静息状态脑网络的时空转换与人类认知能力的关系。

IF 3.9 3区 工程技术 Q2 NEUROSCIENCES
Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-10-04 DOI:10.1007/s11571-025-10347-6
Lv Zhou, Zhengchang Jiang, Zhao Chang, Rong Wang, Ying Wu
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引用次数: 0

摘要

大脑是一个不断在不同状态之间切换的动态系统。这种大脑状态的转变对人类认知有重要的功能影响,但其动力机制却很少被理解。在此,我们通过测量静息脑功能网络中跨越时间和空间的模块结构的时空重构来量化状态转移。通过整合多模态数据、噪声驱动的大尺度动态模型和meta分析,我们发现人类加速区(HARs)基因指示的状态转换与大脑进化之间存在显著关系。这种状态转换与多种认知能力有关,尤其是默认模式网络和控制网络中较好的执行控制能力。静息状态脑在全脑尺度上表现出中等程度的状态转换,但这种转换的区域异质性最高,在功能上与分离与整合的动态平衡有关,在结构上则由脑结构连接的分层模块支持。此外,区域间的高状态转换由血清素1a (5-HT1A)和多巴胺(D2)受体支持。我们的研究结果强调了大脑状态转换在认知能力中的关键作用,揭示了潜在的动态机制,为研究静息大脑的功能原理提供了新的见解。补充信息:在线版本包含补充资料,下载地址:10.1007/s11571-025-10347-6。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatiotemporal transition of resting-state brain networks associates with human cognitive abilities.

The brain is a dynamic system that continuously switches between different states. This brain state transition has significant functional consequences on human cognition, but its dynamic mechanism is rarely understood. Here, we quantified the state transition by measuring the spatiotemporal reconfiguration of modular structure spanning time and space in the resting-brain functional networks. By integrating multimodal data, noise-driven large-scale dynamic model and meta-analysis, we found the significant relationship between state transition and brain evolution indicated by human accelerated regions (HARs) genes. This state transition was associated with diverse cognitive abilities, especially better executive control ability in the default mode network and control network. The resting-state brain showed a moderate degree of state transition at the whole-brain scale, but the regional heterogeneity of the transition was the highest, which functionally, was associated with the dynamic balance between segregation and integration, and structurally, was supported by hierarchical modules in brain structural connectivity. In addition, the high state transition among regions was supported by serotonin 1 A (5-HT1A) and dopamine (D2) receptors. Our findings highlight the critical role of brain state transition in cognitive abilities and reveal the underlying dynamic mechanisms, offering new insights into the functional principles of the resting brain.

Supplementary information: The online version contains supplementary material available at 10.1007/s11571-025-10347-6.

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来源期刊
Cognitive Neurodynamics
Cognitive Neurodynamics 医学-神经科学
CiteScore
6.90
自引率
18.90%
发文量
140
审稿时长
12 months
期刊介绍: Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models. The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome. The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged. 1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics. 2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages. 3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.
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