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Background: Recent research in animal behaviour has contributed to determine how alignment, turning responses, and changes of speed mediate flocking and schooling interactions in different animal species. Here, we address specifically the problem of what interaction responses support different nearest neighbour configurations in terms of mutual position and distance. Results: We find that the different interaction rules observed in different animal species may be a simple consequence of the relative positions that individuals assume when they move together, and of the noise inherent with the movement of animals, or associated with tracking inaccuracy. Conclusions: The anisotropic positioning of individuals with respect to their neighbours, in combination with noise, can explain several aspects of the movement responses observed in real animal groups, and should be considered explicitly in future models of flocking and schooling. By making a distinction between interaction responses involved in maintaining a preferred flock configuration, and interaction responses directed at changing it, we provide a frame to discriminate movement interactions that signal directional conflict from those underlying consensual group motion.
While a rich variety of self-propelled particle models propose to explain the collective motion of fish and other animals, rigorous statistical comparison between models and data remains a challenge. Plausible models should be flexible enough to capt
Collective movement can be achieved when individuals respond to the local movements and positions of their neighbours. Some individuals may disproportionately influence group movement if they occupy particular spatial positions in the group, for exam
Estimators for mutual information are typically biased. However, in the case of the Kozachenko-Leonenko estimator for metric spaces, a type of nearest neighbour estimator, it is possible to calculate the bias explicitly.
Real-time temperature monitoring inside living organisms provides a direct measure of their biological activities, such as homeostatic thermoregulation and energy metabolism. However, it is challenging to reduce the size of bio-compatible thermometer
We present a simple method based on the stability and duality of the properties of sampling and interpolation, which allows one to substantially simplify the proofs of some classical results.