G
F
Last name: GRAMMONT
First name: Franck
Email: Franck.GRAMMONT@univ-cotedazur.fr
Institution: UCA
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International audience
International audience
International audience
En neurosciences, le principal objet d'étude est le train de spike car il est considéré comme le vecteur principal de transmission de l'information de l'activité cérébrale. Au fil des différentes études, plusieurs modélisations pour les trains de spikes ont été proposées, plus pour des raisons biologiques que mathématiques. Nous proposons ici...
En neurosciences, le principal objet d'étude est le train de spike car il est considéré comme le vecteur principal de transmission de l'information de l'activité cérébrale. Au fil des différentes études, plusieurs modélisations pour les trains de spikes ont été proposées, plus pour des raisons biologiques que mathématiques. Nous proposons ici...
When dealing with classical spike train analysis, the practitioner often per-forms goodness-of-fit tests to test whether the observed process is a Poisson process, for instance, or if it obeys another type of probabilistic model (Yana et al. in Bio-phys.. In doing so, there is a fundamental plug-in step, where the parameters of the supposed...
The Unitary Events (UE) method is one of the most popular and efficient methods used this last decade to detect patterns of coincident joint spike activity among simultaneously recorded neurons. The detection of coincidences is usually based on binned coincidence count (Grün, 1996), which is known to be subject to loss in synchrony detection...
This article is threefold: (i) we define the first formal framework able to model dendritic integration within biological neurons, (ii) we show how we can turn continuous time into discrete time consistently and (iii) we show how a Lustre model checker can automatically perform proofs about neuron input/output behavioursowing to our...
We firstly define an improved version of the spiking neuron model with dendrites introduced in [8] and we focus here on the fundamental mathematical properties of the framework. Our main result is that, under few simplifications with respect to biology, dendrites can be simply abstracted by delays. Technically, we define a method allowing to...
When dealing with classical spike train analysis, the practitioner often performs goodness-of-fit tests to test whether the observed process is a Poisson process, for instance, or if it obeys another type of probabilistic model. In doing so, there is a fundamental plug-in step, where the parameters of the supposed underlying model are...
When dealing with classical spike train analysis, the practitioner often performs goodness-of-fit tests to test whether the observed process is a Poisson process, for instance, or if it obeys another type of probabilistic model. In doing so, there is a fundamental plug-in step, where the parameters of the supposed underlying model are...
The Unitary Events (UE) method is one of the most popular and efficient methods used this last decade to detect patterns of coincident joint spike activity among simultaneously recorded neurons. The detection of coincidences is usually based on binned coincidence count (Grün, 1996), which is known to be subject to loss in synchrony detection...
There exists many ways to connect two, three or more neurons together to form different graphs. We call archetypes only the graphs whose properties can be associated with specific classes of biologically relevant structures and behaviors. These archetypes are supposed to be the basis of typical instances of neuronal information ...
There exists many ways to connect two, three or more neu-rons together to form different graphs. We call archetypes only the graphs whose properties can be associated with specific classes of biologically relevant structures and behaviors. These archetypes are supposed to be the basis of typical instances of neuronal information processing. To...
In the literature, neuronal networks are often represented as graphs where each node symbolizes a neuron and each arc stands for a synaptic connection. Some specific neuronal graphs have biologically relevant structures and behaviors and we call them archetypes. Six of them have already been characterized and validated using formal methods. In...
Usual Parallel Discrete Event System Specification (P-DEVS) allows specifying systems from modeling to simulation. However, the framework does not incorporate parallel and stochastic simulations. This work intends to extend P-DEVS to parallel simulations and pseudorandom number generators in the context of a spiking neural network. The discrete...
Having a formal model of neural networks can greatly help in understanding and verifying their properties, behavior, and response to external factors such as disease and medicine. In this paper, we adopt a formal model to represent neurons, some neuronal graphs, and their composition. Some specific neuronal graphs are known for having...
During cortical development, the identity of major classes of long-distance projection neurons is established by the expression of molecular determinants, which become gradually restricted and mutually exclusive. However, the mechanisms by which projection neurons acquire their final properties during postnatal stages are still poorly...
During cortical development, the identity of major classes of long-distance projection neurons is established by the expression of molecular determinants, which become gradually restricted and mutually exclusive. However, the mechanisms by which projection neurons acquire their final properties during postnatal stages are still poorly...