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- G Dumont, J Henry, C O Tarniceriu
- Journal of mathematical biology
- 2016

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 most popular way to deal with neural variability. Another well-known formalism is the escape-rate model: a model… (More)

- Grégory Dumont, Jacques Henry
- Journal of mathematical biology
- 2013

In this paper we study the well-posedness of different models of population of leaky integrate-and-fire neurons with a population density approach. The synaptic interaction between neurons is modeled by a potential jump at the reception of a spike. We study populations that are self excitatory or self inhibitory. We distinguish the cases where this… (More)

- Grégory Dumont, Jacques Henry
- Bulletin of mathematical biology
- 2013

In this paper, we study the influence of the coupling strength on the synchronization behavior of a population of leaky integrate-and-fire neurons that is self-excitatory with a population density approach. Each neuron of the population is assumed to be stochastically driven by an independent Poisson spike train and the synaptic interaction between neurons… (More)

Population density models that are used to describe the evolution of neural populations in a phase space are closely related to the single neuron model that describes the individual trajectories of the neurons of the population and which give in particular the phase-space where the computations are made. Based on a transformation of the quadratic integrate… (More)

- Zirui Huang, Jianfeng Zhang, +8 authors Georg Northoff
- Cerebral cortex
- 2017

The aim of our study was to use functional magnetic resonance imaging to investigate how spontaneous activity interacts with evoked activity, as well as how the temporal structure of spontaneous activity, that is, long-range temporal correlations, relate to this interaction. Using an extremely sparse event-related design (intertrial intervals: 52-60 s), a… (More)

- Grégory Dumont, Georg Northoff, André Longtin
- Physical review. E, Statistical, nonlinear, and…
- 2014

Understanding neural variability is currently one of the biggest challenges in neuroscience. Using theory and computational modeling, we study the behavior of a globally coupled inhibitory neural network, in which each neuron follows a purely stochastic two-state spiking process. We investigate the role of both this intrinsic randomness and the conduction… (More)

- Grégory Dumont, Jacques Henry, Carmen Oana Tarniceriu
- Journal of theoretical biology
- 2016

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 this randomness is the use of stochastic models. In accordance with the origin of variability, the sources of… (More)

- Grégory Dumont, Georg Northoff, André Longtin
- Journal of Computational Neuroscience
- 2015

Gamma-band synchronization has been linked to attention and communication between brain regions, yet the underlying dynamical mechanisms are still unclear. How does the timing and amplitude of inputs to cells that generate an endogenously noisy gamma rhythm affect the network activity and rhythm? How does such ”communication through coherence” (CTC) survive… (More)

After all, variables are just name tags, and the same letter in different contexts may mean two very different things. Or you might want to represent the same thing by two different letters, depending on the situation in which you use it. But when it is clear from the context and from your definitions what exactly you are referring to, it is often… (More)

- Grégory Dumont, Alexandre Payeur, André Longtin
- PLoS computational biology
- 2017

Neural network dynamics are governed by the interaction of spiking neurons. Stochastic aspects of single-neuron dynamics propagate up to the network level and shape the dynamical and informational properties of the population. Mean-field models of population activity disregard the finite-size stochastic fluctuations of network dynamics and thus offer a… (More)