Institute for Complex Systems and Mathematical Biology, University of Aberdeen, SUPA, Aberdeen, United Kingdom.
PLoS One. 2012;7(11):e48118. doi: 10.1371/journal.pone.0048118. Epub 2012 Nov 8.
This work introduces the phenomenon of Collective Almost Synchronisation (CAS), which describes a universal way of how patterns can appear in complex networks for small coupling strengths. The CAS phenomenon appears due to the existence of an approximately constant local mean field and is characterised by having nodes with trajectories evolving around periodic stable orbits. Common notion based on statistical knowledge would lead one to interpret the appearance of a local constant mean field as a consequence of the fact that the behaviour of each node is not correlated to the behaviours of the others. Contrary to this common notion, we show that various well known weaker forms of synchronisation (almost, time-lag, phase synchronisation, and generalised synchronisation) appear as a result of the onset of an almost constant local mean field. If the memory is formed in a brain by minimising the coupling strength among neurons and maximising the number of possible patterns, then the CAS phenomenon is a plausible explanation for it.
这项工作介绍了集体几乎同步(CAS)现象,它描述了一种在小耦合强度下复杂网络中模式出现的通用方式。CAS 现象的出现是由于存在近似恒定的局部平均场,其特征是具有轨迹围绕周期性稳定轨道演化的节点。基于统计知识的常见概念会导致人们将局部恒定平均场的出现解释为每个节点的行为与其他节点的行为不相关的结果。与这个常见概念相反,我们表明,各种众所周知的较弱形式的同步(几乎同步、时滞同步、相位同步和广义同步)是由于几乎恒定的局部平均场的出现而出现的。如果记忆是通过在神经元之间最小化耦合强度和最大化可能模式的数量来形成的,那么 CAS 现象就是对其的一个合理解释。