Shpurov Ivan, Froese Tom
Embodied Cognitive Science Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa 904-0495, Japan.
Entropy (Basel). 2022 Dec 17;24(12):1840. doi: 10.3390/e24121840.
Social insects such as honey bees exhibit complex behavioral patterns, and their distributed behavioral coordination enables decision-making at the colony level. It has, therefore, been proposed that a high-level description of their collective behavior might share commonalities with the dynamics of neural processes in brains. Here, we investigated this proposal by focusing on the possibility that brains are poised at the edge of a critical phase transition and that such a state is enabling increased computational power and adaptability. We applied mathematical tools developed in computational neuroscience to a dataset of bee movement trajectories that were recorded within the hive during the course of many days. We found that certain characteristics of the activity of the bee hive system are consistent with the Ising model when it operates at a critical temperature, and that the system's behavioral dynamics share features with the human brain in the resting state.
蜜蜂等群居昆虫表现出复杂的行为模式，它们的分布式行为协调能够在群体层面进行决策。因此，有人提出，对它们集体行为的高层次描述可能与大脑中神经过程的动态有共同之处。在这里，我们通过关注大脑处于临界相变边缘的可能性以及这种状态能够增强计算能力和适应性这一可能性来研究这一观点。我们将计算神经科学中开发的数学工具应用于在蜂巢内多天记录的蜜蜂运动轨迹数据集。我们发现，蜂巢系统活动的某些特征与伊辛模型在临界温度下运行时一致，并且该系统的行为动态与静息状态下的人类大脑具有共同特征。
