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
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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: 02 out. 2024.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.2022.975743NLM
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 2024 out. 02 ] Available from: https://doi.org/10.3389/fncom.2022.975743Vancouver
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 2024 out. 02 ] Available from: https://doi.org/10.3389/fncom.2022.975743
