Individual decision-making and collective animal behavior
12m 45s
This episode of Science Sessions explores recent advances in understanding collective animal behaviors, moving beyond traditional physics-based models that treat animals as simple particles. Researchers now incorporate cognitive processes—how individuals perceive, process, and decide—to explain emergent group patterns. Connor Hines’ model shows that cognitive agents can replicate natural behaviors like directed motion and milling, and respond to threats such as predators, which older models fail to do. Physical boundaries, studied by Aivakansso, lead to surprising behaviors like double milling, where fish schools split into two rotating groups. Speed influences social dynamics: fish preferentially follow faster neighbors, likely because they carry more urgent information. Ant colonies collectively evacuate at high temperatures, with colony size affecting the threshold. Starlings save energy by flying in optimal positions relative to neighbors, even in chaotic flocks. Weaver ants use visual cues to decide chain length, avoiding risky gaps. False alarms in fish are minimized by adjusting sensitivity to social cues based on group size and speed. However, not all group movement is collective; hermit crabs show individual autonomy despite moving together. Overall, considering individual cognition and environmental factors enriches our understanding of how complex group behaviors emerge.
[Music] A swarm of ants, a flock of birds, and a school of fish are all examples of collective behavior and animals. These complex behaviors emerge without any clear leader as animals respond to the environment and movements of their neighbors. I'm Matthew Hardcastle, and in this episode of Science Sessions, we'll explore advances in the understanding of collective animal behaviors. Animals in a group have traditionally been modeled as particles, influenced by physical forces. While these simple models can successfully reproduce many natural behaviors, they provide little insight into how the decision making processes of individual animals influences the actions of the collective. In a recent PNES article, Connor Hines, a machine learning researcher, advises AI, a cognitive computing company in Canada, and the Max Planck Institute of Animal Behavior in Germany and his colleagues incorporated cognitive processes into a model of collective behavior. In our model, we actually consider each little particle in, say, a school of moving fish or flocking birds. We imagine that they're an agent that's actually undergoing a process of ingesting sensations, doing some cognitive processing on their sensations, on their perceptions, and then taking decisions to act. What you can quickly reveal is that these agents are capable of the exact same kind of collective patterns of motion that we see in the earlier physics-based models. Things like directed motion where all the agents start moving together, you also see milling where they're kind of moving with high angular momentum around some center of mass. Now we can also control and understand the actual causes of these behaviors more from a cognitive level. Let's say one individual at the edge of the school is suddenly informed about the presence of a rapidly approaching predator. Then often with the older self-propelled particle models, the rest of the school will not be able to respond in time. Only agents that are in doubt with this ability to update their beliefs about the statistics of the environment are able to sensitively respond to fluctuations. Classical models often place particle-like animals on undefined planes, but physical boundaries are a facet of both laboratory settings and the natural world. In another PNAS article, Aivakansso, a mechanical engineer at the University of Southern California in Los Angeles, inter-colleagues analyzed how confinement influences collective behavior. The immediate behavior that occurs when you add confinement will they go around the tank wall. Now super surprising, but it's good that the model reproduces experimental observations. The double milling was very surprising because now the school kind of splits randomly into two groups, maybe 60% of them will go in one direction and the other 40% will go in the opposite direction. It has been observed experimentally that with a group of fish put in a tank with geometric confinement, they had seen this ability to switch back and forth between schooling and knitting. What we see from the model is the emergent behavior at the collective level that is switching back and forth without requiring changes in how the individual responds to its neighbor. We could speculate that maybe this could be useful for a group of fish that could transition its behavior from exploring the environment, going around seeing what's out there and then coming back and going into those milling states. Apart from the physical environment, animals in a group are also influenced by the movements of their immediate neighbors. In a PNAS article on Dre Upui, a physicist at the Polytechnic University of Catalonia in Spain and his colleagues consider the role of speed and the leader follow dynamics of schooling fish. When you speech of the species Blackneon tetra, which is a small freshwater species, we recorded the movements with an overhead camera. Then we digitized the trajectories, we found a pattern where fish appeared to line only with faster neighbors and ignore slower neighbors. Additionally, we analyzed leader follow-aware relationships in the experimental data and demonstrated that faster neighbors transmitted information about their direction and speed to slower