The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample.

The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample.
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DOI:
10.1016/j.neuroimage.2015.09.018
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发表时间:
2017-01
期刊:
影响因子:
5.7
通讯作者:
Henson RN
Henson RN
中科院分区:
医学1区
文献类型:
--
作者:
Taylor JR;Williams N;Cusack R;Auer T;Shafto MA;Dixon M;Tyler LK;Cam-Can;Henson RN

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本文描述了剑桥老龄化和神经科学中心(Cam-CAN)初始研究队列的数据存储库。Cam-CAN第2阶段存储库包含来自大型(约N = 700),横断面成人寿命(18-87岁)人群样本的多模态(MRI, MEG和认知行为)数据。该研究旨在描述认知、大脑结构和功能与年龄相关的变化,并揭示支持健康认知衰老的神经认知机制。该数据库包含原始和预处理的结构MRI、功能MRI(活动任务和静息状态)和MEG数据(活动任务和静息状态),以及跨越五大领域(注意力、情感、行动、语言和记忆)的认知行为实验的衍生分数,以及人口统计学和神经心理学数据。因此,该数据集提供了目前无与伦比的深度神经认知表型,能够对大脑结构、脑功能和认知的年龄相关变化进行综合分析,并为多模态神经成像数据的新分析提供了一个测试平台。多模态MRI, fMRI和MEG神经成像数据认知表型前所未有的深度在大脑结构,功能和认知年龄相关的差异
This paper describes the data repository for the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) initial study cohort. The Cam-CAN Stage 2 repository contains multi-modal (MRI, MEG, and cognitive-behavioural) data from a large (approximately N = 700), cross-sectional adult lifespan (18–87 years old) population-based sample. The study is designed to characterise age-related changes in cognition and brain structure and function, and to uncover the neurocognitive mechanisms that support healthy cognitive ageing. The database contains raw and preprocessed structural MRI, functional MRI (active tasks and resting state), and MEG data (active tasks and resting state), as well as derived scores from cognitive behavioural experiments spanning five broad domains (attention, emotion, action, language, and memory), and demographic and neuropsychological data. The dataset thus provides a depth of neurocognitive phenotyping that is currently unparalleled, enabling integrative analyses of age-related changes in brain structure, brain function, and cognition, and providing a testbed for novel analyses of multi-modal neuroimaging data. Cross-sectional uniform adult-lifespan population-based data Multimodal MRI, fMRI and MEG neuroimaging data Unprecedented depth of cognitive phenotyping Age-related differences in brain structure, function, and cognition
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