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Small brains, complex challenges…

The superb navigational skills of ants and bees are proof that small brains can achieve amazingly efficient behaviours in complex environments. We seek to uncover the link between neural dynamics and behavioural decisions, when these insects navigate in their natural habitat. We focus on ant species that are champion visual navigators, who spontaneously learn long routes and home from distant locations. Actually, many ant species do so in various habitats!

We combine computational models based on the insect neural circuitry with behavioural experiments, whether directly in the field or in the lab where ants can navigate within Virtual Reality set-ups. The models enable to explore the complex relationship between the brain, body, and environment; and (hopefully) produce testable behavioural predictions. The behavioural experiments enable to test the models’ predictions, and (hopefully) unravel unsuspected abilities in these little creatures.


A treadmill for ants?!

Virtual Reality

Insects play videogames too…


The nerdy stuff


Field work

Every year, we try to do one or two trips to the field. April to July is the time to go to Seville to study desert ants (Cataglyphis velox). November to March is the time to go to Canberra to study various Aussie ants such as Jack Jumpers (Myremecia pyriformis) or meat ants (Iridiomyrmex purpureus). Field studies often means very long working days, but also lots of fun, and sometimes great discoveries. A vast amount of experiments can be achieved with just a tube, a pen and paper, although others may require more sophisticated equipment. In any case, it is definitely in the field that our research is the most productive. Observing our animal species in their natural environment is also a profound source of inspiration for future, ecologically relevant research questions. And most importantly, it’s a time to learn to better know each other and live a little adventure as a team.


One of our new gadgets! Developed mainly by Hansjuergen Dahmen. Instead of running after your ant, just grab it, attach it by a thread on the thorax and put it on a ball that is floating in the air. Then, when the ant tries to move, the ball turns, but she stays on the spot. That way, we can decouple the motor action from the expected visual feedback (feedback which is, in such case, static). This system has enabled us to ask novel questions about the ways ants process the world for navigation, some already published, and others to come. We are definitely not finished yet with this tool!

Virtual Reality

Once you have an ant running on a trackball, you can actually make it navigate in a virtual world. For that, what you need is a very good panoramic visual display all around the ant. One such display is currently in ANU, Canberra, within our collaborator Prof. Jochen Zeil’s group. It is a big display – more than a meter across, and composed of 20,000 LEDs including UV. The advantage in Canberra is that you can pick a wild ant right in front of your door, which is trained in the real world, and test it in the VR. We are also developing a second type of display using video-projectors in the university of Toulouse, in collaboration with Dr. Andrew Straw. This one is tuned for ants raised in the lab, whom we directly train to navigate in the VR. Needless to say, the VR system enables us to do any instantaneous transformation of the visual environment while the ant is navigating, so the number of possible questions to ask is vast!

Neural modelling

Our goal is to understand how the insect brain enables these little creatures to display such amazing navigational skills. But how can we formulate a hypothesis about brain mechanisms? Instead of using words, we are using neural models. We equip a simplified agent with one of our modelled brains, toss it in a 3D reconstructed ant world, and see how well it performs! One the one hand, our neural models are purely constrained by our actual knowledge of real insect circuits, and on the other hand, we compare the navigational behaviour outputted by the agent to the behaviour of real ants. That way, we hope to slowly refine our models, and thus understand some fundamental principles of how the insect brain works. Sometimes we use our models to try and explain a well-known behavioural feat, other times, we use it to predict the existence of a yet unobserved ability; which leads us straight back to the field. Here are some examples of published models.


Antoine Wystrach

CNRS Researcher, ERC PI

Trained as a biologist, I always wondered whether I preferred neuroscience or evolutionary biology. After a PhD spent outdoors studying ant navigation, I realised that striking a balance between these two research fields was actually possible, and fun! I further spent a few years in the UK as a postdoc modelling insects’ brain and behaviour and eventually got a research position in the CNRS. I now study ant navigation in both the lab and the field, using fancy tools such as VR, neural models and 3D worlds… or sometimes just using my hands to move an ant from A to B

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Google Scholar

Sebastian Schwarz

Postdoc, ERC funded

I am fascinated with all kinds of animal behaviour but predominantly I try to understand how insects with seemingly simple and small brains tackle behavioural problems in their natural environment. My main study animals are social Hymenoptera such as ants and bees. My experimental focus lies in visual navigation and spatial cognition plus their respective learning and memory processes. Currently, I try to combine behaviour field studies on the navigational abilities of desert ants with modern tracking methods and virtual reality devices. More precisely, I am investigating whether visual information derived during navigation can be transferred from the natural environment to the virtual reality and vice versa.

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Google Scholar

Léo Clément

PhD Student, ERC funded

I always liked to observe the behaviour of insect and animals in their natural environment. Recently I chose to focus on social Hymenoptera, such as bees, bumblebees, and some particular species of ants. More precisely I am interested in solitary foragers: they venture out of the nest alone and bring back the food items collected to their nest. They therefore need to have robust navigation mechanisms to ensure the sustainability of the colony. I wish to understand how their miniature brain solve the complex task of navigating in complex environments. Currently as a PhD student, I am using a trackball device to precisely record the motor movements of ant directly in their natural environment. I am also planning to use this trackball combined with a VR set up that allow me to “play” with the visual environment of the ant and thereby decode the sensory-motor rules based on the navigational behaviour.

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Erwan Tilly

Master2 Student

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Jessim Ahdjoudj

Master1 Student

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Previous team members

Florent Le Moël

PhD Student, ERC funded (2018-2021)

I have always been into both neurosciences and computing, and I realised during my Masters internship at the Biorobotics Lab (Edinburgh, Scotland) that insects were a perfectly suited model to link both my passions. Indeed, their tiny, super optimised brains can achieve many complex tasks with impressive accuracy, a statement which holds as a goal for many embedded / robotic applications. Similarly, building computational models of their brains allow us to understand how these animals tackle difficult environmentally-relevant challenges. In the Ant Navigation team, I combine neuroethological studies with desert ants directly in their environment, with computational modelling of visual navigation, and Virtual Reality in the lab.

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Blandine Mahot-Castaing

Undergrad and later Master2 student (2019 and 2021)

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Christelle Gassama (Undergrad internship 2019 and 2021)


Ant Navigation Team

Research Center on Animal Cognition – Center for Integrative Biology

Université Paul Sabatier – Bat. 4R3
710 cours Rosalind Franklin
118 route de Narbonne
31062 Toulouse cedex 09


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