Dataset of whole-brain resting-state fMRI of 227 young and elderly adults acquired at 3T

Xia Li; Håkan Fischer; Amirhossein Manzouri; Kristoffer N.T. Månsson; Tie-Qiang Li

Data in Brief (Oct 2021)

Dataset of whole-brain resting-state fMRI of 227 young and elderly adults acquired at 3T

Xia Li,
Håkan Fischer,
Amirhossein Manzouri,
Kristoffer N.T. Månsson,
Tie-Qiang Li

Affiliations

Xia Li: Institute of Informatics Engineering, China Jiliang University, Hangzhou, China
Håkan Fischer: Department of Psychology, Stockholm University, Sweden; Stockholm University Brain Imaging Centre, Sweden
Amirhossein Manzouri: Department of Psychology, Stockholm University, Sweden
Kristoffer N.T. Månsson: Department of Psychology, Stockholm University, Sweden
Tie-Qiang Li: Institute of Informatics Engineering, China Jiliang University, Hangzhou, China; Department of Clinical Science, Intervention, and Technology, Karolinska Institute, Sweden; Department of Medical Radiation and Nuclear Medicine, Karolinska University Hospital, Sweden; Corresponding author at: Department of Clinical Science, Intervention, and Technology, Karolinska Institutet, Sweden

Journal volume & issue: Vol. 38
p. 107333

Abstract

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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.

Published in Data in Brief

ISSN: 2352-3409 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Medicine: Medicine (General): Computer applications to medicine. Medical informatics; Science: Science (General)
Website: http://www.journals.elsevier.com/data-in-brief/

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