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Dataset of whole-brain resting-state fMRI of 227 young and elderly adults acquired at 3T
Stockholm University, Faculty of Social Sciences, Department of Psychology, Biological psychology.ORCID iD: 0000-0001-6710-1744
Stockholm University, Faculty of Social Sciences, Department of Psychology, Biological psychology.
Stockholm University, Faculty of Social Sciences, Department of Psychology, Clinical psychology.
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2021 (English)In: Data in Brief, E-ISSN 2352-3409, Vol. 38, article id 107333Article in journal (Refereed) Published
Abstract [en]

To investigate the impact of adult age on the brain functional connectivity, whole-brain resting-state functional magnetic resonance imaging (R-fMRI) data were acquired on a 3T clinical MRI scanner in a cohort of 227, right-handed, native Swedish-speaking, healthy adult volunteers (N=227, aged 18-74 years old, male/female=99/128). The dataset is mainly consisted of a younger (18-30 years old n=124, males/females=51/73) and elderly adult (n=76, 60-76 years old, males/females=35/41) subgroups. The dataset was analyzed using a new data-driven analysis (QDA) framework. With QDA two types of threshold-free voxel-wise resting-state functional connectivity (RFC) metrics were derived: the connectivity strength index (CSI) and connectivity density index (CDI), which can be utilized to assess the brain changes in functional connectivity associated with adult age. The dataset can also be useful as a reference to identify abnormal changes in brain functional connectivity resulted from neurodegenerative or neuropsychiatric disorders.

Place, publisher, year, edition, pages
2021. Vol. 38, article id 107333
Keywords [en]
Quantitative data-driven analysis (QDA), Resting-state functional magnetic resonance imaging (R-fMRI), Resting-state functional connectivity (RFC), Connectivity strength index (CSI), Connectivity density index (CDI), adult age
National Category
Psychology
Research subject
Psychology
Identifiers
URN: urn:nbn:se:su:diva-198142DOI: 10.1016/j.dib.2021.107333ISI: 000702923300012OAI: oai:DiVA.org:su-198142DiVA, id: diva2:1606965
Note

This work was supported by China Scholarship Council, Zhejiang Natural Science Foundation of China (No. LY18E070005), Key Research and Development Program of Zhejiang Province (No. 2020C03020), and Stockholm Regional ALF fund.

Available from: 2021-10-29 Created: 2021-10-29 Last updated: 2022-02-25Bibliographically approved

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Fischer, HåkanManzouri, AmirhosseinMånsson, Kristoffer N. T.Li, Tie-Qiang

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