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Animal Behaviour


Collective decision making is essential for multicellular and self-organized society coordination, but how this occurs when most of the individuals have limited knowledge of the external environment remains elusive. Using empirical data to inform a neuroscience-based firing-rate model, we found that integration of negative feedback and network dynamics in a honeybee, Apis mellifera, hive demonstrates strong similarities to the neuronal interactions of the human brain, where very brief perturbations of feedback in the system result in more rapid and accurate decisions. We show that honey bees used an inhibitory ‘stop’ signal towards dancing honey bees that reduced both waggle dancing and waggle dance pheromone production. Stop signals were probably elicited by individuals with no individual knowledge of food quality change in the external environment. Therefore, we demonstrate that collective behaviour across different biological levels of organization exhibits a dynamic complex system that is self-organized, but is governed by simple feedback mechanisms, facilitating efficient group decision making by optimally aggregating individuals that have relatively limited cognitive capabilities within a society or cell in a multicellular organism. We discuss how despite being on two different levels of biological organization, both neurons in the brain and honeybee individuals, within the hive, can operate collectively, which is probably a result of convergent evolution.


balanced network theory, collective decision making, forager regulation, inhibitory feedback, stop signal, waggle dance


This work is a preprint that is freely available courtesy of Elsevier

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