混合站点fMRI数据集

该数据集由剑桥大学精神病学系创建，包含43,838个功能性磁共振成像（fMRI）数据点，用于研究自闭症和其他任务。数据集涵盖多个来源，旨在通过深度学习模型分析大脑功能连接性，特别是在自闭症与典型发展（TD）控制组的对比中。此外，数据集还用于性别和任务与休息状态的分类分析。通过这些分析，研究旨在揭示自闭症患者大脑功能连接的特定差异，以及这些差异如何影响大脑网络的整体功能。

This dataset was created by the Department of Psychiatry, University of Cambridge, and contains 43,838 functional magnetic resonance imaging (fMRI) data points for research on autism and other relevant tasks. The dataset draws from multiple sources, and is designed to analyze brain functional connectivity via deep learning models, with a particular focus on comparisons between autistic individuals and typically developing (TD) control groups. Additionally, the dataset is utilized for classification analyses related to gender, task states and resting states. Through these analyses, the research aims to uncover specific disparities in brain functional connectivity among autistic populations, as well as how these disparities influence the overall function of brain networks.