neighbors. There are several biological reasons why fish might pay more attention to faster moving neighbors. First, focusing on quicker neighbors can reduce the cognitive flow of fish, allowing them to simplify their decision making. Second, leave faster fish often carry more relevant information. Fish that speed up might be responding to an urgent situation such as the presence of a predator for discovery of food. In addition to visual stimuli, animals perceive a variety of sensations from their environment that can influence their individual and collective decision making. In another PNAS article, Daniel Cronauer, an evolutionary biologist at Rockefeller University in New York and his colleagues explored "Hallic colony of clonal radar ants" collectively responds to rising temperatures. The answer usually is settled by default, right? They form a pretty dense nest cluster. There's always a few ants that kind of explore the arena. Then when you increase the temperature, you'll see that the ants start to move around. They become restless inside the nest cluster. And then at some point, when the temperature becomes too high, you'll see that there's some kind of collective decision emerging in which all the ants decide to pack up and move to nest somewhere else. It's a collective response in the sense that the ants are highly correlated in their response. It's an all-or-nothing response. Either the colony evacuates to nest or they don't evacuate to nest. When they evacuate to nest, they all move in the same direction. The larger the colony sizes, the higher the temperature of the elevation it has to be in order to make the ant colony evacuate in a collective way. So there seems to some kind of balance between the temperature that the ants perceive and then the kind of settling on the "hibitory force" that scales what the colony says. Moving in a group provides several benefits to individual animals, such as defense from predators. Birds flying in a V formation also save on energy expenditures due to aerodynamic forces. In a recent PNAS article, Sanya Freeman, an environmental physicist at Lund University in Sweden, and her colleagues quantified the energy savings of starlings, which fly in more complex formations. So starlings obviously don't fly in V formation. They fly in much larger flocks, like up to a few thousand birds. And to the undrained eye, they actually look very chaotic. We used the wind tunnel where we had two or three birds flying at the same time. We had a camera set up around the wind tunnel to get their positions and their location relative to each other. We had a little backpack on the birds that was measuring their acceleration. We also measured their metabolic cost. They had a very dynamic way of flying together. They didn't fly at the same spots as if they would be flying alone, which we also tested with each other. They were actually in average finding this V formation. So they found a spot relative to the bird that was flying in front of them that they like to fly at. We also found that the birds that flew in this position actually were using less energy than if they were flying alone. Another example of collective behavior, some ants species formed structures out of the living bodies of individual ants. In a PNAS article, Danielle Kilesso, a behavioral biologist at the University of Constance in Germany and his colleagues modeled how weaver ants decide to form chains to explore their environment. We essentially modeled the chain as being a a a simple structure composed of the number of fence joining the chain, minus the number of fence living it. They seem to join at quite a fixed rate, but instead they are modulating the probability of living. So when they are farther away from the ground, they seem to live more often. And so seems to stop building chains over gaps above nine centimeters and length. This seems to be modulated by the visual stimuli that the ants perceive at the end of the chain. By adding that this individual decision so together, the ants can actually reach a tradeoff between building the chain or not depending on the cost and benefit that the structure provides. We built a very simple apparatus in which the ants tried to reach a little platform that was put on a microscope slider. We could lower the platform as the chain grew. So the ants arriving at the end of the chain were always thinking that they were very close to the ground. Through this mechanism, we could actually trick the ants into building very long chains, even 12.5 centimeters long. By observing their neighbors, animals in a group can extend their own sensory perceptions. However, if one animal perceives a threat where there is none, a false alarm can quickly spread. In another PNAS article, Ash Khan Fahimipur, a community ecologist at Florida Atlantic University in Boca Ratan, and his colleagues explored how refish minimized the spread of misinformation. Really, really common form of misinformation that these animals experience are false alarms. How do animals usually respond to true threats, but avoid making these false alarms? We had to know what these animals were taking in in the first place from their sensory systems. We actually employed this algorithm to reconstruct the first person view from our overhead cameras. When we look at our cameras from across these coral reefs, we see that these false alarm events are basically happening all of the time. Almost always, these mistakes that propagate spread to a really small number of fish. These animals are sensitive to information that they get from their social ties, but they're tuning this sensitivity up and down depending on what's happened.
