论文标题
自适应流网络的记忆力
Memory capacity of adaptive flow networks
论文作者
论文摘要
生物流动网络适应其网络形态以优化流动，同时暴露于环境中不同空间位置的外部刺激。这些自适应流网络保留了网络形态中刺激位置的记忆。然而，什么限制了这种记忆以及可以存储多少刺激是未知的。在这里，我们通过随后应用多个刺激来研究自适应流动网络的数值模型。我们发现，很长一段时间以来，刺激的记忆信号很长一段时间。因此，网络可以存储许多刺激以用于中间刺激持续时间，这些刺激持续时间是平衡印记和老化的。
Biological flow networks adapt their network morphology to optimise flow while being exposed to external stimuli from different spatial locations in their environment. These adaptive flow networks retain a memory of the stimulus location in the network morphology. Yet, what limits this memory and how many stimuli can be stored is unknown. Here, we study a numerical model of adaptive flow networks by applying multiple stimuli subsequently. We find strong memory signals for stimuli imprinted for a long time into young networks. Consequently, networks can store many stimuli for intermediate stimulus duration, which balance imprinting and ageing.
