci.biomedcentral.com/track/pdf/10.1186/s12868-017-0371-2
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