in the environment. They're tuning their sensitivity to social information way down when their groups just get too large and things are moving too fast. Sometimes animals that appear to be moving as a collective are not actually responding to their neighbors. An article published in scientific reports, Clare Doherty, an evolutionary ecologist at Oldstore University in Ireland, and her colleagues explored the individualism of terrestrial hermit crabs moving in groups. The species that we conducted this study and was seen a beta compressive. They had a dealing migrations from the forest down to the beach front in the early morning to eight and fourage. We were able to physically form sham aggregations of these groups. We used 60 shells which have been used as proxies and we were able to attach 60 standings for our crabs to clear fishing lengths that we've been pulled synchronously in one direction down the beach. We viewed the experiments overhead by a drawing. We would measure the starting point of or focal individual and the end point to get the direction that they traveled with respect to the direction of the synchronously moving group. What we find from these experiments is that surprisingly the group didn't bias the direction of the individual. The interesting thing about this species is that they do live in these portable shells and therefore grants them a certain level of autonomy in their movement. The individual decisions made by animals can produce complex, emergent behaviors at the group level considering the cognitive processes of individual animals can enhance our understanding of these fascinating behaviors. Thanks for tuning in to science sessions. If you liked this episode please consider leaving a review and helping us spread the word. [Music]
Podcast Summary
Key Points:
Traditional physics-based models of collective animal behavior treat animals as particles but fail to explain how individual cognitive decision-making influences group actions.
Connor Hines and colleagues developed a model incorporating cognitive processes (sensation, perception, decision-making) that reproduces collective patterns like directed motion and milling, and allows groups to respond to threats like predators.
Physical boundaries (confinement) can cause unexpected behaviors, such as fish schools splitting into two milling groups, as shown by Aivakansso and colleagues.
Fish (Blackneon tetra) preferentially align with faster neighbors, which may reduce cognitive load and convey urgent information (e.g., predators or food).
Ant colonies exhibit collective evacuation decisions in response to rising temperatures, with larger colonies requiring higher temperatures to trigger evacuation.
Starlings flying in complex formations gain energy savings by finding optimal positions relative to neighbors, similar to V-formation benefits.
Weaver ants modulate chain-building decisions based on perceived distance to the ground, using visual cues to balance costs and benefits.
False alarms in fish groups are minimized by tuning sensitivity to social information based on group size and environmental context.
Terrestrial hermit crabs moving in groups show no collective bias; individuals maintain autonomy due to their portable shells.
Summary:
This episode of Science Sessions explores recent advances in understanding collective animal behaviors, moving beyond traditional physics-based models that treat animals as simple particles. Researchers now incorporate cognitive processes—how individuals perceive, process, and decide—to explain emergent group patterns. Connor Hines’ model shows that cognitive agents can replicate natural behaviors like directed motion and milling, and respond to threats such as predators, which older models fail to do.
Physical boundaries, studied by Aivakansso, lead to surprising behaviors like double milling, where fish schools split into two rotating groups. Speed influences social dynamics: fish preferentially follow faster neighbors, likely because they carry more urgent information. Ant colonies collectively evacuate at high temperatures, with colony size affecting the threshold.
Starlings save energy by flying in optimal positions relative to neighbors, even in chaotic flocks. Weaver ants use visual cues to decide chain length, avoiding risky gaps. False alarms in fish are minimized by adjusting sensitivity to social cues based on group size and speed.
However, not all group movement is collective; hermit crabs show individual autonomy despite moving together. Overall, considering individual cognition and environmental factors enriches our understanding of how complex group behaviors emerge.
FAQs
Collective behavior in animals, such as swarms of ants, flocks of birds, and schools of fish, involves complex group actions that emerge without a clear leader, as animals respond to their environment and neighbors.
Cognitive models treat individual animals as agents that process sensations and make decisions, revealing collective patterns like directed motion and milling, and providing insights into how cognitive processes influence group actions.
Confinement can lead to behaviors like swimming along tank walls or double milling, where the school splits into two groups moving in opposite directions, and can cause switching between schooling and milling without changes in individual responses.
Fish focus on faster neighbors to reduce cognitive load and because faster fish often carry relevant information about urgent situations like predators or food, allowing for efficient information transfer.
Ant colonies exhibit an all-or-nothing evacuation response when temperatures become too high, with larger colonies requiring higher temperatures to trigger collective movement, balancing perceived temperature with inhibitory forces.
Starlings flying in complex formations, like V-shaped positions relative to others, use less energy than flying alone, as measured by metabolic cost and acceleration in wind tunnel experiments.
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