健康与遗传心理学研究室知识库

静息态脑功能网络是指在无外在认知任务的情形下，大脑皮层自发的同步活动形成的功能模块。静息态下的功能磁共振成像（functional Magnetic Resonance Imaging,fMRI）揭示了多种静息态网络，这些网络对应着不同的认知功能，并且在神经心理疾病中发生改变，具有成为这些神经心理疾病生物标记物的潜在价值。fMRI成像基于血氧水平依赖信号（BloodOxygen Level-Dependent,BOLD），是在较慢时间尺度上对神经活动的间接反映。对于静息态下神经电生理活动特征的皮层分布和基于fMRI发现的脑功能网络的神经电生理特征，目前仍然缺乏系统的、来自脑电活动直接记录的证据。

颅内脑电记录由于其成像特点，能够记录到丰富的神经振荡活动，在多个时间尺度上直接反映神经元群的介观场电位活动。本论文基于静息态颅内脑电数据，在已有的关于BOLD功能网络的神经电生理基础的颅内脑电研究基础上，围绕静息态下颅内电极记录的神经振荡频谱与功能连接，进一步研究以下几个静息态脑功能相关的问题：

静息态颅内脑电经典频段能量和无标度特征在皮层的分布。

静息态下不同脑结构/功能网络区域之间神经振荡功能连接的特征，并比较常见的不同脑电功能连接指标下功能网络结构的异同。

静息态下功能连接个体变异性的潜在神经振荡相关物。

睁眼与闭眼两种不同的静息状态下神经振荡局部与功能连接特征差异。

提出一种从记录的原始信号中消除参考信号的方法，以构建静息态脑功能网络为例，评估该方法的效果。

本文的研究发现，不同频段的神经振荡的皮层分布具有差异性。静息态颅内脑电的神经振荡以Alpha和Theta频段为主，Alpha频段的神经振荡主要出现在枕叶、顶叶、楔前叶、颞枕区，Theta频段主要出现在颞叶、边缘系统和额叶。整体而言，静息态下神经振荡呈现出在皮层从后往前、由下往上的方向上主导频段由低变高的规律，而颅内脑电信号频谱无标度特征斜率的绝对值也在同样的方向上出现由大变小的趋势。

功能连接的主导频段同样以Theta和Alpha为主。尽管不同连接指标对应功能连接的整体频谱特征基本一致，但不同连接指标强度与距离的关系、强连接所出现的配对脑区却存在差异，提示了不同脑区间信号同步机制的差异。在功能连接个体变异性方面，各个脑区的个体变异程度的高低与其神经振荡的整体节律性水平呈负相关，这可能提示了功能连接个体变异性的神经电生理基础。通过分别使用单变量统计与多变量模式分析的方法，本文揭示了睁眼与闭眼静息态之间，神经振荡的频谱与功能连接特征在皮层上存在着广泛分布的差异。

本文围绕静息态下颅内脑电神经振荡的局部与功能连接特征，通过一系列研究，总结了这些特征的一般性规律，并检验了这些特征在睁眼/闭眼静息状态下的差异。在群组水平的整体性结论之外，本文进一步揭示了静息态下功能连接个体变异性的潜在脑电对应物。最后，本文讨论了参考电极对颅内脑电神经振荡的影响，提出了一种基于分频段空间约束独立成分分析的估计并除去参考信号的转参考方法，并在模拟数据和真实静息态数据上验证了该方法在除去参考信号上的有效性。这一系列研究探索了静息态下大脑皮层神经振荡自身的活动规律及其与fMRI功能连接个体变异性之间的关系，为进一步探索和理解神经振荡如何编码认知过程和形成功能网络提供了基础。

The brain’s resting state functional network is the functional modules spontaneously formed without explicit cognitive task. Multiple resting state networks have been revealed with resting state functional resonance imaging(fMRI). These networks corresponds to different cognitive function and is reported to be altered under different neuropsychological disease，which give them the potential to serve as a biomarker to detect and diagnose these disease that currently lack of any gold standard. The imaging principle of fMRI limits the its detection of resting state functional network of neuronal activity to an indirect way. With intracranial electroencephalograph(iEEG) recordings, this thesis aims to study the following aspects of resting state brain function, centered by the frequency spectrum of neuronal oscillation and the functional connectivity between different cortical regions：

The cortical distribution of spectral energy of typical frequency bands and scale free characteristic slope.

The functional connectivity pattern between different structural and functional modules under different functional EEG connectivity indices.

The neuroelectrophysiology correlates of the individual variation in fMRI functional connectivity.

Difference in local frequency spectrum and connectivity pattern between eye open and eye close resting state.

Propose a method to remove reference signal from unipolar recorded iEEG signal and test its validity on an exemplar resting state functional network construction.

Results of this thesis revealed that the strength of neural oscillation in different frequency bands have different distribution patterns across cortical surface. Theta and Alpha oscillation dominate the resting state iEEG, with Alpha oscillations appear in occipital, parietal, precuneus and temporo-occipital regions and Theta oscillations dominate temporal, frontal and limbic regions. As a general pattern, the dominate frequency of neural oscillation increases from posterior to anterior, inferior to superior. The absolute value of scale free characteristic slope shares a similar pattern. Functional connectivity in resting state iEEG is also dominated by Theta and Alpha band. While different functional connectivity indices share this similar connectivity spectrum, their strength-distance relationship differs. The brain regions show strongest connection are inconsistent under different connectivity indices, which indicates that the neural communication mechanism differs depends on brain region pairs.A cortex region’s individual variance of its resting state fMRI connectivity pattern correlates negatively with its extent of rhythmicity of resting state iEEG neural oscillation, which is mediated by local BOLD connectivity strength. There are wide spread frequency spectrum and connectivity difference between eyes-open and eyes-close resting state, with stronger oscillation power and connectivity in eyes-close state.

This thesis conducted a series of studies to reveal the patterns of local spectrum and functional connectivity of neural oscillation recorded with resting state iEEG. Their difference in eyes-open and eyes-close resting state is analyzed and discussed. Beyond the group level consistent patterns, this thesis also targeted the individual variance in functional connectivity and revealed a neural oscillation correlates to this phenomenon. Finally, a re-reference method is proposed to remove reference signals from unipolar iEEG signal to reconstruct neural oscillation and tested on simulated and empirical iEEG data. By investigating the properties of local and inter regional connectivity of neural oscillations, these studies offers basis for further understanding of how neural oscillation encode cognitive process and form functional networks.