200 Objects Infants EEG

Data and code for the paper: Tijl Grootswagers, Genevieve Quek, Zhen Zeng, & Manuel Varlet. 2025. “Human Infant EEG Recordings for 200 Object Images Presented in Rapid Visual Streams.” Scientific Data. https://doi.org/10.1038/s41597-025-04744-z See the linked paper for details. The "code" directory contains all the code to reproduce the figures in the paper. It requires fieldtrip and cosmomvpa, change the paths to these toolboxes at the top of each script (or remove the lines and add them to the path manually). Then run the scripts to reproduce each step reported in the paper: 1. run_preprocessing.m (preprocess and epoch data) 2. run_rsa.m (makes the individual RDMs) 3. stats_rsa.m (computes the RSA correlations) 4. plot_design.m (produces Figure 1 in the paper) 5. plot_peaks.m (produces Figure 2 in the paper) 6. plot_rsa.m (produces Figure 3 in the paper) Each script can also run standalone, as intermediate results are saved in the derivates folder本数据集配套发表论文信息如下： Tijl Grootswagers、Genevieve Quek、Zhen Zeng、Manuel Varlet，2025年，《用于快速视觉流呈现的200幅物体图像的人类婴儿脑电图（Electroencephalogram, EEG）记录》，刊载于《科学数据》（Scientific Data）。DOI：https://doi.org/10.1038/s41597-025-04744-z 详细信息请参阅该刊发论文。 `code` 目录包含复现论文中所有图表的全部代码。该代码依赖FieldTrip与CosmoMVPA工具包，请在各脚本顶部修改对应工具包的路径（或删除原有路径代码，手动将工具包添加至MATLAB运行路径）。 随后运行以下脚本即可复现论文中报道的全部研究步骤： 1. run_preprocessing.m：完成数据预处理与分段 2. run_rsa.m：生成个体表征差异矩阵（Representational Dissimilarity Matrix, RDM） 3. stats_rsa.m：计算表征相似性分析（Representational Similarity Analysis, RSA）相关性 4. plot_design.m：生成论文图1 5. plot_peaks.m：生成论文图2 6. plot_rsa.m：生成论文图3 各脚本均可独立运行，中间计算结果均保存至`derivates`目录。

搜集汇总

背景与挑战

背景概述

该数据集记录了42名婴儿在观看200个物体图像时的EEG数据，用于研究婴儿对物体图像的神经反应。数据集包含预处理和分析代码，支持重现相关研究论文中的图表结果。