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pro vyhledávání: '"Dumont, Grégory"'
Elucidating the neurophysiological mechanisms underlying neural pattern formation remains an outstanding challenge in Computational Neuroscience. In this paper, we address the issue of understanding the emergence of neural patterns by considering a n
Externí odkaz:
http://arxiv.org/abs/2406.01167
Brain rhythms emerge as a result of synchronization among interconnected spiking neurons. Key properties of such rhythms can be gleaned from the phase-resetting curve (PRC). Inferring the macroscopic PRC and developing a systematic phase reduction th
Externí odkaz:
http://arxiv.org/abs/2102.09409
Autor:
Dumont, Gregory, Gutkin, Boris
Macroscopic oscillations of different brain regions show multiple phase relationships that are persistent across time and have been implicated routing information. Various cellular level mechanisms influence the network dynamics and structure the mac
Externí odkaz:
http://arxiv.org/abs/1812.03455
Autor:
Dumont, Grégory, Gabriel, Pierre
Publikováno v:
Nonlinearity, 2020, 33 (12), pp.6381-6420
Neural network dynamics emerge from the interaction of spiking cells. One way to formulate the problem is through a theoretical framework inspired by ideas coming from statistical physics, the so-called mean-field theory. In this document, we investi
Externí odkaz:
http://arxiv.org/abs/1710.05596
One of the most important challenges in mathematical neuroscience is to properly illustrate the stochastic nature of neurons. Among different approaches, the noisy leaky integrate-and-fire and the escape rate models are probably the most popular. The
Externí odkaz:
http://arxiv.org/abs/1702.01391
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Identifying the right tools to express the stochastic aspects of neural activity has proven to be one of the biggest challenges in computational neuroscience. Even if there is no definitive answer to this issue, the most common procedure to express t
Externí odkaz:
http://arxiv.org/abs/1602.03764
Providing an analytical treatment to the stochastic feature of neurons' dynamics is one of the current biggest challenges in mathematical biology. The noisy leaky integrate-and-fire model and its associated Fokker-Planck equation are probably the mos
Externí odkaz:
http://arxiv.org/abs/1512.03785
Autor:
Dumont, Grégory
Ce travail de thèse concerne la modélisation mathématique et l’étude du comportement d’une population de neurones. Dans tout ce travail on s’arrêtera principalement sur une population de neurones auto-excitateurs où chaque cellule du rés
Externí odkaz:
http://www.theses.fr/2012BOR14601/document
Akademický článek
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