NCANDA

该数据集包含了12至21岁参与者的纵向静息态功能性磁共振成像（rs-fMRI）和弥散张量成像（DTI）数据，主要关注利用神经影像数据来预测参与者的年龄和性别。根据Cahalan量表，参与者在过去一年内的酒精摄入量为无至低。数据处理过程包括运动校正、异常值检测和空间平滑。数据集规模为662名参与者，共1976对扫描数据（平均每位参与者进行了3次访问）。任务是基于神经影像数据预测参与者的年龄和性别。

This dataset contains longitudinal resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) data from participants aged 12 to 21 years. Its core objective is to predict the age and gender of participants using neuroimaging data. According to the Cahalan Scale, the participants' alcohol consumption over the past year ranges from none to low. The data processing workflow includes motion correction, outlier detection, and spatial smoothing. The dataset comprises 662 participants with a total of 1976 scan pairs, with an average of 3 visits per participant. The task is to predict the participants' age and gender based on neuroimaging data.