Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms (2022)
- Authors:
- Autor USP: FUJITA, ANDRÉ - IME
- Unidade: IME
- DOI: 10.3389/fncom.2022.975743
- Subjects: TEORIA DOS GRAFOS; NEUROCIÊNCIAS
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Frontiers in Computational Neuroscience
- ISSN: 1662-5188
- Volume/Número/Paginação/Ano: v. 16, art. 975743, 2022
- Este artigo NÃO possui versão em acesso aberto
-
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: 07 mar. 2026. -
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 2026 mar. 07 ] 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 2026 mar. 07 ] Available from: https://doi.org/10.3389/fncom.2022.975743 - Conservative generalized bifurcation diagrams and phase space properties for oval-like billiards
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