Interpersonal Support, Functional Brain Architecture, and Internalizing Symptoms during Adolescence
Poster No:
835
Submission Type:
Abstract Submission
Authors:
Sunghyun Hong1, Cleanthis Michael1, Felicia Hardi1, Scott Tillem1, Jeanne Brooks-Gunn2, Vonnie McLoyd1, Colter Mitchell1, Luke Hyde1, Christopher Monk1
Institutions:
1University of Michigan, Ann Arbor, MI, 2Columbia University, New York, NY
First Author:
Co-Author(s):
Introduction:
Interpersonal support is the perceived ability to receive desired support through social connections. Interpersonal support buffers against the negative effects of stress and contributes to overall psychological well-being. While there is preliminary work linking interpersonal support to the functional activation of various brain regions, it is unknown how interpersonal support relates to the overall functional organization of the brain. This study investigated the association between interpersonal support and functional brain organization in adolescence and how these networks are related to internalizing symptoms, which become more prevalent during this developmental period.
Methods:
The study included 173 adolescents from the Future of Families and Child Wellbeing Study, a population-based study. Interpersonal support was measured using the Interpersonal Support Evaluation List, while depressive and anxiety symptoms were assessed using the Center for Epidemiologic Studies Depression Scale and Brief Symptom Inventory 18. We measured functional brain architecture by integrating resting-state and task-based scans (with task effects regressed out), generating 20+ minutes of 'pseudo-rest' fMRI data to enhance metric reliability. Weighted, undirected graphs were constructed to examine three whole-brain level metrics: global efficiency (integration), modularity (segregation), and small-world propensity (segregation-integration balance). Several demographic covariates (e.g., sex, household income, and puberty status) and head motion during scanning were included. Multiple path analyses were conducted. First, we examined the association between youth interpersonal support and network metrics while controlling for covariates. Subsequently, we investigated associations between network metrics and depression, as well as network metrics and anxiety, while controlling for covariates. In an exploratory analysis, a single model included interpersonal support, depression, anxiety, and covariates as predictors of network metrics, considering the influences of current depressive and anxiety symptoms on perceived support. False discovery rate correction was applied, and Full Information Maximum Likelihood was used to handle missing data.
Results:
Higher youth interpersonal support was associated with reduced global efficiency (β=-0.178, padj=0.026) and small-world propensity (β=-0.225, padj=0.009), with no association found for modularity (β=-0.048, padj=0.496). Reduced global efficiency and small-world propensity were linked to decreased levels of anxiety (β=0.202, padj=0.018; β=0.261, padj=0.003). Small-world propensity was also associated with decreased levels of depression (β=0.256, padj=0.003). Additionally, the relationship between interpersonal support and global efficiency (β=-0.168, padj=0.042), as well as small-world propensity (β=-0.186, padj=0.042), remained significant even after adjusting for depression, anxiety, and covariates.
Conclusions:
A higher level of interpersonal support was associated with lower global efficiency and small-world propensity, suggesting less efficient information flow and a less optimal balance between integration and segregation. These topological alterations were, in turn, linked to lower anxiety (for both global efficiency and small-world propensity) and depression (for small-world propensity only). These findings suggest that interpersonal support-linked neural changes may be adaptive for mental health in youth. While our cross-sectional analyses cannot directly address developmental pace, the results suggest that having a higher level of interpersonal support may be associated with a more protracted pace of functional neurodevelopment. We are currently following up with participants at age 22 to assess the longitudinal implications of our findings on changes in social conditions, network metrics, and psychological well-being during their transition to young adulthood.
Emotion, Motivation and Social Neuroscience:
Social Neuroscience Other 1
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 2
Keywords:
Affective Disorders
Anxiety
Development
MRI
PEDIATRIC
Social Interactions
1|2Indicates the priority used for review
Provide references using author date format
Cho, J. W. (2021). Impact of concatenating fMRI data on reliability for functional connectomics. Neuroimage, 226, 117549.
Cohen, S. (1985) Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310-357,
Fair D.A. (2007) A method for using blocked and event-related fMRI data to study “resting state” functional connectivity. NeuroImage. 35 (1) 396-405.
Gong, Q. (2015). Depression, neuroimaging and connectomics: a selective overview. Biological Psychiatry, 77(3), 223-235.
Gunnar, M. R. (2015) Parental buffering of fear and stress neurobiology: Reviewing parallels across rodent, monkey, and human models. Social neuroscience, 10(5), 474–478.
Holz, N. E. (2020) Resilience and the brain: a key role for regulatory circuits linked to social stress and support. Molecular psychiatry, 25(2), 379-396.
Kraus, B. T. (2021). Network variants are similar between task and rest states. Neuroimage, 229, 117743.
Power, J. D. (2010) The development of human functional brain networks. Neuron, 67(5), 735-748.