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Integrated and segregated frequency architecture of the human brain network

机译:人脑网络的集成和隔离频率架构

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The frequency of brain activity modulates the relationship between the brain and human behavior. Insufficient understanding of frequency-specific features may thus lead to inconsistent explanations of human behavior. However, to date, the frequency-specific features of the human brain functional network at the whole-brain level remain poorly understood. Here, we used resting-state fMRI data and graph-theory analyses to investigate the frequency-specific characteristics of fMRI signals in 12 frequency bands (frequency range 0.01-0.7 Hz) in 75 healthy participants. We found that brain regions with higher level and more complex functions had a more variable functional connectivity pattern but engaged less in higher frequency ranges. Moreover, brain regions that engaged in fewer frequency bands played more integrated roles (i.e., higher network participation coefficient and lower within-module degree) in the functional network, whereas regions that engaged in broader frequency ranges exhibited more segregated functions (i.e., lower network participation coefficient and higher within-module degree). Finally, behavioral analyses revealed that regional frequency variability was associated with a spectrum of behavioral functions from sensorimotor functions to complex cognitive and social functions. Taken together, our results showed that segregated functions are executed in wide frequency ranges, whereas integrated functions are executed mainly in lower frequency ranges. These frequency-specific features of brain networks provided crucial insights into the frequency mechanism of fMRI signals, suggesting that signals in higher frequency ranges should be considered for their relation to cognitive functions.
机译:脑活动的频率调制大脑与人类行为之间的关系。因此,对频率特定特征的理解不足可能导致对人类行为的不一致解释。然而,迄今为止,全脑水平的人脑功能网络的频率特征仍然明白。在这里,我们使用休息状态的FMRI数据和图解分析,以研究在75名健康参与者中的12个频带(频率范围0.01-0.7 Hz)中FMRI信号的频率特定特性。我们发现,具有更高水平和更复杂功能的大脑区域具有更具变量的功能连接模式,但在更高频率范围内从此均匀。此外,从事频带较少的脑区域在功能网络中发挥了更多的集成角色(即,较高的网络参与系数和较低的模块内部),而从更宽的频率范围接合的区域呈现出更多的隔离功能(即,下部网络参与系数和更高的模块内部程度)。最后,行为分析表明,区域频率变异性与来自传感器函数与复杂认知和社会功能的频谱相关的行为函数。我们的结果表明,分离功能在宽频率范围内执行,而集成功能主要以较低频率的范围执行。大脑网络的这些频率特定特征为FMRI信号的频率机制提供了重要的见解,这表明应考虑更高频率范围的信号与认知功能的关系。

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