Algorithms of information transfer between zebrafish individuals: from perceptual decisions to collective behavior

Rapid information exchange between individuals is key to coordinated behavior.

In a traffic lane, a well-timed brake can signal the presence of an obstacle to the drivers behind, avoiding a vehicle pileup. In a crowd of people, individuals can infer the position of an obscured exit from the movement of their neighbors. How do individual behavioral patterns enable efficient information transfer in a group?

Animal biodiversity displays a vast amount of remarkable collective phenomena that can provide us insight into this question, such as the behavior of fish schools, manifesting almost instantaneous information transfer between individuals.

The INTERZEB project will use zebrafish as a model system to experimentally establish the behavioral algorithms that enable individuals to transmit information within a group.

By employing immersive virtual reality techniques for freely-swimming fish, the project will pursue two objectives:1) Extracting the functions that enable information transfer from individuals in the front (leaders) to those in the back (followers) arranged in long transmission chains.2) Establishing how information transfer in the above settings is modulated by feedback sent by followers to leaders.The resulting algorithms will be implemented in agent-based models and tested in collective simulations as well as in hybrid interactions between multiple fish and algorithm-controlled virtual avatars.

The achievement of the projects objectives will provide a substantial contribution to linking individual decision-making and collective animal behavior, will foster interdisciplinary exchange, and will offer potential inspiration for biomimetic technologies.

The project will also strongly contribute to the Researchers professional growth by granting interdisciplinary training, leadership, and mastering of cutting-edge methodologies for the study of behavior.