随机门限网络中的最大信息传递与行为多样性
Maximal Information Transfer and Behavior Diversity in Random Threshold Networks
摘要：
随机阈值网络是稀释的、非对称的自旋玻璃、神经网络或基因调控网络的理想化模型。区域主题网络也是任何协调因果系统的一个有趣的一般例子。在这里，我们研究的条件，最大的信息传输和行为多样性的RTNs。这些条件可能在物理和生物系统中发挥重要作用，可能在生物系统中作为重要的选择性状。我们证明了在动态临界网络中两两互信息最大化。此外，我们表明，相关的行为多样性是最大化的轻微混乱的网络，接近临界区域。重要的是，关键网络最大化了整个网络和整个时间的协调，多样的动态行为：源和接收器节点之间的信息传输和动态行为的多样性，当测量源和接收器之间的时间延迟时，对于关键网络最大化。
英文摘要：
Random Threshold Networks (RTNs) are an idealized model of diluted, non symmetric spin glasses, neural networks or gene regulatory networks. RTNs also serve as an interesting general example of any coordinated causal system. Here we study the conditions for maximal information transfer and behavior diversity in RTNs. These conditions are likely to play a major role in physical and biological systems, perhaps serving as important selective traits in biological systems. We show that the pairwise mutual information is maximized in dynamically critical networks. Also, we show that the correlated behavior diversity is maximized for slightly chaotic networks, close to the critical region. Importantly, critical networks maximize coordinated, diverse dynamical behavior across the network and across time: the information transmission between source and receiver nodes and the diversity of dynamical behaviors, when measured with a time delay between the source and receiver, are maximized for critical networks.
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