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多层脑网络频率特异性的动态分析

Dynamic analysis of frequency specificity in multilayer brain networks.

作者信息

Ke Ming, Cao Peihui, Chai Xiaoliang, Yao Xinyi, Liu Guangyao

机构信息

School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China.

School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China.

出版信息

Brain Res. 2025 Mar 1;1850:149418. doi: 10.1016/j.brainres.2024.149418. Epub 2024 Dec 21.

Abstract

The brain is a highly complex and delicate system, and its internal neural processes are manifested as the interweaving and superposition of multi-frequency neural signals. However, traditional brain network studies are often limited to the whole frequency band or a specific frequency band, ignoring the potentially profound impact of the diversity of information within the frequency on the dynamics of brain networks. To comprehensively and deeply analyze this phenomenon, the present study is devoted to exploring the specific performance of brain networks at different frequencies. We used the maximum overlap discrete wavelet transform technique to finely divide the time series data into the following frequency bands: scale 1 (0.125-0.25 Hz), scale 2 (0.06-0.125 Hz), scale 3 (0.03-0.06 Hz) and scale 4 (0.015-0.03 Hz). Based on these frequency bands, we constructed multilayer networks from both dynamic and static perspectives, respectively. From the dynamic perspective, we quantitatively evaluated the dynamic differences among different frequency bands using metrics such as flexibility, promiscuity, integration, and recruitment, and found that scale 3 and scale 4 bands performed particularly well. In contrast, from a static perspective, we measured the cross-frequency interaction capability between different frequency bands through metrics such as multilayer clustering coefficient and entropy of multiplexing degree, and the results show that scale 2, scale 3, and scale 4 band networks have enhanced global integration capability and local capability. In addition, we explored the correlation of gender and age with the properties of brain networks in different frequency bands. In the scale 1 frequency band, the organization of brain functions showed significant gender differences, while in the scale 2 frequency band, there was a significant correlation between age and global efficiency. By integrating the dual perspectives of time and frequency domains, this study not only reveals the critical role of frequency specificity in the brain's information processing and functional organization but also provides new perspectives for understanding the complex working mechanisms of the brain as well as gender- and age-related cognitive differences.

摘要

大脑是一个高度复杂且脆弱的系统,其内部神经过程表现为多频神经信号的交织与叠加。然而,传统的脑网络研究往往局限于全频段或特定频段,忽略了频率内信息多样性对脑网络动力学可能产生的深远影响。为了全面深入地分析这一现象,本研究致力于探索不同频率下脑网络的具体表现。我们使用最大重叠离散小波变换技术将时间序列数据精细划分为以下频段:尺度1(0.125 - 0.25赫兹)、尺度2(0.06 - 0.125赫兹)、尺度3(0.03 - 0.06赫兹)和尺度4((0.015 - 0.03赫兹)。基于这些频段,我们分别从动态和静态角度构建了多层网络。从动态角度,我们使用灵活性、混杂性、整合性和募集性等指标定量评估不同频段之间的动态差异,发现尺度3和尺度4频段表现尤为突出。相比之下,从静态角度,我们通过多层聚类系数和复用度熵等指标测量不同频段之间的跨频交互能力,结果表明尺度2、尺度3和尺度4频段网络具有增强的全局整合能力和局部能力。此外,我们还探讨了性别和年龄与不同频段脑网络属性的相关性。在尺度1频段,脑功能组织存在显著的性别差异,而在尺度2频段,年龄与全局效率之间存在显著相关性。通过整合时域和频域的双重视角,本研究不仅揭示了频率特异性在大脑信息处理和功能组织中的关键作用,还为理解大脑复杂的工作机制以及与性别和年龄相关的认知差异提供了新的视角。

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