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

By Jason R. Taylor, Nitin Williams, Rhodri Cusack, Tibor Auer, Meredith A. Shafto, Marie Dixon, Lorraine K. Tyler, Cam-CAN Group, Richard N. Henson. NeuroImage, 2017

729 citations recorded by the source corpus.

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.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/af905255bb478690f10ab5c04b988c4d99820ea3

How researchers see this paper

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In Cognitive Neuroscience

1. Alexandre Gramfort
2. Yousra Bekhti
3. Mainak Jas
4. Denis-Alexander Engemann
5. Federico Raimondo

In Radiology, Nuclear Medicine and Imaging

1. Alexandre Gramfort
2. Mainak Jas
3. Denis-Alexander Engemann

Citations in the corpus

• A massive 7T fMRI dataset to bridge cognitive neuroscience and artificial intelligence (2021, neutral): “53 ).”
• Autoreject: Automated artifact rejection for MEG and EEG data (2016, background): “Examples of such large electrophysiological datasets include the Human Connectome Project (HCP) (Van Essen et al., 2012; Larson-Prior et al., 2013), the Physiobank (Goldberger et al., 2000), the OMEGA archive (Niso et al., 2016) and Cam-CAN (Taylor et al., 2015).”
• Human alpha frequency and expression across the lifespan: a 2,172-participant electrophysiology-MRI atlas (2026, unknown): “Published cohort descriptions are available for HBN [31], CamCAN [32], OMEGA [33], LEMON [34], and MOUS [35].”
• Model selection for spectral parameterization (2024, unknown): “We applied ms-specparam to resting-state MEG data from the Cam-CAN repository (N=606; Shafto et al., 2014; Taylor et al., 2017).”
• Stability of spectral estimates in resting-state magnetoencephalography: Recommendations for minimal data duration with neuroanatomical specificity (2021, unknown): “, 2016) and the Cambridge Centre for Ageing and Neuroscience dataset (Cam-CAN; Shafto et al., 2014; Taylor et al., 2017).”