Literature DB >> 30332613

The Lifespan Human Connectome Project in Aging: An overview.

Susan Y Bookheimer1, David H Salat2, Melissa Terpstra3, Beau M Ances4, Deanna M Barch5, Randy L Buckner6, Gregory C Burgess7, Sandra W Curtiss8, Mirella Diaz-Santos9, Jennifer Stine Elam8, Bruce Fischl10, Douglas N Greve2, Hannah A Hagy3, Michael P Harms7, Olivia M Hatch2, Trey Hedden2, Cynthia Hodge7, Kevin C Japardi9, Taylor P Kuhn9, Timothy K Ly9, Stephen M Smith11, Leah H Somerville12, Kâmil Uğurbil3, Andre van der Kouwe2, David Van Essen8, Roger P Woods13, Essa Yacoub3.   

Abstract

The original Human Connectome Project yielded a rich data set on structural and functional connectivity in a large sample of healthy young adults using improved methods of data acquisition, analysis, and sharing. More recent efforts are extending this approach to include infants, children, older adults, and brain disorders. This paper introduces and describes the Human Connectome Project in Aging (HCP-A), which is currently recruiting 1200 + healthy adults aged 36 to 100+, with a subset of 600 + participants returning for longitudinal assessment. Four acquisition sites using matched Siemens Prisma 3T MRI scanners with centralized quality control and data analysis are enrolling participants. Data are acquired across multimodal imaging and behavioral domains with a focus on factors known to be altered in advanced aging. MRI acquisitions include structural (whole brain and high resolution hippocampal) plus multiband resting state functional (rfMRI), task fMRI (tfMRI), diffusion MRI (dMRI), and arterial spin labeling (ASL). Behavioral characterization includes cognitive (such as processing speed and episodic memory), psychiatric, metabolic, and socioeconomic measures as well as assessment of systemic health (with a focus on menopause via hormonal assays). This dataset will provide a unique resource for examining how brain organization and connectivity changes across typical aging, and how these differences relate to key characteristics of aging including alterations in hormonal status and declining memory and general cognition. A primary goal of the HCP-A is to make these data freely available to the scientific community, supported by the Connectome Coordination Facility (CCF) platform for data quality assurance, preprocessing and basic analysis, and shared via the NIMH Data Archive (NDA). Here we provide the rationale for our study design and sufficient details of the resource for scientists to plan future analyses of these data. A companion paper describes the related Human Connectome Project in Development (HCP-D, Somerville et al., 2018), and the image acquisition protocol common to both studies (Harms et al., 2018).
Copyright © 2018. Published by Elsevier Inc.

Entities:  

Keywords:  Brain; Connectivity; Connectomics; Diffusion imaging; Functional connectivity; MRI; Morphometry; Neuroimaging; fMRI

Mesh:

Year:  2018        PMID: 30332613      PMCID: PMC6649668          DOI: 10.1016/j.neuroimage.2018.10.009

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  130 in total

1.  Application of cortical unfolding techniques to functional MRI of the human hippocampal region.

Authors:  M M Zeineh; S A Engel; S Y Bookheimer
Journal:  Neuroimage       Date:  2000-06       Impact factor: 6.556

2.  Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery.

Authors:  J M Guralnik; L Ferrucci; C F Pieper; S G Leveille; K S Markides; G V Ostir; S Studenski; L F Berkman; R B Wallace
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2000-04       Impact factor: 6.053

3.  Longitudinal analysis of the effects of the aging process on neuropsychological test performance in the healthy young-old and oldest-old.

Authors:  S E Hickman; D B Howieson; A Dame; G Sexton; J Kaye
Journal:  Dev Neuropsychol       Date:  2000       Impact factor: 2.253

4.  Thalamic volume predicts performance on tests of cognitive speed and decreases in healthy aging. A magnetic resonance imaging-based volumetric analysis.

Authors:  Y D Van Der Werf; D J Tisserand; P J Visser; P A Hofman; E Vuurman; H B Uylings; J Jolles
Journal:  Brain Res Cogn Brain Res       Date:  2001-06

5.  Predictors of healthy brain aging.

Authors:  M Gonzales Mc Neal; S Zareparsi; R Camicioli; A Dame; D Howieson; J Quinn; M Ball; J Kaye; H Payami
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2001-07       Impact factor: 6.053

6.  The Oregon brain aging study: neuropathology accompanying healthy aging in the oldest old.

Authors:  M S Green; J A Kaye; M J Ball
Journal:  Neurology       Date:  2000-01-11       Impact factor: 9.910

7.  A validity study of the SSAGA--a comparison with the SCAN.

Authors:  M Hesselbrock; C Easton; K K Bucholz; M Schuckit; V Hesselbrock
Journal:  Addiction       Date:  1999-09       Impact factor: 6.526

8.  Frailty in older adults: evidence for a phenotype.

Authors:  L P Fried; C M Tangen; J Walston; A B Newman; C Hirsch; J Gottdiener; T Seeman; R Tracy; W J Kop; G Burke; M A McBurnie
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2001-03       Impact factor: 6.053

9.  Cardiovascular risk factors and cognitive decline in middle-aged adults.

Authors:  D Knopman; L L Boland; T Mosley; G Howard; D Liao; M Szklo; P McGovern; A R Folsom
Journal:  Neurology       Date:  2001-01-09       Impact factor: 9.910

