Ofer Feinerman's Lab

The physicality of the world in which the animal acts—its anatomical structure, physiology, perception, emotional states, and cognitive capabilities—determines the boundaries of the behavioral space within which the animal can operate. Behavior, therefore, can be considered as the subspace that remains after secluding all actions that are not available to the animal due to constraints. The very signature of being a certain creature is reflected in these limitations that shape its behavior. A major goal of ethology is to expose those constraints that carve the intricate structure of animal behavior and reveal both uniqueness and commonalities between animals within and across taxa. Exploratory behavior in an empty arena seems to be stochastic; nevertheless, it does not mean that the moving animal is a random walker. In this study, we present how, by adding constraints to the animal’s locomotion, one can gradually retain the ‘mousiness’ that characterizes the behaving mouse. We then introduce a novel phenomenon of high mirror symmetry along the locomotion of mice, which highlights another constraint that further compresses the complex nature of exploratory behavior in these animals. We link these findings to a known neural mechanism that could explain this phenomenon. Finally, we suggest our novel finding and derived methods to be used in the search for commonalities in the motion trajectories of various organisms across taxa.

Animal groups need to achieve and maintain consensus to minimise conflict among individuals and prevent group fragmentation. An excellent example of a consensus challenge is cooperative transport, where multiple individuals cooperate to move a large item together. This behavior, regularly displayed by ants and humans only, requires individuals to agree on which direction to move in. Unlike humans, ants cannot use verbal communication but most likely rely on private information and/or mechanical forces sensed through the carried item to coordinate their behaviour. Here we investigated how groups of weaver ants achieve consensus during cooperative transport using a tethered-object protocol, where ants had to transport a prey item that was tethered in place with a thin string. This protocol allows the decoupling of the movement of informed ants from that of uninformed individuals. We showed that weaver ants pool together the opinions of all group members to increase their navigational accuracy. We confirmed this result using a symmetry-breaking task, in which we challenged ants with navigating an open-ended corridor. Weaver ants are the first reported ant species to use a ‘wisdom of the crowd’ strategy for cooperative transport, demonstrating that consensus mechanisms may differ according to the ecology of each species.Competing Interest StatementThe authors have declared no competing interest.

Some ant species are known as efficient transporters that can cooperatively carry food items which would be too large for a single ant. Previous studies of cooperative transport focused on the role of individual ants and their behavioral rules that allow for efficient coordination. However, the resulting detailed microscopic description requires a numerical treatment in order to extract macroscopic features of the object's trajectory. Here, we instead treat the carried object as a single active swimmer whose movement is characterized by two variables: velocity amplitude and direction. We experimentally observe Paratrechina longicornis ants cooperatively transporting loads of varying sizes. By analyzing the statistical features of the load's movement, we show how the salient properties of the cooperative transport are encoded in its deterministic and random accelerations. We find that while the autocorrelation time of the velocity direction increases with group size, the autocorrelation time of the speed has a maximum at an intermediate group size, corresponding to the critical slow down close to the previously identified phase transition. Our statistical model for cooperative ant transport demonstrates that an active swimmer model can be employed to describe a system of interacting individuals.