Gender-Related and Hemispheric Effects in Cortical Thickness-Based Hemispheric Brain Morphological Network

Objective. The current study examined gender-related differences in hemispheric asymmetries of graph metrics, calculated from a cortical thickness-based brain structural covariance network named hemispheric morphological network. Methods. Using the T1-weighted magnetic resonance imaging scans of 285...

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Bibliographic Details
Published in:BioMed research international 2020, Vol.2020 (2020), p.1-13
Main Authors: Song, Sa-Kwang, Lee, Min-Ho, Kim, Bo-Hyun, Yun, Je-Yeon, Choi, Yong-Ho, Lee, Jong-Min
Format: Article
Language:English
Subjects:
Adult
Algorithms
Asymmetry
Automation
Brain
Brain - diagnostic imaging
Brain - physiology
Brain Cortical Thickness
Brain Mapping
Cerebral hemispheres
Clustering
Connectome - methods
Covariance
Efficiency
Female
Functional Laterality - physiology
Gender
Gender differences
Hemispheric laterality
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Male
Mathematical analysis
Morphology
Networks
Neural circuitry
Neuroimaging
Physiological aspects
Prefrontal Cortex - diagnostic imaging
Prefrontal Cortex - physiology
Rectum
Sex Characteristics
Sex differences
Thickness
Young adults
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Summary:Objective. The current study examined gender-related differences in hemispheric asymmetries of graph metrics, calculated from a cortical thickness-based brain structural covariance network named hemispheric morphological network. Methods. Using the T1-weighted magnetic resonance imaging scans of 285 participants (150 females, 135 males) retrieved from the Human Connectome Project (HCP), hemispheric morphological networks were constructed per participant. In these hemispheric morphologic networks, the degree of similarity between two different brain regions in terms of the distributed patterns of cortical thickness values (the Jensen–Shannon divergence) was defined as weight of network edge that connects two different brain regions. After the calculation and summation of global and local graph metrics (across the network sparsity levels K=0.10‐0.36), asymmetry indexes of these graph metrics were derived. Results. Hemispheric morphological networks satisfied small-worldness and global efficiency for the network sparsity ranges of K=0.10–0.36. Between-group comparisons (female versus male) of asymmetry indexes revealed opposite directionality of asymmetries (leftward versus rightward) for global metrics of normalized clustering coefficient, normalized characteristic path length, and global efficiency (all p
ISSN:2314-6133
2314-6141
DOI:10.1155/2020/3560259