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哺乳动物视交叉上核连接模式的进化限制

Evolutionary Constraints on Connectivity Patterns in the Mammalian Suprachiasmatic Nucleus.

作者信息

Spencer Connor, Tripp Elizabeth, Fu Feng, Pauls Scott

机构信息

Department of Mathematics, Dartmouth College, Hanover, NH, United States.

Department of Mathematics, Sacred Heart University, Fairfield, CT, United States.

出版信息

Front Netw Physiol. 2021 Aug 19;1:716883. doi: 10.3389/fnetp.2021.716883. eCollection 2021.

Abstract

The mammalian suprachiasmatic nucleus (SCN) comprises about 20,000 interconnected oscillatory neurons that create and maintain a robust circadian signal which matches to external light cues. Here, we use an evolutionary game theoretic framework to explore how evolutionary constraints can influence the synchronization of the system under various assumptions on the connection topology, contributing to the understanding of the structure of interneuron connectivity. Our basic model represents the SCN as a network of agents each with two properties-a phase and a flag that determines if it communicates with its neighbors or not. Communication comes at a cost to the agent, but synchronization of phases with its neighbors bears a benefit. Earlier work shows that when we have "all-to-all" connectivity, where every agent potentially communicates with every other agent, there is often a simple trade-off that leads to complete communication and synchronization of the system: the benefit must be greater than twice the cost. This trade-off for all-to-all connectivity gives us a baseline to compare to when looking at other topologies. Using simulations, we compare three plausible topologies to the all-to-all case, finding that convergence to synchronous dynamics occurs in all considered topologies under similar benefit and cost trade-offs. Consequently, sparser, less biologically costly topologies are reasonable evolutionary outcomes for organisms that develop a synchronizable oscillatory network. Our simulations also shed light on constraints imposed by the time scale on which we observe the SCN to arise in mammals. We find two conditions that allow for a synchronizable system to arise in relatively few generations. First, the benefits of connectivity must outweigh the cost of facilitating the connectivity in the network. Second, the game at the core of the model needs to be more cooperative than antagonistic games such as the Prisoner's Dilemma. These results again imply that evolutionary pressure may have driven the system towards sparser topologies, as they are less costly to create and maintain. Last, our simulations indicate that models based on the mutualism game fare the best in uptake of communication and synchronization compared to more antagonistic games such as the Prisoner's Dilemma.

摘要

哺乳动物的视交叉上核(SCN)由大约20000个相互连接的振荡神经元组成,这些神经元产生并维持一个与外部光信号相匹配的强大昼夜节律信号。在此,我们使用进化博弈论框架来探究在连接拓扑的各种假设下,进化约束如何影响系统的同步性,这有助于理解中间神经元连接的结构。我们的基本模型将SCN表示为一个由智能体组成的网络,每个智能体具有两个属性——一个相位和一个标志,该标志决定它是否与其邻居进行通信。通信对智能体来说是有成本的,但与其邻居的相位同步会带来好处。早期的研究表明,当我们有“全对全”连接时,即每个智能体都有可能与其他每个智能体进行通信,通常会有一个简单的权衡,导致系统完全通信和同步:好处必须大于成本的两倍。这种全对全连接的权衡为我们在研究其他拓扑时提供了一个比较基准。通过模拟,我们将三种合理的拓扑与全对全情况进行比较,发现在相似的收益和成本权衡下,所有考虑的拓扑中都会出现向同步动态的收敛。因此,对于发育出可同步振荡网络的生物体来说,更稀疏、生物学成本更低的拓扑是合理的进化结果。我们的模拟还揭示了我们观察到哺乳动物中SCN出现的时间尺度所施加的约束。我们发现了两个条件,使得在相对较少的几代中就能出现一个可同步的系统。首先,连接的好处必须超过促进网络中连接的成本。其次,模型核心的博弈需要比诸如囚徒困境等对抗性博弈更具合作性。这些结果再次表明,进化压力可能使系统朝着更稀疏的拓扑发展,因为创建和维持这些拓扑的成本更低。最后,我们的模拟表明,与诸如囚徒困境等更具对抗性的博弈相比,基于互利共生博弈的模型在通信和同步的采用方面表现最佳。

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