Comparison of characteristics between region-and voxel-based network analyses in resting-state fMRI data.
Comparison of characteristics between region-and voxel-based network analyses in resting-state fMRI data.
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DOI：
10.1016/j.neuroimage.2009.12.051
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发表时间：
2010-04-01
期刊：
影响因子：
5.7
通讯作者：
Laurienti, Paul J.
中科院分区：
文献类型：
--
作者：
Hayasaka, Satoru;Laurienti, Paul J.
关键词：
小世界网络是一类表现出有效的远距离通信和紧密相连的本地社区的网络。近年来，使用基于网络理论的方法对功能和结构脑网络进行了研究，并一致显示出具有小世界特性。此外，一些基于体素的大脑网络表现出无标度网络的特性，这是一类具有超大集线器的网络。然而，研究中使用的方法和观察到的结果存在相当大的不一致性，特别是基于区域和基于体素的大脑网络之间。我们使用相同的静息状态fMRI数据在多个分辨率下构建了功能性脑网络，并比较了各种网络指标、程度分布和感兴趣节点的定位。结果表明，分辨率越高的网络表现出越明显的小世界网络特征。研究还发现，与基于区域的网络相比，基于体素的网络对网络碎片的抵抗力更强。虽然所有网络的度分布遵循指数截断幂律而不是真正的幂律，但分辨率越高，分布越接近幂律。基于体素的分析还增强了结果在三维大脑空间中的可视化。研究发现，具有高连通性的节点往往具有高效率，这是一种在基于区域的网络中不一致观察到的属性的共定位。我们的结果证明了在实验允许的最佳规模上构建大脑网络的好处。
Small-world networks are a class of networks that exhibit efficient long-distance communication and tightly interconnected local neighborhoods. In recent years, functional and structural brain networks have been examined using network theory-based methods, and consistently shown to have small-world properties. Moreover, some voxel-based brain networks exhibited properties of scale-free networks, a class of networks with mega-hubs. However, there are considerable inconsistencies across studies in the methods used and the results observed, particularly between region-based and voxel-based brain networks. We constructed functional brain networks at multiple resolutions using the same resting-state fMRI data, and compared various network metrics, degree distribution, and localization of nodes of interest. It was found that the networks with higher resolutions exhibited the properties of small-world networks more prominently. It was also found that voxel-based networks were more robust against network fragmentation compared to region-based networks. Although the degree distributions of all networks followed an exponentially truncated power law rather than true power law, the higher the resolution, the closer the distribution was to a power law. The voxel-based analyses also enhanced visualization of the results in the 3D brain space. It was found that nodes with high connectivity tended have high efficiency, a co-localization of properties that was not as consistently observed in the region-based networks. Our results demonstrate benefits of constructing the brain network at the finest scale the experiment will permit.
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DOI：
10.1073/pnas.0504136102
发表时间：
2005-07-05
影响因子：
11.1
作者：
Fox, MD;Snyder, AZ;Raichle, ME
通讯作者：
Raichle, ME
影响因子：
5.3
作者：
Achard, S;Salvador, R;Bullmore, ET
通讯作者：
Bullmore, ET
影响因子：
3.7
作者：
Humphries MD;Gurney K
通讯作者：
Gurney K
影响因子：
3.7
作者：
Hagmann, Patric;Kurant, Maciej;Gigandet, Xavier;Thiran, Patrick;Wedeen, Van J.;Meuli, Reto;Thiran, Jean-Philippe
通讯作者：
Thiran, Jean-Philippe
影响因子：
5.7
作者：
Iturria-Medina, Yasser;Sotero, Roberto C.;Melie-Garcia, Lester
通讯作者：
Melie-Garcia, Lester