The reorganization of communication hubs coordinate neurofunctional network development in children’s visual word processing

The folder "Individual_ESI_matrix.zip" is the dataset for the task-related electrical source imaging dynamics when the subjects were passively viewing visual Chinese character, human face, and common object. The source localization was based on functional brain region parcellations, and the automated anatomical labeling (AAL) parcellation with 90 brain regions across the whole brain was adopted.The folder "Individual_FCs_matrix.zip" is the dataset for the task-related functional connectivity edge (debiased weighted phase lag index) between each two brain regions. The dwPLI of each pair was averaged at the dimension of trial, timestep (0–600ms), and frequency (9–30Hz) to represent the FCs.The folder "Individual_DOC_matrix.zip" is the dataset for the task-related hubness of each node. We employed DOC as an unbiased, count-based graph-theory measurement to assess the intensity of hubness of every region in the brain. Based on the graph theory of functional network, the centrality is defined as the sum of weights from edges connecting to a node.文件夹“Individual_ESI_matrix.zip”为被试被动观看视觉呈现的汉字、人脸与常见物体时，对应的任务相关脑电源成像（electrical source imaging, ESI）动力学数据集。该数据集的源定位基于脑功能分区，采用覆盖全脑共90个脑区的自动解剖标记（automated anatomical labeling, AAL）分区方案。 文件夹“Individual_FCs_matrix.zip”为任务相关的脑区两两间功能连接（functional connectivity, FC）边数据集，其连接指标为去偏加权相位滞后指数（debiased weighted phase lag index, dwPLI）。每一对脑区的dwPLI会在试次、时间步长（0–600ms）与频率（9–30Hz）三个维度上取平均，以此表征功能连接强度。 文件夹“Individual_DOC_matrix.zip”为任务相关的各节点中心性数据集。本研究采用DOC作为一种基于计数的无偏图论指标，用以评估大脑各区域的枢纽性强度。基于功能网络的图论定义，节点中心性被定义为该节点所连接的全部边的权重之和。