Loneliness inside of the brain: evidence from a large dataset of resting-state fMRI in young adult.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
12 05 2022
Historique:
received: 25 01 2022
accepted: 25 04 2022
entrez: 13 5 2022
pubmed: 14 5 2022
medline: 18 5 2022
Statut: epublish

Résumé

Although loneliness itself is a natural emotion, prolonged loneliness is detrimental to human health. Despite its detrimental effect, few loneliness-related neuroimaging studies have been published and some have limitations on the sample size number. This study aims to find the difference in resting-state functional connectivity associated with loneliness within a big sample size via the seed-based approach. Functional connectivity analysis was performed on a large cohort of young adults (N = 1336) using the seed-based functional connectivity approach to address the concern from previous studies. The analysis yielded statistically significant positive correlations between loneliness and functional connectivities between the inferior frontal gyrus and supplementary motor area, precentral gyrus, and superior parietal lobule. Additionally, the analysis replicated a finding from a previous study, which is increased functional connectivities between the inferior frontal gyrus and supplementary motor area. In conclusion, greater loneliness is reflected by stronger functional connectivity of the visual attention brain area.

Identifiants

pubmed: 35550564
doi: 10.1038/s41598-022-11724-5
pii: 10.1038/s41598-022-11724-5
pmc: PMC9098468
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

7856

Informations de copyright

© 2022. The Author(s).

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Auteurs

Denilson Brilliant T (D)

Department of Advanced Brain Science, Institute of Development, Ageing and Cancer, Tohoku University, Sendai, Japan. denilson.brilliant.tjoktandwinata.p3@dc.tohoku.ac.jp.

Hikaru Takeuchi (H)

Division of Developmental Cognitive Neuroscience, Institute of Development, Ageing and Cancer, Tohoku University, Sendai, Japan.

Rui Nouchi (R)

Smart-Aging Research Center, Tohoku University, Sendai, Japan.
Departments of Cognitive Health Science, Institute of Development, Ageing and Cancer, Tohoku University, Sendai, Japan.

Ryoichi Yokoyama (R)

Suwa Red Cross Hospital, Suwa, Japan.

Yuka Kotozaki (Y)

Division of Clinical Research, Medical-Industry Translational Research Center, Fukushima Medical University School of Medicine, Fukushima, Japan.

Seishu Nakagawa (S)

Department of Human Brain Science, Institute of Development, Ageing and Cancer, Tohoku University, Sendai, Japan.
Division of Psychiatry, Tohoku Medical and Pharmaceutical University, Sendai, Japan.

Sugiko Hanawa (S)

Department of Human Brain Science, Institute of Development, Ageing and Cancer, Tohoku University, Sendai, Japan.

Atsushi Sekiguchi (A)

Department of Behavioral Medicine, National Center of Neurology and Psychiatry, National Institute of Mental Health, Tokyo, Japan.

Shigeyuki Ikeda (S)

RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.

Kohei Sakaki (K)

Department of Advanced Brain Science, Institute of Development, Ageing and Cancer, Tohoku University, Sendai, Japan.

Kelssy Hitomi Dos Santos Kawata (KHDS)

Department of Mechanical and Intelligent Systems Engineering, The University of Electro-Communications, Tokyo, Japan.

Takayuki Nozawa (T)

Research Institute for the Earth Inclusive Sensing, Tokyo Institute of Technology, Tokyo, Japan.

Susumu Yokota (S)

Faculty of Arts and Science, Kyushu University, Fukuoka, Japan.

Daniele Magistro (D)

Department of Sport Science, Nottingham Trent University, Nottingham, England.

Ryuta Kawashima (R)

Department of Advanced Brain Science, Institute of Development, Ageing and Cancer, Tohoku University, Sendai, Japan.
Division of Developmental Cognitive Neuroscience, Institute of Development, Ageing and Cancer, Tohoku University, Sendai, Japan.
Smart-Aging Research Center, Tohoku University, Sendai, Japan.

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Classifications MeSH