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多主体、多模态人类神经影像学数据集。

A multi-subject, multi-modal human neuroimaging dataset.

机构信息

Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts 02129, USA ; MRC Cognition & Brain Sciences Unit , Cambridge CB2 7EF, England.

MRC Cognition & Brain Sciences Unit , Cambridge CB2 7EF, England.

出版信息

Sci Data. 2015 Jan 20;2:150001. doi: 10.1038/sdata.2015.1. eCollection 2015.

Abstract

We describe data acquired with multiple functional and structural neuroimaging modalities on the same nineteen healthy volunteers. The functional data include Electroencephalography (EEG), Magnetoencephalography (MEG) and functional Magnetic Resonance Imaging (fMRI) data, recorded while the volunteers performed multiple runs of hundreds of trials of a simple perceptual task on pictures of familiar, unfamiliar and scrambled faces during two visits to the laboratory. The structural data include T1-weighted MPRAGE, Multi-Echo FLASH and Diffusion-weighted MR sequences. Though only from a small sample of volunteers, these data can be used to develop methods for integrating multiple modalities from multiple runs on multiple participants, with the aim of increasing the spatial and temporal resolution above that of any one modality alone. They can also be used to integrate measures of functional and structural connectivity, and as a benchmark dataset to compare results across the many neuroimaging analysis packages. The data are freely available from https://openfmri.org/.

摘要

我们描述了在同一 19 名健康志愿者身上获取的多种功能和结构神经影像学模态的数据。功能数据包括脑电图 (EEG)、脑磁图 (MEG) 和功能磁共振成像 (fMRI) 数据,这些数据是在志愿者在实验室两次访问期间执行多次数百次简单感知任务的图片的熟悉、不熟悉和打乱的面孔时记录的。结构数据包括 T1 加权 MPRAGE、多回波 FLASH 和弥散加权 MR 序列。尽管仅来自一小部分志愿者,但这些数据可用于开发方法,以便整合来自多个参与者的多个运行的多种模态,目的是提高任何单一模态的空间和时间分辨率。它们还可用于整合功能和结构连通性的度量,并作为基准数据集,以便在许多神经影像学分析软件包之间比较结果。这些数据可从 https://openfmri.org/ 免费获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3a4/4412149/9dcdf559d2a3/sdata20151-f1.jpg

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