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静息状态下局部信号与全脑信号之间的频率依赖性有效连接。

Frequency-dependent effective connections between local signals and the global brain signal during resting-state.

作者信息

Wang Yifeng, Yang Chengxiao, Li Gen, Ao Yujia, Jiang Muliang, Cui Qian, Pang Yajing, Jing Xiujuan

机构信息

Institute of Brain and Psychological Sciences, Sichuan Normal University, No.5, Jing'an Road, Chengdu, 610066 China.

First Affiliated Hospital, Guangxi Medical University, Nanning, 530021 China.

出版信息

Cogn Neurodyn. 2023 Apr;17(2):555-560. doi: 10.1007/s11571-022-09831-0. Epub 2022 Jul 2.

Abstract

UNLABELLED

The psychological and physiological meanings of resting-state global brain signal (GS) and GS topography have been well confirmed. However, the causal relationship between GS and local signals was largely unknown. Based on the Human Connectome Project dataset, we investigated the effective GS topography using the Granger causality (GC) method. In consistent with GS topography, both effective GS topographies from GS to local signals and from local signals to GS showed greater GC values in sensory and motor regions in most frequency bands, suggesting that the unimodal superiority is an intrinsic architecture of GS topography. However, the significant frequency effect for GC values from GS to local signals was primarily located in unimodal regions and dominated at slow 4 frequency band whereas that from local signals to GS was mainly located in transmodal regions and dominated at slow 6 frequency band, consisting with the opinion that the more integrated the function, the lower the frequency. These findings provided valuable insight for the frequency-dependent effective GS topography, improving the understanding of the underlying mechanism of GS topography.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11571-022-09831-0.

摘要

未标注

静息态全脑信号(GS)及其地形图的心理和生理意义已得到充分证实。然而,GS与局部信号之间的因果关系在很大程度上尚不清楚。基于人类连接体项目数据集,我们使用格兰杰因果关系(GC)方法研究了有效的GS地形图。与GS地形图一致,从GS到局部信号以及从局部信号到GS的有效GS地形图在大多数频段的感觉和运动区域均显示出更大的GC值,这表明单峰优势是GS地形图的一种内在结构。然而,从GS到局部信号的GC值的显著频率效应主要位于单峰区域,并在慢4频段占主导,而从局部信号到GS的频率效应主要位于跨模态区域,并在慢6频段占主导,这与功能越整合、频率越低的观点一致。这些发现为频率依赖性有效GS地形图提供了有价值的见解,有助于加深对GS地形图潜在机制的理解。

补充信息

在线版本包含可在10.1007/s11571-022-09831-0获取的补充材料。

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3
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5
DREAM : A Toolbox to Decode Rhythms of the Brain System.
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7
Frequency-dependent circuits anchored in the dorsal and ventral left anterior insula.
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8
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9
Frequency-specific alteration of functional connectivity density in bipolar disorder depression.
Prog Neuropsychopharmacol Biol Psychiatry. 2021 Jan 10;104:110026. doi: 10.1016/j.pnpbp.2020.110026. Epub 2020 Jul 2.
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