The Burden of Alzheimer's Disease and Other Dementias Attribute to Metabolic Risks in Western Europe From 1990 to 2023.

Some of the most complex patterns of collective behavior in animals are displayed when groups are threatened by a predator. Rapid changes in shape and internal structure of the group confuse the predator and reduce the flock members’ risk of getting caught. The murmurations of European starlings () are one of the best-known phenomena of collective behavior; their large flocks exhibit a great diversity of complex patterns, in particular when attacked by aerial predators such as the peregrine falcon (). However, besides insight into the collective motion of their flocks, little is known about what rules of motion and interaction underlie their patterns of collective escape, knowledge that is vital to understand the adaptive value of these social interactions and the formation of the spatiotemporal patterns we observe in nature. In starlings, many patterns of collective escape can be distinguished based on shape, darkness, size, internal structure and dynamics of the flock (similar to other systems), namely the agitation wave, the vacuole, the flash expansion, the collective turn, the cordon, the split, blackening, compacting, and dilution. During an agitation wave, a dark band moves from one side of the flock (closer to the predator) to the other. During flash expansion, flock members suddenly move radially outwards (usually away from the attacking predator). The split implies that the flock divides into two or more parts, referred to as sub-flocks. During blackening, the flock (or part thereof) appears darker, and during compacting smaller. During dilution, the distance between flock members increases and the flock becomes lighter in color. The vacuole refers to a hole in a polarized flock with the individuals around the hole moving in the same direction, and the cordon to the thin line (cordon) that connects two relatively large parts of the flock. Earlier studies have only focused on the relation between the frequency of these patterns and the frequency and timing of predator attacks, without investigating the mechanisms driving their emergence. The link between individual behavior and global patterns can be detected through computational models based on self-organization although it is important to note that in a simulation, the same macroscopic patterns may emerge from different rules of individual behavior. There is thus no guarantee that models represent correctly individual behavior of animals in nature but they offer a theoretical understanding of what is possible given a set of assumptions. To increase the biological relevance of the theoretical predictions of a model, the local interactions and individual motion of simulated agents can be adjusted to empirical data. Model predictions can then in turn drive the collection of more empirical data in order to validate or challenge our theoretical understanding. In the case of collective motion, models usually include moving agents that align with and are attracted to each other while avoiding collisions (but see also). In these models, the emergence of several collective properties have been examined such as flock diffusion, milling, and flock shape.