Abstract
Animals rely on movement to efficiently locate essential resources—such as food, mates, or nesting sites—for survival and reproduction. Over millions of generations, natural selection has refined neural algorithms guiding these movements to ensure reliability and efficiency. My research focuses on identifying and analysing such functional movement algorithms, particularly the mechanisms underlying decision-making and spontaneous search behaviours. Specifically, I study how ring attractor neural networks can integrate spatial information, support adaptive decision-making, and generate exploratory patterns. To test and refine this theoretical framework, I conduct experiments where real ants interact with virtual environments, effectively playing video games designed to probe their spatial decision-making processes.
About the speaker
August Paula is a researcher at the Department of Collective Behavior, Max Planck Institute of Animal Behavior and the University of Konstanz. His research explores emergent patterns in animal movement by developing virtual reality systems for insects and computer vision algorithms for wildlife videography.