标题： 分形盆地作为敏捷大脑的机制 显示英文标题

标题： Fractal Basins as a Mechanism for the Nimble Brain

摘要： 大脑的一个有趣特征是，它能够根据环境背景或当前的大脑状态以独特的方式响应来自环境的不同的感官信号。 在动力系统中，这是一种多稳定性（multi-stability）的例子，即能够在多个对应特定大脑活动/连接模式的稳定状态下切换的能力。 在本文中，我们描述了在受大脑启发的动力系统模型中出现的镶嵌态（chimera states），这些状态由混合同步和非同步组成，并且该模型由具有弱个体相互作用和混沌/周期性局部动态的网络构成。 我们通过在基于人类弥散张量成像（DTI）的现实解剖大脑网络上交互的合成时间序列来说明这一机制。 我们引入所谓的向量模式状态（Vector Pattern State, VPS）作为一种有效识别镶嵌态和映射吸引域结构的方法。 通过对不同初始条件下的相似VPS进行聚类，我们展示了这些状态的共存吸引子揭示了复杂交织的分形吸引域边界，这些边界可以立即到达。 这可能解释了灵活大脑迅速在共存吸引子之间切换模式的能力。 显示英文摘要

摘要： An interesting feature of the brain is its ability to respond to disparate sensory signals from the environment in unique ways depending on the environmental context or current brain state. In dynamical systems, this is an example of multi-stability, the ability to switch between multiple stable states corresponding to specific patterns of brain activity/connectivity. In this article, we describe chimera states, which are patterns consisting of mixed synchrony and incoherence, in a brain-inspired dynamical systems model composed of a network with weak individual interactions and chaotic/periodic local dynamics. We illustrate the mechanism using synthetic time series interacting on a realistic anatomical brain network derived from human diffusion tensor imaging (DTI). We introduce the so-called Vector Pattern State (VPS) as an efficient way of identifying chimera states and mapping basin structures. Clustering similar VPSs for different initial conditions, we show that coexisting attractors of such states reveal intricately "mingled" fractal basin boundaries that are immediately reachable. This could explain the nimble brain's ability to rapidly switch patterns between coexisting attractors.