10.  Midlife vascular risk factors and late-life mild cognitive impairment: A population-based study.

Authors:  M Kivipelto; E L Helkala; T Hänninen; M P Laakso; M Hallikainen; K Alhainen; H Soininen; J Tuomilehto; A Nissinen
Journal:  Neurology       Date:  2001-06-26       Impact factor: 9.910

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  49 in total

1.  Behavioral and Neural Signatures of Working Memory in Childhood.

Authors:  Monica D Rosenberg; Steven A Martinez; Kristina M Rapuano; May I Conley; Alexandra O Cohen; M Daniela Cornejo; Donald J Hagler; Wesley J Meredith; Kevin M Anderson; Tor D Wager; Eric Feczko; Eric Earl; Damien A Fair; Deanna M Barch; Richard Watts; B J Casey
Journal:  J Neurosci       Date:  2020-05-25       Impact factor: 6.167

2.  Age differences in specific neural connections within the Default Mode Network underlie theory of mind.

Authors:  Colleen Hughes; Brittany S Cassidy; Joshua Faskowitz; Andrea Avena-Koenigsberger; Olaf Sporns; Anne C Krendl
Journal:  Neuroimage       Date:  2019-02-19       Impact factor: 6.556

3.  Associations between cerebral blood flow and structural and functional brain imaging measures in individuals with neuropsychologically defined mild cognitive impairment.

Authors:  Chan-Mi Kim; Rachel L Alvarado; Kimberly Stephens; Hsiao-Ying Wey; Dany J J Wang; Elizabeth C Leritz; David H Salat
Journal:  Neurobiol Aging       Date:  2019-11-06       Impact factor: 4.673

4.  The Lifespan Human Connectome Project in Development: A large-scale study of brain connectivity development in 5-21 year olds.

Authors:  Leah H Somerville; Susan Y Bookheimer; Randy L Buckner; Gregory C Burgess; Sandra W Curtiss; Mirella Dapretto; Jennifer Stine Elam; Michael S Gaffrey; Michael P Harms; Cynthia Hodge; Sridhar Kandala; Erik K Kastman; Thomas E Nichols; Bradley L Schlaggar; Stephen M Smith; Kathleen M Thomas; Essa Yacoub; David C Van Essen; Deanna M Barch
Journal:  Neuroimage       Date:  2018-08-22       Impact factor: 6.556

5.  A field-monitoring-based approach for correcting eddy-current-induced artifacts of up to the 2nd spatial order in human-connectome-project-style multiband diffusion MRI experiment at 7T: A pilot study.

Authors:  Ruoyun Ma; Mehmet Akçakaya; Steen Moeller; Edward Auerbach; Kâmil Uğurbil; Pierre-François Van de Moortele
Journal:  Neuroimage       Date:  2020-04-16       Impact factor: 6.556

6.  Self-navigation for 3D multishot EPI with data-reference.

Authors:  Steen Moeller; Sudhir Ramanna; Christophe Lenglet; Pramod K Pisharady; Edward J Auerbach; Lance Delabarre; Xiaoping Wu; Mehmet Akcakaya; Kamil Ugurbil
Journal:  Magn Reson Med       Date:  2020-03-02       Impact factor: 4.668

7.  Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects.

Authors:  Michael P Harms; Leah H Somerville; Beau M Ances; Jesper Andersson; Deanna M Barch; Matteo Bastiani; Susan Y Bookheimer; Timothy B Brown; Randy L Buckner; Gregory C Burgess; Timothy S Coalson; Michael A Chappell; Mirella Dapretto; Gwenaëlle Douaud; Bruce Fischl; Matthew F Glasser; Douglas N Greve; Cynthia Hodge; Keith W Jamison; Saad Jbabdi; Sridhar Kandala; Xiufeng Li; Ross W Mair; Silvia Mangia; Daniel Marcus; Daniele Mascali; Steen Moeller; Thomas E Nichols; Emma C Robinson; David H Salat; Stephen M Smith; Stamatios N Sotiropoulos; Melissa Terpstra; Kathleen M Thomas; M Dylan Tisdall; Kamil Ugurbil; Andre van der Kouwe; Roger P Woods; Lilla Zöllei; David C Van Essen; Essa Yacoub
Journal:  Neuroimage       Date:  2018-09-24       Impact factor: 6.556

8.  Characterizing cerebral hemodynamics across the adult lifespan with arterial spin labeling MRI data from the Human Connectome Project-Aging.

Authors:  Meher R Juttukonda; Binyin Li; Randa Almaktoum; Kimberly A Stephens; Kathryn M Yochim; Essa Yacoub; Randy L Buckner; David H Salat
Journal:  Neuroimage       Date:  2021-01-29       Impact factor: 7.400

9.  Improving in vivo human cerebral cortical surface reconstruction using data-driven super-resolution.

Authors:  Qiyuan Tian; Berkin Bilgic; Qiuyun Fan; Chanon Ngamsombat; Natalia Zaretskaya; Nina E Fultz; Ned A Ohringer; Akshay S Chaudhari; Yuxin Hu; Thomas Witzel; Kawin Setsompop; Jonathan R Polimeni; Susie Y Huang
Journal:  Cereb Cortex       Date:  2021-01-01       Impact factor: 5.357

Review 10.  The scientific body of knowledge - Whose body does it serve? A spotlight on oral contraceptives and women's health factors in neuroimaging.

Authors:  Caitlin M Taylor; Laura Pritschet; Emily G Jacobs
Journal:  Front Neuroendocrinol       Date:  2020-09-28       Impact factor: 8.606

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