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. 2018 Oct 11:12:741.
doi: 10.3389/fnins.2018.00741. eCollection 2018.

Structural and Functional Brain Connectivity Changes Between People With Abdominal and Non-abdominal Obesity and Their Association With Behaviors of Eating Disorders

Bo-Yong Park  1   2 , Mi Ji Lee  3 , Mansu Kim  1   2 , Se-Hong Kim  4 , Hyunjin Park  2   5
Affiliations

Structural and Functional Brain Connectivity Changes Between People With Abdominal and Non-abdominal Obesity and Their Association With Behaviors of Eating Disorders

Bo-Yong Park et al. Front Neurosci. .

Abstract

Abdominal obesity is important for understanding obesity, which is a worldwide medical problem. We explored structural and functional brain differences in people with abdominal and non-abdominal obesity by using multimodal neuroimaging and up-to-date analysis methods. A total of 274 overweight people, whose body mass index exceeded 25, were enrolled in this study. Participants were divided into abdominal and non-abdominal obesity groups using a waist-hip ratio threshold of 0.9 for males and 0.85 for females. Structural and functional brain differences were assessed with diffusion tensor imaging and resting-state functional magnetic resonance imaging. Centrality measures were computed from structural fiber tractography, and static and dynamic functional connectivity matrices. Significant inter-group differences in structural and functional connectivity were found using degree centrality (DC) values. The associations between the DC values of the identified regions/networks and behaviors of eating disorder scores were explored. The highest association was achieved by combining DC values of the cerebral peduncle, anterior corona radiata, posterior corona radiata (from structural connectivity), frontoparietal network (from static connectivity), and executive control network (from dynamic connectivity) compared to the use of structural or functional connectivity only. Our results demonstrated the effectiveness of multimodal imaging data and found brain regions or networks that may be responsible for behaviors of eating disorders in people with abdominal obesity.

Keywords: abdominal obesity; eating disorder behaviors; multimodal imaging analysis; probabilistic fiber tractography; static and dynamic connectivity analysis.

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Figures

FIGURE 1
FIGURE 1
Flowchart of processing steps adopted in this analysis.
FIGURE 2
FIGURE 2
(A) ROIs used in this study. (Left) ICBM DTI-81 atlas and (right) 16 functionally interpretable ICs. (B) Brain regions and networks that showed significant associations with EDE-Q scores. VN, visual network; DMN, default mode network; ECN, executive control network; FPN, frontoparietal network; SMN, sensorimotor network; AN, auditory network; BG, basal ganglia.
FIGURE 3
FIGURE 3
Nine group-level brain states. VN, visual network; DMN, default mode network; ECN, executive control network; FPN, frontoparietal network; SMN, sensorimotor network; AN, auditory network; BG, basal ganglia.
FIGURE 4
FIGURE 4
Representative networks of each group-level states. Elements of the matrix represent the hubness of BC. Representative networks are marked with the symbols “+.” VN, visual network; DMN, default mode network; ECN, executive control network; FPN, frontoparietal network; SMN, sensorimotor network; AN, auditory network; BG, basal ganglia; ICs, independent components.
See this image and copyright information in PMC

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