Network-based approaches to examining stress in the adolescent brain

被引:24
作者
Ho, Tiffany C. [1 ]
Dennis, Emily L. [2 ]
Thompson, Paul M. [2 ]
Gotlib, Ian H. [1 ]
机构
[1] Stanford Univ, Dept Psychol, 450 Serra Mall,Bldg 420 Jordan Hall, Stanford, CA 94305 USA
[2] Univ Southern Calif, Keck Sch Med, Imaging Genet Ctr, Mary & Mark Stevens Inst Neuroimaging & Informat, Los Angeles, CA USA
来源
NEUROBIOLOGY OF STRESS | 2018年 / 8卷
基金
美国国家卫生研究院;
关键词
Graph theory; Stress; Adolescent; Diffusion tensor imaging; Resting-state functional magnetic resonance imaging; Depression; TEST-RETEST RELIABILITY; RICH-CLUB ORGANIZATION; FUNCTIONAL CONNECTIVITY; CHILDHOOD MALTREATMENT; ANTERIOR CINGULATE; STRUCTURAL CONNECTIVITY; CORTICAL THICKNESS; ANATOMICAL NETWORKS; GENDER-DIFFERENCES; SENSITIVE PERIODS;
D O I
10.1016/j.ynstr.2018.05.002
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Exposure to stress, particularly in periods of rapid brain maturation such as adolescence, can profoundly influence developmental processes that undergird the organization of structural and functional brain networks and that may mediate the association between stressful experiences and maladaptive outcomes. While studies in translational developmental neuroscience often focus on how specific brain regions or targeted connections are altered by stress and psychiatric disease, the emerging field of network science may be especially valuable for elucidating the impact of stress on the intricate connectomics of the adolescent brain. Here we review recent studies that use graph theory and other network science approaches to understand normative adolescent brain development, effects of childhood maltreatment on the brain, and disorders characterized by pathological responses to stress in adolescents. Overall, these studies demonstrate that graph theory can be useful in identifying and quantifying developmental processes related to segregation, integration, and localized hub influence that are affected by stress exposure and that may lead to psychopathology. Finally, we discuss limitations in the current application of graph theory in this area and suggest what we believe are important directions for future work.
引用
收藏
页码:147 / 157
页数:11
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