Association between high levels of body-esteem and increased degree of midcingulate cortex global connectivity: A resting-state fMRI study.
Ximei ChenMingyue XiaoJingmin QinZiming BianJiang QiuTingyong FengQinghua HeXu LeiHong ChenPublished in: Psychophysiology (2022)
Multiple neuroimaging studies have examined the neural underpinnings of body image disturbances in patients with eating disorders. However, key brain regions related to body image, such as body-esteem (BE), among healthy individuals are understudied. Given the extremely crucial role of BE in eating behaviors and physical and mental health, the current study conducted data-driven analysis and characterized the neurobiological correlates of BE with the network properties of the resting brain using the voxel-wise degree centrality (DC) measures of resting-state functional magnetic resonance imaging (rs-fMRI) data and seed-based resting-state functional connectivity (RSFC). A total of 694 healthy young adults (females = 474, mean age = 18.38 years, range = 17-22) underwent rs-fMRI, and completed the Body-Esteem Scale for Adolescents and Adults, the Eating Disorder Diagnosis Scale, and the Restraint Scale. After correcting for differences in age, gender, body mass index, and head motion, whole-brain correlation analyses revealed that a high level of BE was associated with increased DC within the right midcingulate cortex (MCC) and subsequent high levels of MCC-based RSFC strengths. Furthermore, MCC connectivity patterns related to BE were inversely associated with disordered eating behaviors. These findings suggest that adaptive cognitive and emotional regulation (i.e., self-evaluation and emotion based on body image) may explain the potential relationship between MCC connectivity patterns and BE to a certain extent. As such, future studies should investigate these interesting possibilities.
Keyphrases
- resting state
- functional connectivity
- mental health
- young adults
- physical activity
- magnetic resonance imaging
- dendritic cells
- depressive symptoms
- electronic health record
- big data
- current status
- blood pressure
- mental illness
- subarachnoid hemorrhage
- high resolution
- deep learning
- optical coherence tomography
- data analysis