After a short review of biologically inspired navigation architectures, mainly relying on
modeling the hippocampal anatomy, or at least some of its functions, we present a …

In this paper, we present a model for the generation of grid cells and the emergence of place
cells from multimodal input to the entorhinal cortex (EC). In this model, grid cell activity in the …

This article presents a bio-inspired neural network providing planning capabilities in
autonomous navigation applications. The proposed architecture (hippocampus model) …

This article investigates how a motivational module can drive an animat to learn a
sensorimotor cognitive map and use it to generate flexible goal-directed behavior. Inspired …

In this paper, we present two graphical softwares which help the modeling and the
simulation of real time, distributed neural networks (NNs). Used in the frame of the …

It is believed that humans and animals like rodents and bats navigate in a familiar
environment using a cognitive map. Yet, how maps are previously learned when exploring a …

Humans and animals are able to flexibly learn internal, cognitive maps of their environments
and are able to use these maps to approach goals efficiently, reliably, and flexibly. Recent …

For the last decade, we have developed a bio-inspired control architecture for the
autonomous navigation of mobile robots. The robot is able to learn to reproduce a homing or …

Although hippocampal grid cells are thought to be crucial for spatial navigation, their
computational purpose remains disputed. Recently, they were proposed to represent spatial …

Grid cells of the rodent entorhinal cortex are essential for spatial navigation. Although their
function is commonly believed to be either path integration or localization, the origin or …