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Filtros : "Frontiers in Computational Neuroscience" "NEUROCIÊNCIAS" Removido: "Financiamento CNPq" Limpar

Filtros

Artigo de periodico
Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms (2022)
Oku, Amanda Yumi Ambriola ; Barreto, Candida ; Bruneri, Guilherme; Brockington, Guilherme ; Fujita, André ; Sato, João Ricardo
Source: Frontiers in Computational Neuroscience. Unidade: IME
Subjects: TEORIA DOS GRAFOS, NEUROCIÊNCIAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OKU, Amanda Yumi Ambriola et al. Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms. Frontiers in Computational Neuroscience, v. 16, 2022Tradução . . Disponível em: https://doi.org/10.3389/fncom.2022.975743. Acesso em: 01 dez. 2025.
APA
Oku, A. Y. A., Barreto, C., Bruneri, G., Brockington, G., Fujita, A., & Sato, J. R. (2022). Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms. Frontiers in Computational Neuroscience, 16. doi:10.3389/fncom.2022.975743
NLM
Oku AYA, Barreto C, Bruneri G, Brockington G, Fujita A, Sato JR. Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms [Internet]. Frontiers in Computational Neuroscience. 2022 ; 16[citado 2025 dez. 01 ] Available from: https://doi.org/10.3389/fncom.2022.975743
Vancouver
Oku AYA, Barreto C, Bruneri G, Brockington G, Fujita A, Sato JR. Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms [Internet]. Frontiers in Computational Neuroscience. 2022 ; 16[citado 2025 dez. 01 ] Available from: https://doi.org/10.3389/fncom.2022.975743
Artigo de periodico
Mechanisms of self-sustained oscillatory states in hierarchical modular networks with mixtures of electrophysiological cell types (2016)
Tomov, Petar; Pena, Rodrigo F. O.; Roque, Antônio Carlos; Zaks, Michael A.
Source: Frontiers in Computational Neuroscience. Unidade: FFCLRP
Subjects: NEUROCIÊNCIAS, CIÊNCIA DA COMPUTAÇÃO, ELETROFISIOLOGIA, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TOMOV, Petar et al. Mechanisms of self-sustained oscillatory states in hierarchical modular networks with mixtures of electrophysiological cell types. Frontiers in Computational Neuroscience, 2016Tradução . . Disponível em: https://doi.org/10.3389/fncom.2016.00023. Acesso em: 01 dez. 2025.
APA
Tomov, P., Pena, R. F. O., Roque, A. C., & Zaks, M. A. (2016). Mechanisms of self-sustained oscillatory states in hierarchical modular networks with mixtures of electrophysiological cell types. Frontiers in Computational Neuroscience. doi:10.3389/fncom.2016.00023
NLM
Tomov P, Pena RFO, Roque AC, Zaks MA. Mechanisms of self-sustained oscillatory states in hierarchical modular networks with mixtures of electrophysiological cell types [Internet]. Frontiers in Computational Neuroscience. 2016 ;[citado 2025 dez. 01 ] Available from: https://doi.org/10.3389/fncom.2016.00023
Vancouver
Tomov P, Pena RFO, Roque AC, Zaks MA. Mechanisms of self-sustained oscillatory states in hierarchical modular networks with mixtures of electrophysiological cell types [Internet]. Frontiers in Computational Neuroscience. 2016 ;[citado 2025 dez. 01 ] Available from: https://doi.org/10.3389/fncom.2016.00023

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