Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Brain and Mind Center, The University of Sydney, Sydney, NSW, Australia.
Nat Commun. 2022 Aug 15;13(1):4791. doi: 10.1038/s41467-022-32381-2.
In the absence of external stimuli, neural activity continuously evolves from one configuration to another. Whether these transitions or explorations follow some underlying arrangement or lack a predictable ordered plan remains to be determined. Here, using fMRI data from highly sampled individuals (~5 hours of resting-state data per individual), we aimed to reveal the rules that govern transitions in brain activity at rest. Our Topological Data Analysis based Mapper approach characterized a highly visited transition state of the brain that acts as a switch between different neural configurations to organize the spontaneous brain activity. Further, while the transition state was characterized by a uniform representation of canonical resting-state networks (RSNs), the periphery of the landscape was dominated by a subject-specific combination of RSNs. Altogether, we revealed rules or principles that organize spontaneous brain activity using a precision dynamics approach.
在没有外部刺激的情况下，神经活动会不断地从一种状态转变到另一种状态。这些转变或探索是否遵循某种潜在的安排，或者缺乏可预测的有序计划，还有待确定。在这里，我们使用来自高度采样个体（每个个体约 5 小时的静息态数据）的 fMRI 数据，旨在揭示支配静息状态下大脑活动转变的规律。我们基于拓扑数据分析的映射器方法，对大脑中一个高度活跃的转换状态进行了特征描述，这个状态充当了不同神经状态之间的开关，从而对自发性大脑活动进行了组织。进一步地，尽管转换状态的特征是典型静息态网络（RSN）的统一表示，但景观的外围则由 RSN 的特定于个体的组合所主导。总之，我们使用精确动力学方法揭示了组织自发性大脑活动的规则或原则。
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