Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Costa, Ariadne A."'
In this work, we study the topological transition on the associated networks in a model proposed by Saeedian et al. (Scientific Reports 2019 9:9726), which considers a coupled dynamics of node and link states. Our goal was to better understand the tw
Externí odkaz:
http://arxiv.org/abs/2112.04874
Autor:
Girardi-Schappo, Mauricio, Brochini, Ludmila, Costa, Ariadne A., Carvalho, Tawan T. A., Kinouchi, Osame
Publikováno v:
Phys. Rev. Research 2, 012042(R) (2020)
Recent experiments suggested that homeostatic regulation of synaptic balance leads the visual system to recover and maintain a regime of power-law avalanches. Here we study an excitatory/inhibitory (E/I) mean-field neuronal network that has a critica
Externí odkaz:
http://arxiv.org/abs/2002.09117
Autor:
Girardi-Schappo, Mauricio, Brochini, Ludmila, Costa, Ariadne A., Carvalho, Tawan T. A., Kinouchi, Osame
Publikováno v:
Phys. Rev. Research 2, 012042(R) (2020)
Asynchronous irregular (AI) and critical states are two competing frameworks proposed to explain spontaneous neuronal activity. Here, we propose a mean-field model with simple stochastic neurons that generalizes the integrate-and-fire network of Brun
Externí odkaz:
http://arxiv.org/abs/1906.05624
Akademický článek
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Although there is increasing evidence of criticality in the brain, the processes that guide neuronal networks to reach or maintain criticality remain unclear. The present research examines the role of neuronal gain plasticity in time-series of simula
Externí odkaz:
http://arxiv.org/abs/1801.08087
Publikováno v:
Entropy 19 (2017) 399
Networks of stochastic spiking neurons are interesting models in the area of Theoretical Neuroscience, presenting both continuous and discontinuous phase transitions. Here we study fully connected networks analytically, numerically and by computation
Externí odkaz:
http://arxiv.org/abs/1705.08549
Autor:
Costa, Ariadne A., Frigori, Rafael B.
Publikováno v:
Frontiers in Research Metrics & Analytics; 2024, p1-9, 9p
Publikováno v:
Phys. Rev. E 95, 042303 (2017)
In a recent work, mean-field analysis and computer simulations were employed to analyze critical self-organization in networks of excitable cellular automata where randomly chosen synapses in the network were depressed after each spike (the so-called
Externí odkaz:
http://arxiv.org/abs/1604.05779
Neuronal networks can present activity described by power-law distributed avalanches presumed to be a signature of a critical state. Here we study a random-neighbor network of excitable cellular automata coupled by dynamical synapses. The model exhib
Externí odkaz:
http://arxiv.org/abs/1405.7740
Akademický článek
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