Collective decision-making in biological systems requires all individuals in the group to go through a behavioural change of state. During this transition fast and robust transfer of information is essential to prevent cohesion loss. The mechanism by which natural groups achieve such robustness, though, is not clear. Here we present an experimental study of starling flocks performing collective turns. We find that information about direction changes propagates across the flock with a linear dispersion law and negligible attenuation, hence minimizing group decoherence. These results contrast starkly with current models of collective motion, which predict diffusive transport of information. Building on spontaneous symmetry breaking and conservation laws arguments, we formulate a new theory that correctly reproduces linear and undamped propagation. Essential to the new framework is the inclusion of the birds’ behavioural inertia. The new theory not only explains the data, but also predicts that information transfer must be faster the stronger the group’s orientational order, a prediction accurately verified by the data. Our results suggest that swift decision-making may be the adaptive drive for the strong behavioural polarization observed in many living groups.

Collective behaviour is a widespread phenomenon in biology, cutting through a huge span of scales, from cell colonies up to bird flocks and fish schools. The most prominent trait of collective behaviour is the emergence of global order: individuals synchronize their states, giving the stunning impression that the group behaves as one. In many biological systems, though, it is unclear whether global order is present. A paradigmatic case is that of insect swarms, whose erratic movements seem to suggest that group formation is a mere epiphenomenon of the independent interaction of each individual with an external landmark. In these cases, whether or not the group behaves truly collectively is debated. Here, we experimentally study swarms of midges in the field and measure how much the change of direction of one midge affects that of other individuals. We discover that, despite the lack of collective order, swarms display very strong correlations, totally incompatible with models of non-interacting particles. We find that correlation increases sharply with the swarm's density, indicating that the interaction between midges is based on a metric perception mechanism. By means of numerical simulations we demonstrate that such growing correlation is typical of a system close to an ordering transition. Our findings suggest that correlation, rather than order, is the true hallmark of collective behaviour in biological systems.

Recent experiments with self-phoretic particles at low concentrations show a pronounced dynamic clustering [I. Theurkauff et al., Phys. Rev. Lett. 108, 268303 (2012)]. We model this situation by taking into account the translational and rotational diffusiophoretic motion, which the active particles perform in their self-generated chemical field. Our Brownian dynamics simulations show pronounced dynamic clustering only when these two phoretic contributions give rise to competing attractive and repulsive interactions, respectively. We identify two dynamic clustering states and characterize them by power-law-exponential distributions. In case of mere attraction a chemotactic collaps occurs directly from the gas-like into the collapsed state, which we also predict by mapping our Langevin dynamics on the Keller-Segel model for bacterial chemotaxis.The collective motion of self-propelling objects is a most fascinating subject which has been studied in a variety of systems [1,2]. At the macroscale, collective patterns occur, for example, in flocks of birds or fish schooles [3][4][5] while at the microscopic scale bacterical cells in an aqueous environment generate intricate motional patterns [6][7][8]. To understand basic features of structure formation in non-equilibrium, systems with spherical or circular microswimmers are investigated. A number of theoretical and experimental studies have demonstrated that activity of microswimmers alone can result in clustering and phase separation [9-17] due to reduced motility in dense aggregates [9,15]. However, the colloidal density has to be large enough that the characteristic time for a particle to join a cluster becomes comparable to its rotational diffusion time needed to dissolve from it [13]. Other investigations explore the influence of hydrodynamics on collective motion [18][19][20][21][22][23][24].In experiments with dilute suspensions of self-phoretic active Janus colloids, dynamic clustering has been observed [25,26]. In this novel non-equilibrium phenomenon, particles constantly join and leave clusters which exhibit a very dynamic shape. [7,29,30,32].Recent theoretical and experimental studies included short-range attraction between active colloids and observed clustering at low colloidal densities [26,[33][34][35].Ref.[36] implements diffusiophoresis for concrete surface properties of self-phoretic colloids and indentifies various states such as clumping and asters.The work presented here has very much been inspired by the experiments of the Lyon group [25]. The diffusiophoretic interaction has a translational and orientational contribution. Using Brownian dynamics simulations, we demonstrate that pronounced dynamic clustering occurs only when these two contributions give rise to competing attractive and repulsive interactions, respectively. We identify two dynamic clustering states and characterize them. Otherwise, in case of mere attraction a chemotactic collaps occurs directly from the gas-like state before pronounced clusters are able to form. We support this...