论文标题

静止状态的MEG节奏揭示了皮质活动的动力学

Dynamics in cortical activity revealed by resting-state MEG rhythms

论文作者

Mendoza-Ruiz, J., Alonso-Malaver, C. E., Valderrama, M., Rosso, O. A., Martínez, J. H.

论文摘要

大脑可以被认为是一种多体构建,具有神经元结构描述的时空动力学。大脑活动的振荡性质允许这些结构(节点)描述为一组耦合的振荡器,形成了一个网络,可以研究节点动力学和网络拓扑的振荡器。在各种尺度上量化其动力学是一个问题,声称要在几个大脑活动中探索,例如静止活动。静止状态将健康受试者的基本大脑动力学联系起来,而这些受试者没有积极妥协的感觉或认知过程。研究其动力学是高度不平凡的,但为了解大脑功能的一般原理打开了大门。我们假设如何成为健康受试者在静息状态受试者的皮质波动的时空动力学。我们检索了重建磁脑化信号的动力学(熵/复杂性)的字母。我们组装皮层连接以引发网络的动态。我们描述了频带的熵/复杂性之间的订单关系。我们揭示了后皮层砾岩会在α频带中具有更强动力学和高聚类的淋巴结。这些秩序关系的存在表明每个频段的新现象。有趣的是,我们发现后皮层在静止状态的动力学和结构中起着基本的作用。据我们所知,这是涉及信息理论和网络科学的磁脑疗法的首次研究,以更好地了解不同频段和尺度的REST脑活动的动态和结构。

The brain may be thought of as a many-body architecture with a spatio-temporal dynamics described by neuronal structures. The oscillatory nature of brain activity allows these structures (nodes) to be described as a set of coupled oscillators forming a network where the node dynamics, and that of the network topology can be studied. Quantifying its dynamics at various scales is an issue that claims to be explored for several brain activities, e.g., activity at rest. The resting-state associates the underlying brain dynamics of healthy subjects that are not actively compromised with sensory or cognitive processes. Studying its dynamics is highly non-trivial but opens the door to understand the general principles of brain functioning. We hypothesize about how could be the spatio-temporal dynamics of cortical fluctuations for healthy subjects at resting-state. We retrieve the alphabet that reconstructs the dynamics (entropy/complexity) of magnetoencephalograpy signals. We assemble the cortical connectivity to elicit the network's dynamics. We depict an order relation between entropy/complexity for frequency bands. We unveiled that the posterior cortex conglomerates nodes with both stronger dynamics and high clustering for α band. The existence of these order relations suggests an emergent phenomenon of each band. Interestingly, we find that the posterior cortex plays a cardinal role in both the dynamics and structure regarding the resting-state. To the best of our knowledge, this is the first study with magnetoencephalograpy involving information theory and network science to better understand the dynamics and structure of brain activity at rest for different bands and scales.

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