15 Result(s)
within
Article
Luc Berthouze
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Article
Open AccessTowards Inferring Network Properties from Epidemic Data
Epidemic propagation on networks represents an important departure from traditional mass-action models. However, the high-dimensionality of the exact models poses a challenge to both mathematical analysis and ...
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Open AccessThe Impact of Contact Structure and Mixing on Control Measures and Disease-Induced Herd Immunity in Epidemic Models: A Mean-Field Model Perspective
The contact structure of a population plays an important role in transmission of infection. Many ‘structured models’ capture aspects of the contact pattern through an underlying network or a mixing matrix. An ...
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Article
Open AccessEpidemic threshold in pairwise models for clustered networks: closures and fast correlations
The epidemic threshold is probably the most studied quantity in the modelling of epidemics on networks. For a large class of networks and dynamics, it is well studied and understood. However, it is less so for...
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Open AccessEdge-Based Compartmental Modelling of an SIR Epidemic on a Dual-Layer Static–Dynamic Multiplex Network with Tunable Clustering
The duration, type and structure of connections between individuals in real-world populations play a crucial role in how diseases invade and spread. Here, we incorporate the aforementioned heterogeneities into...
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Article
Oscillating epidemics in a dynamic network model: stochastic and mean-field analysis
An adaptive network model using SIS epidemic propagation with link-type-dependent link activation and deletion is considered. Bifurcation analysis of the pairwise ODE approximation and the network-based stochasti...
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Open AccessBeyond clustering: mean-field dynamics on networks with arbitrary subgraph composition
Clustering is the propensity of nodes that share a common neighbour to be connected. It is ubiquitous in many networks but poses many modelling challenges. Clustering typically manifests itself by a higher tha...
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Open AccessIdentification of Criticality in Neuronal Avalanches: II. A Theoretical and Empirical Investigation of the Driven Case
The observation of apparent power laws in neuronal systems has led to the suggestion that the brain is at, or close to, a critical state and may be a self-organised critical system. Within the framework of sel...
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Open AccessIdentification of Criticality in Neuronal Avalanches: I. A Theoretical Investigation of the Non-driven Case
In this paper, we study a simple model of a purely excitatory neural network that, by construction, operates at a critical point. This model allows us to consider various markers of criticality and illustrate ...
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Open AccessAdaptive time-varying detrended fluctuations analysis: a new method for characterizing time-varying scaling parameters in physiological time series
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Open AccessDetecting the presence of long-range temporal correlations in a time-varying measure of phase synchrony
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Open AccessRole of three key developmental variables in the emergence of long-range temporal correlations in a network of spiking neurons without plasticity
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Open AccessRole of STDP and heterogeneity in the emergence of long-range temporal correlations and frequency scaling in networks of LIF neurons
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Article
A Neural Model for Context-dependent Sequence Learning
A novel neural network model is described that implements context-dependent learning of complex sequences. The model utilises leaky integrate-and-fire neurons to extract timing information from its input and m...
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Article
Emergence and Categorization of Coordinated Visual Behavior Through Embodied Interaction
This paper discusses the emergence of sensorimotor coordination for ESCHeR, a 4DOF redundant foveated robot-head, by interaction with its environment. A feedback-error-learning (FEL)-based distributed control ...
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Article
Emergence and Categorization of Coordinated Visual Behavior Through Embodied Interaction
This paper discusses the emergence of sensorimotor coordination for ESCHeR, a 4DOF redundant foveated rob ot-head, by interaction with its environment. A feedback-error-learning(FEL)-based distributed control ...
