Collective Information Processing - From Individual Sensory Inputs to Collective Motion and Decision Making

• Applicant: Dr. Pawel Romanczuk
• Subject Area: Statistical Physics, Nonlinear Dynamics, Complex Systems, Soft and Fluid Matter, Biological Physics ; Bioinformatics and Theoretical Biology ; Human Cognitive and Systems Neuroscience
• Term: from 2016 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 280037999

The main objective of the project is the development and analysis of new individual-based mathematical models of collective motion, which explicitly take sensory perception into account, as the proximate mechanism of social interactions. This approach represents a paradigm change with respect to the currently dominating social-force models. These models are typically restricted to the modeling of specific experimental observations by a corresponding choice of interactions and parameters and have often only limited predictive power with respect to changes of the experimental system. A possible reason for this may be the insufficient foundation of these pairwise social forces in the sensory perception of individuals. Using our modeling approach, we aim at a systematic investigation of the possibilities and limitations of sensory perception on information transfer within animal groups, to enhance our understanding of natural collective behavior and develop models with enhanced predictive capabilities. The project has a theoretical focus on modeling, mathematical analysis, and numerical simulations. However, it shall be closely integrated with empirical research of our collaborators on two experimental model systems: desert locusts and fish (guppies/golden shiners). The project is structured in two parts: (I) Emergence of collective motion via visual perception, and (II) Collective decision making under sensory constraints. For the first part, desert locusts will be the primary experimental system, and our long term aim is to develop a mathematical model, which explicitly incorporates neuronal processing of visual social stimuli. The second part focuses on biologically functional behavior of collective decision making with fish as the model organism. Here, the central question is how near-optimal and robust collective decision making emerges despite sensory constraints. Our research will provide important contribution to the understanding of collective behavior, reveal corresponding evolutionary adaptations, and establish new interdisciplinary connections to other fields such as robotics.

• DFG Programme: Independent Junior Research Groups
• Cooperation Partner: Professor Iain Couzin, Ph.D.