基于静息态磁共振的突显网络频率特异性研究
发布时间：2018-12-16 16:53
【摘要】：神经活动的基本特征表现为神经活动的节律性,是指神经元在某个相同频率的活动特征。大脑中不同脑区的神经振荡有不同的优势频率,脑区功能越高级,其所体现的优势频率越低,表现为趋于功能整合的低频神经振荡,而部分信息加工的功能分离发生在更高级的脑区活动。然而因为技术方面的缺陷,无法揭示低频神经振荡的生理学机制,需要更先进的技术。功能磁共振成像技术(functional magnetic resonance imaging,fMRI)是目前研究低频神经振荡的主要工具,主要原因是其采集的低频信号是稳定的,图像的空间分辨率很高,存在的神经活动具有相关性。在传统的低频振荡研究中,突显网络(salience network,SN)可被分成背侧认知网络和腹侧情绪网络。而突显网络的主要区域是脑岛,右侧前脑岛在协调其他脑网络的自适应行为方面起到重要作用。然而,网络间的协调是否受时间-空间限制的,这是一个值得深思的问题。换句话说,脑岛的不同亚区是否存在功能分离和功能整合?在不同频段是否存在频谱指纹现象?窄的频段间隔难以阐述这些网络的复杂功能作用。通过网上的人类脑连接项目(human connectcome project,HCP)大数据,我们计算不同频段的功能连接的频率特异性,比如全频段(full frequency,0.001-0.694Hz)、亚慢频段(infra slow frequency,0.001-0.1Hz)、慢频段(slow frequency,0.1-0.694Hz)。研究结果发现背侧前脑岛构成的背侧突显网络跟外在朝向网络之间有联系,而腹侧突显网络与内在朝向网络有连接,比如,可以发现背侧突显网络跟中央执行网络存在连接,而腹侧突显网络跟默认网络存在连接;甚至背侧突显网络和腹侧突显网络有各自的频率效应区域;慢频段时,突显网络的功能连接分布存在右侧偏侧化现象;而且两个突显网络的功能连接区域有重叠,部分区域是存在生理意义的。这些发现为我们理解突显网络功能连接分布的频率特征提供依据,同时揭示了网络频率特异性的生理机制,将对生理机制的理解从低频分析延伸到高频范围,例如枕叶α波的躲避作用。这些发现对于功能分离和功能整合、网络间的协调有重要的启示。
[Abstract]:The basic characteristic of neural activity is the rhythm of neural activity, which refers to the characteristics of neuron activity at the same frequency. The higher the brain function, the lower the dominant frequency. Part of the functional separation of information processing occurs in higher-level brain activity. However, due to technical shortcomings, it is impossible to reveal the physiological mechanism of low frequency neural oscillation, and more advanced techniques are needed. Functional Magnetic Resonance Imaging (functional magnetic resonance imaging,fMRI) is the main tool for studying low frequency neural oscillations. The main reason is that the low frequency signals collected by (functional magnetic resonance imaging,fMRI are stable, the spatial resolution of images is very high, and the neural activity is correlated. In the traditional low-frequency oscillation research, the salient network (salience network,SN) can be divided into dorsal cognitive network and ventral emotional network. The main area that highlights the network is the brain island, and the right forebrain island plays an important role in coordinating the adaptive behavior of other brain networks. However, whether the coordination between networks is limited by time-space is a question worth pondering. In other words, is there functional separation and functional integration in different subareas of the brain island? Is there a spectrum fingerprint phenomenon in different frequency bands? It is difficult to describe the complex function of these networks at narrow frequency intervals. Using the online human brain connection project (human connectcome project,HCP) big data, we calculated the frequency specificity of functional connections at different frequencies, such as full frequency band (full frequency,0.001-0.694Hz), subslow band (infra slow frequency, 0.001-0.1Hz, slow band (slow frequency,0.1-0.694Hz). The results show that there is a connection between the dorsal salience network and the outward orientation network, while the ventral salience network is connected to the inward orientation network. For example, it can be found that there is a connection between the dorsal salience network and the central executive network. But the ventral side highlights the network to have the connection with the default network; Even the dorsal and ventral salience networks have their own frequency effect regions, and the distribution of the functional connections of the salient networks has the phenomenon of right-flanking in the slow band. Moreover, there is overlap between the two salient networks, some of which have physiological significance. These findings provide a basis for us to understand the frequency characteristics that highlight the distribution of network functional connections, and at the same time reveal the network frequency specific physiological mechanism, which extends the understanding of physiological mechanism from low frequency analysis to high frequency range. For example, occipital 伪-wave avoidance. These findings have important implications for functional separation and functional integration and coordination between networks.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R445.2;R338
[Abstract]:The basic characteristic of neural activity is the rhythm of neural activity, which refers to the characteristics of neuron activity at the same frequency. The higher the brain function, the lower the dominant frequency. Part of the functional separation of information processing occurs in higher-level brain activity. However, due to technical shortcomings, it is impossible to reveal the physiological mechanism of low frequency neural oscillation, and more advanced techniques are needed. Functional Magnetic Resonance Imaging (functional magnetic resonance imaging,fMRI) is the main tool for studying low frequency neural oscillations. The main reason is that the low frequency signals collected by (functional magnetic resonance imaging,fMRI are stable, the spatial resolution of images is very high, and the neural activity is correlated. In the traditional low-frequency oscillation research, the salient network (salience network,SN) can be divided into dorsal cognitive network and ventral emotional network. The main area that highlights the network is the brain island, and the right forebrain island plays an important role in coordinating the adaptive behavior of other brain networks. However, whether the coordination between networks is limited by time-space is a question worth pondering. In other words, is there functional separation and functional integration in different subareas of the brain island? Is there a spectrum fingerprint phenomenon in different frequency bands? It is difficult to describe the complex function of these networks at narrow frequency intervals. Using the online human brain connection project (human connectcome project,HCP) big data, we calculated the frequency specificity of functional connections at different frequencies, such as full frequency band (full frequency,0.001-0.694Hz), subslow band (infra slow frequency, 0.001-0.1Hz, slow band (slow frequency,0.1-0.694Hz). The results show that there is a connection between the dorsal salience network and the outward orientation network, while the ventral salience network is connected to the inward orientation network. For example, it can be found that there is a connection between the dorsal salience network and the central executive network. But the ventral side highlights the network to have the connection with the default network; Even the dorsal and ventral salience networks have their own frequency effect regions, and the distribution of the functional connections of the salient networks has the phenomenon of right-flanking in the slow band. Moreover, there is overlap between the two salient networks, some of which have physiological significance. These findings provide a basis for us to understand the frequency characteristics that highlight the distribution of network functional connections, and at the same time reveal the network frequency specific physiological mechanism, which extends the understanding of physiological mechanism from low frequency analysis to high frequency range. For example, occipital 伪-wave avoidance. These findings have important implications for functional separation and functional integration and coordination between networks.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R445.2;R338
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