The Study Of Collective Bacterial Behavior Using Structural Sums

This paper builds upon and expands the research method presented in Ligocki (2024)(*) at the previous ECMS conference, offering an update on the current state of the study. It explores the challenges encountered by the author in selecting appropriate mathematical methods for image analysis and justifies these decisions through graphical visualizations. The article outlines the stages of development that led to the final choice of methods and algorithms. Compared to the previous article, the current results show greater promise, offering enhanced potential for high-quality analyses. In the earlier work, certain inaccuracies were identified, which were addressed in subsequent discussions and consultations after the ECMS 2024 presentation. The paper introduces a novel quantitative criterion for detecting collective behavior in bacteria, based on a robust computational theory known as aRVE, which leverages structural sums. Application of this criterion to both simulated and experimental data on Bacillus subtilis reveals significant differences, underscoring the presence of collective motion in the bacteria. (*) Application of structural sums to study collective behavior of bacteria. European Council for Modelling and Simulation, 594:304– 409.