Navigating the Space of Collective Transitions in Biology and Society

This working group explores how systems ranging from neural networks to fish schools and human organizations shift between uncertain states and symmetry-broken decision states. These transitions, often driven by collective dynamics among individual units (e.g., neurons, cells, animals), are thought to enhance adaptability and computational power in biological systems. Characterizing such transitions becomes an essential ingredient in understanding the evolution and regulation of collective behavior, with important implications for the function of these systems and for scientists who aim to build parsimonious models of the systems. 

Despite their promise, the theoretical foundation for collective transitions in living systems remains fragmented. Existing frameworks—statistical physics' phase transitions and dynamical systems’ bifurcations—do not fully accommodate the stochastic, heterogeneous, and out-of-equilibrium nature of biological systems. The workshop will tackle both theoretical and experimental challenges, such as examining the functional consequences of different types of transitions (continuous, discontinuous, local, global), methods for identifying transition types from empirical data, and developing experimental systems that optimally test theoretical predictions. Participants will also discuss how systems tune and regulate these transitions, how to test the predictions of theoretical models of transitions, the role of decentralized control, and whether a generalized concept of universality might apply to collective transitions.