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

Taylor, Jason R.; Williams, Nitin; Cusack, Rhodri; Auer, Tibor; Shafto, Meredith A.; Dixon, Marie; Tyler, Lorraine K.; Cam‐CAN,; Henson, Richard N.

doi:10.1016/j.neuroimage.2015.09.018

Cited by 573 publications

(639 citation statements)

References 36 publications

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“…For preprocessing details, see Taylor et al (2017). In short, we used Automatic Analysis (AA version 4.0; Cusack et al, 2014) pipelines and modules, which called functions from SPM12 (Wellcome Department of Imaging Neuroscience, London, UK; Friston et al, 2007).…”

Section: Methodsmentioning

confidence: 99%

Activity and Connectivity Differences Underlying Inhibitory Control Across the Adult Life Span

et al. 2018

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Inhibitory control requires precise regulation of activity and connectivity within multiple brain networks. Previous studies have typically evaluated age-related changes in regional activity or changes in interregional interactions. Instead, we test the hypothesis that activity and connectivity make distinct, complementary contributions to performance across the life span and the maintenance of successful inhibitory control systems. A representative sample of healthy human adults in a large, population-based life span cohort performed an integrated Stop-Signal (SS)/No-Go task during functional magnetic resonance imaging (n = 119; age range, 18–88 years). Individual differences in inhibitory control were measured in terms of the SS reaction time (SSRT), using the blocked integration method. Linear models and independent components analysis revealed that individual differences in SSRT correlated with both activity and connectivity in a distributed inhibition network, comprising prefrontal, premotor, and motor regions. Importantly, this pattern was moderated by age, such that the association between inhibitory control and connectivity, but not activity, differed with age. Multivariate statistics and out-of-sample validation tests of multifactorial functional organization identified differential roles of activity and connectivity in determining an individual's SSRT across the life span. We propose that age-related differences in adaptive cognitive control are best characterized by the joint consideration of multifocal activity and connectivity within distributed brain networks. These insights may facilitate the development of new strategies to support cognitive ability in old age.SIGNIFICANCE STATEMENT The preservation of cognitive and motor control is crucial for maintaining well being across the life span. We show that such control is determined by both activity and connectivity within distributed brain networks. In a large, population-based cohort, we used a novel whole-brain multivariate approach to estimate the functional components of inhibitory control, in terms of their activity and connectivity. Both activity and connectivity in the inhibition network changed with age. But only the association between performance and connectivity, not activity, differed with age. The results suggest that adaptive control is best characterized by the joint consideration of multifocal activity and connectivity. These insights may facilitate the development of new strategies to maintain cognitive ability across the life span in health and disease.

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Section: Methodsmentioning

confidence: 99%

Activity and Connectivity Differences Underlying Inhibitory Control Across the Adult Life Span

et al. 2018

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“…and the Cambridge Centre for Ageing and Neuroscience 13 (Cam-CAN) (n=588, M age = 52.31; SD = 17.38, 50 % female) from the Cambridge Center for Ageing and Neuroscience 14 (CamCAN). Data used in the preparation of this work were obtained from the CamCAN repository (available at http://www.mrc-cbu.cam.ac.uk/datasets/camcan/) 13, 14 . All procedures were in accordance with relevant IRBs.…”

Section: Methodsmentioning

confidence: 99%

An augmented aging process in brain white matter in HIV

Kuhn

Kaufmann

Doan

et al. 2018

Human Brain Mapping

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“…To test the applicability of the fully automated habenula segmentation on more commonly available lower resolution (e.g., 1.0 mm isotropic) 3T anatomical data, a public dataset of 40 subjects (mean age 28.4 years, range 20–34 years, 25 females) were obtained from the CamCAN repository (http://www.mrc-cbu.cam.ac.uk/datasets/camcan; Taylor et al, ) and analyzed similarly. Anatomical acquisition parameters: T1w MPRAGE, 1.0 mm isotropic resolution, TR/TI/TE = 2250/900/2.98 ms, FA = 9°, in‐plane acceleration (GRAPPA) factor 2, total acquisition time 4.5 min; and T2w SPACE, 1.0 mm isotropic resolution, TR/TE = 2800/408 ms, in‐plane acceleration (GRAPPA) factor 2, total acquisition time 4.5 min (Shafto et al, ).…”

Section: Methodsmentioning

confidence: 99%

Reproducibility of myelin content‐based human habenula segmentation at 3 Tesla

Kim

Naidich

Joseph

et al. 2018

Human Brain Mapping

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In vivo morphological study of the human habenula, a pair of small epithalamic nuclei adjacent to the dorsomedial thalamus, has recently gained significant interest for its role in reward and aversion processing. However, segmenting the habenula from in vivo magnetic resonance imaging (MRI) is challenging due to the habenula's small size and low anatomical contrast. Although manual and semi-automated habenula segmentation methods have been reported, the test-retest reproducibility of the segmented habenula volume and the consistency of the boundaries of habenula segmentation have not been investigated. In this study, we evaluated the intra- and inter-site reproducibility of in vivo human habenula segmentation from 3T MRI (0.7-0.8 mm isotropic resolution) using our previously proposed semi-automated myelin contrast-based method and its fully-automated version, as well as a previously published manual geometry-based method. The habenula segmentation using our semi-automated method showed consistent boundary definition (high Dice coefficient, low mean distance, and moderate Hausdorff distance) and reproducible volume measurement (low coefficient of variation). Furthermore, the habenula boundary in our semi-automated segmentation from 3T MRI agreed well with that in the manual segmentation from 7T MRI (0.5 mm isotropic resolution) of the same subjects. Overall, our proposed semi-automated habenula segmentation showed reliable and reproducible habenula localization, while its fully-automated version offers an efficient way for large sample analysis.

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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

Cited by 573 publications

References 36 publications

Activity and Connectivity Differences Underlying Inhibitory Control Across the Adult Life Span

Activity and Connectivity Differences Underlying Inhibitory Control Across the Adult Life Span

An augmented aging process in brain white matter in HIV

Reproducibility of myelin content‐based human habenula segmentation at 3 Tesla

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