V. Lecheval

Random walks with spatial and temporal resets may underlie searching movements in ants

The paper models ant foraging movements using a random walk with stochastic resetting and finds that the probability of returning to the nest decreases with more foraging trips.

Smart self-propelled particles: a framework to investigate the cognitive bases of movement

The paper presents a framework using artificial neural networks and genetic algorithms to study spatial decision-making in agents learning to explore an environment without leaving its boundaries.

Conditioning a collective avoidance response in rummy-nose tetra

This study conditions a collective avoidance response in rummy-nose tetra using a shuttle box paradigm with green light, showing successful aversive conditioning, collective escape reactions, and transferability to new environments.

A data-driven method for reconstructing and modelling social interactions in moving animal groups

The paper introduces a data-driven method to reconstruct social interactions in moving animal groups and applies it to shoaling fish to create predictive models of collective behavior.

Domino-Like Propagation Of Collective U-Turns In Fish Schools

The paper studies collective U-turns in fish schools, showing that speed decreases trigger these events, which propagate like dominoes and are modeled using an Ising spin model.