Department of Radiology and BRIC, University of North Carolina at Chapel Hill, CB#7513, 130 Mason Farm Road, Chapel Hill, NC, 27599, USA.
Division of Psychiatry, Geneva University Hospitals, Geneva, Switzerland.
Neuroinformatics. 2019 Oct;17(4):547-561. doi: 10.1007/s12021-018-9413-x.
Little is known about the high-order interactions among brain regions measured by the similarity of higher-order features (other than the raw blood-oxygen-level-dependent signals) which can characterize higher-level brain functional connectivity (FC). Previously, we proposed FC topographical profile-based high-order FC (HOFC) and found that this metric could provide supplementary information to traditional FC for early Alzheimer's disease (AD) detection. However, whether such findings apply to network-level brain functional integration is unknown. In this paper, we propose an extended HOFC method, termed inter-network high-order FC (IN-HOFC), as a useful complement to the traditional inter-network FC methods, for characterizing more complex organizations among the large-scale brain networks. In the IN-HOFC, both network definition and inter-network FC are defined in a high-order manner. To test whether IN-HOFC is more sensitive to cognition decline due to brain diseases than traditional inter-network FC, 77 mild cognitive impairments (MCIs) and 89 controls are compared among the conventional methods and our IN-HOFC. The result shows that IN-HOFCs among three temporal lobe-related high-order networks are dampened in MCIs. The impairment of IN-HOFC is especially found between the anterior and posterior medial temporal lobe and could be a potential MCI biomarker at the network level. The competing network-level low-order FC methods, however, either revealing less or failing to detect any group difference. This work demonstrates the biological meaning and potential diagnostic value of the IN-HOFC in clinical neuroscience studies.
目前对于通过高阶特征（除原始血氧水平依赖信号之外）的相似性来测量大脑区域之间的高阶相互作用知之甚少，这些高阶特征可以描述更高阶的大脑功能连接（FC）。以前，我们提出了基于 FC 地形分布的高阶 FC（HOFC），并发现该指标可以为传统 FC 提供补充信息，用于早期阿尔茨海默病（AD）的检测。然而，这种发现是否适用于网络水平的大脑功能整合尚不清楚。在本文中，我们提出了一种扩展的 HOFC 方法，称为网络间高阶 FC（IN-HOFC），作为传统网络间 FC 方法的有用补充，用于描述大规模脑网络之间更复杂的组织。在 IN-HOFC 中，网络定义和网络间 FC 都是以高阶方式定义的。为了测试 IN-HOFC 是否比传统的网络间 FC 更能检测到由于大脑疾病导致的认知下降，我们在常规方法和 IN-HOFC 中比较了 77 名轻度认知障碍（MCI）患者和 89 名对照组。结果表明，在 MCI 中，三个与颞叶相关的高阶网络之间的 IN-HOFC 减弱。IN-HOFC 的损伤尤其在前内侧和后内侧颞叶之间发现，这可能是网络水平上潜在的 MCI 生物标志物。然而，竞争的网络级低阶 FC 方法要么揭示的差异较小，要么未能检测到任何组间差异。这项工作证明了 IN-HOFC 在临床神经科学研究中的生物学意义和潜在诊断价值。
