Linking human brain local activity fluctuations to structural and functional network architectures.
Linking human brain local activity fluctuations to structural and functional network architectures.
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DOI：
10.1016/j.neuroimage.2013.01.072
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发表时间：
2013-06
期刊：
影响因子：
5.7
通讯作者：
Apkarian, A. V.
中科院分区：
文献类型：
--
作者：
Baria, A. T.;Mansour, A.;Huang, L.;Baliki, M. N.;Cecchi, G. A.;Mesulam, M. M.;Apkarian, A. V.
皮质局部神经元群体的活动不断波动，并且这些波动的很大一部分是在神经元群体之间共享的。在这里，我们寻求将这两种现象联系起来的组织规则。使用功能性MRI（fMRI）识别的神经元活动，对于给定的体素或大脑区域，我们通过计算对数线性功率谱的斜率α，推导出全带宽脑氧合水平依赖性（BOLD）波动的单一测量。对于相同的体素或区域，我们还基于超过零滞后相关的给定阈值Θ来测量其波动与其他体素或区域的时间相干性，从而建立神经元群体对之间的功能连接性。通过静息状态的功能磁共振成像，我们计算了α和功能连接的全脑组平均图。两张图显示了相似的空间组织，所有脑体素的两个参数之间的相关系数为0.75，以及hodology的变异性。一个计算模型复制了主要结果，表明突触低通滤波可以解释这些相互关系。我们还研究了α和结构连通性之间的关系，如基于弥散张量成像的纤维束成像所确定的。我们观察到α和连接性之间的相关性取决于注意力状态;具体来说，α在休息时与结构连接性的相关性比在注意任务时更高。总的来说，这些结果提供了全球规则的局部大脑活动的频率特性和底层的大脑网络的架构之间的动态。
Activity of cortical local neuronal populations fluctuates continuously, and a large proportion of these fluctuations are shared across populations of neurons. Here we seek organizational rules that link these two phenomena. Using neuronal activity, as identified by functional MRI (fMRI) and for a given voxel or brain region, we derive a single measure of full bandwidth brain-oxygenation-level-dependent (BOLD) fluctuations by calculating the slope, α, for the log-linear power spectrum. For the same voxel or region, we also measure the temporal coherence of its fluctuations to other voxels or regions, based on exceeding a given threshold, Θ, for zero lag correlation, establishing functional connectivity between pairs of neuronal populations. From resting state fMRI, we calculated whole-brain group-averaged maps for α and for functional connectivity. Both maps showed similar spatial organization, with a correlation coefficient of 0.75 between the two parameters across all brain voxels, as well as variability with hodology. A computational model replicated the main results, suggesting that synaptic low-pass filtering can account for these interrelationships. We also investigated the relationship between α and structural connectivity, as determined by diffusion tensor imaging-based tractography. We observe that the correlation between α and connectivity depends on attentional state; specifically, α correlated more highly to structural connectivity during rest than while attending to a task. Overall, these results provide global rules for the dynamics between frequency characteristics of local brain activity and the architecture of underlying brain networks.
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影响因子：
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