Whole‐brain functional connectivity correlates of obesity phenotypes

Dysregulated neural mechanisms in reward and somatosensory circuits result in an increased appetitive drive for and reduced inhibitory control of eating, which in turn causes obesity. Despite many studies investigating the brain mechanisms of obesity, the role of macroscale whole‐brain functional co...

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Published inHuman brain mapping Vol. 41; no. 17; pp. 4912 - 4924
Main Authors Park, Bo‐yong, Byeon, Kyoungseob, Lee, Mi Ji, Chung, Chin‐Sang, Kim, Se‐Hong, Morys, Filip, Bernhardt, Boris, Dagher, Alain, Park, Hyunjin
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 01.12.2020
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Summary:Dysregulated neural mechanisms in reward and somatosensory circuits result in an increased appetitive drive for and reduced inhibitory control of eating, which in turn causes obesity. Despite many studies investigating the brain mechanisms of obesity, the role of macroscale whole‐brain functional connectivity remains poorly understood. Here, we identified a neuroimaging‐based functional connectivity pattern associated with obesity phenotypes by using functional connectivity analysis combined with machine learning in a large‐scale (n ~ 2,400) dataset spanning four independent cohorts. We found that brain regions containing the reward circuit positively associated with obesity phenotypes, while brain regions for sensory processing showed negative associations. Our study introduces a novel perspective for understanding how the whole‐brain functional connectivity correlates with obesity phenotypes. Furthermore, we demonstrated the generalizability of our findings by correlating the functional connectivity pattern with obesity phenotypes in three independent datasets containing subjects of multiple ages and ethnicities. Our findings suggest that obesity phenotypes can be understood in terms of macroscale whole‐brain functional connectivity and have important implications for the obesity neuroimaging community.
Bibliography:Funding information
Fonds de la Recherche du Québec ‐ Santé (FRQ‐S), Grant/Award Number: Postdoctoral Training; Institute for Basic Science, Grant/Award Number: IBS‐R015‐D1; Korean government under the AI Graduate School Support Program, Grant/Award Number: 2019‐0‐00421; MIST (Ministry of Science and ICT) of Korea under the ITRC (Information Technology Research Center), Grant/Award Number: IITP‐2020‐2018‐0‐01798 National Research Foundation of Korea (NRF‐2020M3E5D2A01084892); Montreal Neurological Institute and Hospital (MNI), Grant/Award Number: Molson Neuro‐Engineering Fellowship
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Funding information Fonds de la Recherche du Québec ‐ Santé (FRQ‐S), Grant/Award Number: Postdoctoral Training; Institute for Basic Science, Grant/Award Number: IBS‐R015‐D1; Korean government under the AI Graduate School Support Program, Grant/Award Number: 2019‐0‐00421; MIST (Ministry of Science and ICT) of Korea under the ITRC (Information Technology Research Center), Grant/Award Number: IITP‐2020‐2018‐0‐01798 National Research Foundation of Korea (NRF‐2020M3E5D2A01084892); Montreal Neurological Institute and Hospital (MNI), Grant/Award Number: Molson Neuro‐Engineering Fellowship
ISSN:1065-9471
1097-0193
1097-0193
DOI:10.1002/hbm.25167