G. Theraulaz

Cooperation and deception through stigmergic interactions in human groups

The paper investigates how human groups use stigmergic interactions in a rating system to find hidden values, finding cooperation and deception in competitive settings.

Tuning social interactions' strength drives collective response to light intensity in schooling fish

This study shows that varying light intensity affects social interactions and collective behavior in schooling fish by altering their responses to obstacles and group motion patterns.

Predicting long-term collective animal behavior with deep learning

This paper introduces a deep learning model to predict long-term collective behavior in fish and compares it to analytical models and experiments.

Computational modelling of cell motility modes emerging from cell-matrix adhesion dynamics

This paper develops a computational model to simulate how extracellular matrix composition affects lymphocyte motility patterns through cell-matrix adhesion dynamics.

The impact of individual perceptual and cognitive factors on collective states in a data-driven fish school model

This paper uses a data-driven fish school model to study how perceptual and cognitive factors affect collective swimming patterns in Hemigrammus rhodostomus, finding that minimal alignment and attraction are required for schooling, and that stronger interactions or larger group sizes can disrupt coordination.

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.

Computational and robotic modeling reveal parsimonious combinations of interactions between individuals in schooling fish

The paper uses computational and robotic models to show that fish schools maintain cohesion with minimal neighbor interaction, specifically by responding to the most influential neighbor.

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.