Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks (2018)
- Authors:
- Autor USP: SILVA FILHO, ANTONIO CARLOS ROQUE DA - FFCLRP
- Unidade: FFCLRP
- DOI: 10.3389/fncom.2018.00009
- Subjects: REDES COMPLEXAS; REDE NERVOSA; REDES NEURAIS; MODELOS PARA PROCESSOS ESTOCÁSTICOS
- Keywords: Complex networks; Stochastic models; Neural noise; Recurrent neural networks; Neural dynamics; Spike-train statistics; Spike-train power spectrum
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Frontiers in Computational Neuroscience
- ISSN: 1662-5188
- Volume/Número/Paginação/Ano: v. 12, art. 9, 2018
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by
-
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: 11 jan. 2026. -
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 2026 jan. 11 ] 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 2026 jan. 11 ] Available from: https://doi.org/10.3389/fncom.2018.00009 - Interplay of periglomerular and granule cell inhibitory synapses on mitral cell spiking
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Informações sobre o DOI: 10.3389/fncom.2018.00009 (Fonte: oaDOI API)
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