Experiences of animal and human beings are structured by the continuity of space and time
coupled with the uni-directionality of time. In addition to its pivotal position in spatial …

The aim of the present paper is to study the effects of Hebbian learning in random recurrent
neural networks with biological connectivity, ie sparse connections and separate …

We study theoretically the dimensional crossover from a three-dimensional elongated
condensate to a one-dimensional condensate as the transverse degrees of freedom get …

This study presents experiments on the imitative interactions between a small humanoid
robot and a user. A dynamic neural network model of a mirror system was implemented in a …

In this letter we describe a hippocampo-cortical model of spatial processing and navigation
based on a cascade of increasingly complex associative processes that are also relevant for …

We present a framework based on iterative free-energy optimization with spiking neural
networks for modeling the fronto-striatal system (PFC-BG) for the generation and recall of …

This paper presents an overview of some techniques and concepts coming from dynamical
system theory and used for the analysis of dynamical neural networks models. In a first …

In order to keep trace of information and grow up, the infant brain has to resolve the problem
about where old information is located and how to index new ones. We propose that the …

We use dynamical neural networks based on the neural field formalism for the control of a
mobile robot. The robot navigates in an open environment and is able to plan a path for …

Abstract Spiking Neuron Networks (SNNs) are often referred to as the 3rd generation of
neural networks. They derive their strength and interest from an accurate modelling of …