Zhang Shu, He Zhibin, Du Lei, Zhang Yin, Yu Sigang, Wang Ruoyang, Hu Xintao, Jiang Xi, Zhang Tuo
Center for Brain and Brain-Inspired Computing Research, School of Computer Science, Northwestern Polytechnical University, Xi'an, China.
School of Automation, Northwestern Polytechnical University, Xi'an, China.
Front Neurosci. 2021 Oct 6;15:724391. doi: 10.3389/fnins.2021.724391. eCollection 2021.
Preterm is a worldwide problem that affects infants' lives significantly. Moreover, the early impairment is more than limited to isolated brain regions but also to global and profound negative outcomes later, such as cognitive disorder. Therefore, seeking the differences of brain connectome between preterm and term infant brains is a vital step for understanding the developmental impairment caused by preterm. Existing studies revealed that studying the relationship between brain function and structure, and further investigating their differentiable connectomes between preterm and term infant brains is a way to comprehend and unveil the differences that occur in the preterm infant brains. Therefore, in this article, we proposed a novel canonical correlation analysis (CCA) with locality preserving projection (LPP) approach to investigate the relationship between brain functional and structural connectomes and how such a relationship differs between preterm and term infant brains. CCA is proposed to study the relationship between functional and structural connections, while LPP is adopted to identify the distinguishing features from the connections which can differentiate the preterm and term brains. After investigating the whole brain connections on a fine-scale connectome approach, we successfully identified 89 functional and 97 structural connections, which mostly contributed to differentiate preterm and term infant brains from the functional MRI (fMRI) and diffusion MRI (dMRI) of the public developing Human Connectome Project (dHCP) dataset. By further exploring those identified connections, the results innovatively revealed that the identified functional connections are short-range and within the functional network. On the contrary, the identified structural connections are usually remote connections across different functional networks. In addition, these connectome-level results show the new insights that longitudinal functional changes could deviate from longitudinal structural changes in the preterm infant brains, which help us better understand the brain-behavior changes in preterm infant brains.
早产是一个全球性问题，对婴儿的生命有重大影响。此外，早期损伤不仅局限于孤立的脑区，还会导致后期全面而严重的负面后果，如认知障碍。因此，探寻早产和足月婴儿大脑之间脑连接组的差异，是理解早产所致发育损伤的关键一步。现有研究表明，研究脑功能与结构之间的关系，并进一步探究早产和足月婴儿大脑之间可区分的连接组，是理解和揭示早产婴儿大脑中出现的差异的一种方法。因此，在本文中，我们提出了一种新的结合局部保持投影（LPP）的典型相关分析（CCA）方法，以研究脑功能连接组和结构连接组之间的关系，以及这种关系在早产和足月婴儿大脑之间有何不同。提出CCA来研究功能连接和结构连接之间的关系，同时采用LPP从连接中识别出能够区分早产和足月大脑的显著特征。在以精细尺度连接组方法研究全脑连接后，我们成功识别出89个功能连接和97个结构连接，这些连接在很大程度上有助于根据公开的人类连接组计划发育中数据集（dHCP）的功能磁共振成像（fMRI）和扩散磁共振成像（dMRI）区分早产和足月婴儿大脑。通过进一步探索这些识别出的连接，结果创新性地表明，识别出的功能连接是短程的且在功能网络内。相反，识别出的结构连接通常是跨不同功能网络的远程连接。此外，这些连接组水平的结果显示了新的见解，即早产婴儿大脑中的纵向功能变化可能偏离纵向结构变化，这有助于我们更好地理解早产婴儿大脑中的脑-行为变化。
