Early brain development is characterized by the formation of a highly
organized structural connectome. The interconnected nature of this connectome
underlies the brain's cognitive abilities and influences its response to
diseases and environmental factors. Hence, quantitative assessment of
structural connectivity in the perinatal stage is useful for studying normal
and abnormal neurodevelopment. However, estimation of the connectome from
diffusion MRI data involves complex computations. For the perinatal period,
these computations are further challenged by the rapid brain development and
imaging difficulties. Combined with high inter-subject variability, these
factors make it difficult to chart the normal development of the structural
connectome. As a result, there is a lack of reliable normative baselines of
structural connectivity metrics at this critical stage in brain development. In
this study, we developed a computational framework, based on spatio-temporal
averaging, for determining such baselines. We used this framework to analyze
the structural connectivity between 33 and 44 postmenstrual weeks using data
from 166 subjects. Our results unveiled clear and strong trends in the
development of structural connectivity in perinatal stage. Connection weighting
based on fractional anisotropy and neurite density produced the most consistent
results. We observed increases in global and local efficiency, a decrease in
characteristic path length, and widespread strengthening of the connections
within and across brain lobes and hemispheres. We also observed asymmetry
patterns that were consistent between different connection weighting
approaches. The new computational method and results are useful for assessing
normal and abnormal development of the structural connectome early in life.

早期脑发育的组织联系相连接机构形成高度有序的结构连接组。通过该连接组的相互连接性，大脑的认知能力受到影响，并对疾病和环境因素产生影响。因此，对围产期阶段的结构连接进行定量评估有助于研究正常和异常的神经发展。然而，从扩散 MRI 数据中估计连接组涉及复杂的计算。对于围产期，这些计算进一步受到脑快速发育和图像难度的挑战。加上高主体间变异性，这些因素使得在脑发育的这一关键阶段建立结构连接的可靠参考基线变得困难。在本研究中，我们开发了一个基于时空平均的计算框架来确定此类基线。我们使用该框架来分析来自 166 个主体的 33 到 44 周月经后的结构连接。我们的结果揭示了围产期结构连通性发展中的明确且强烈的趋势。基于纤维状异性和神经树突密度的连接权重产生了最一致的结果。我们观察到全局和局部效率的增加，特征路径长度的减小，以及大脑叶和半球内外之间连接的广泛增强。我们还观察到不同连接权重方法之间一致的不对称模式。这种新的计算方法和结果在早期评估结构连接的正常和异常发展中非常有用。