Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States.
Neurosciences Graduate Program, Washington University in St. Louis, St. Louis, MO 63110, United States.
Cereb Cortex. 2024 Jan 31;34(2). doi: 10.1093/cercor/bhae047.
The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that existing parcellations, including surface-based parcels derived from older samples as well as volume-based neonatal parcels, are a poor fit for neonatal surface data. We next derive a set of 283 cortical surface parcels from a sample of n = 261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies.
大脑皮层组织为不同但相互连接的皮层区域,这些区域可以通过皮层表面静息状态功能连接 (FC) 模式的急剧差异来定义。这种皮层分割在成人和年龄较大的婴儿中已经得到了证实,但对于新生儿大脑,还没有广泛使用的皮层表面分割方法。在这里,我们首先证明现有的分割方法,包括来自较老样本的基于表面的分割以及基于体积的新生儿分割,都不适合新生儿的表面数据。接下来,我们从 n = 261 名新生儿的样本中提取了一组 283 个皮质表面分割。这些分割具有高度同质的 FC 模式,并使用三个外部新生儿数据集进行了验证。使用 Infomap 算法为每个分割分配功能网络标识,并且得到的网络与新生儿中的先前工作一致。所提出的分割方法可能代表新生儿皮层区域,并为新生儿神经影像学研究提供了有力的工具。