Predicting trait sensation seeking using resting-state functional connectivity
Poster No:
1141
Submission Type:
Abstract Submission
Authors:
Sophia Bibb1, Elana Schettini1, David Osher1, Zeynep Saygin1
Institutions:
1Ohio State University, Columbus, OH
First Author:
Co-Author(s):
Introduction:
Past research has revealed that youth who initiate alcohol use before age 15 are significantly more likely to have alcohol use disorder (AUD) in adulthood (Tanaree et al., 2017). Sensation seeking is one personality trait that is related to increased experimentation with alcohol in youth (Cappelli et al., 2019). What is the neural basis of this individual variability? Can sensation seeking be characterized and predicted by individual differences in functional connectivity? This work investigates the relationship between resting state functional connectivity (rsFC) and sensation seeking in pre-adolescents, with the goal of identifying the neural networks that drive future risk for early initiation of alcohol use.
Methods:
6,979 youth between 9 and 11 years of age were enrolled as a part of the Adolescent Behavioral Cognitive Development (ABCD) study (Casey et al., 2018). Participants completed a baseline in-person lab visit, including a ten-minute resting state functional magnetic resonance imaging scan and completion of the parent-report UPPS scale (Whiteside and Lynam, 2001), which contains the sensation seeking subscale. rsFC data were divided into train and test sets and scaled. A support vector regression with elastic net regularization was trained to predict trait sensation seeking using rsFC covariates, controlling for effects of sex and head motion. The trained model was then applied to the held-out rsFC data, and the Pearson's correlation between predicted and actual sensation seeking scores was calculated. Results were compared to null models, wherein sensation seeking scores for each individual were randomly permuted (1,000 permutations); the model was then trained on rsFC and the permuted sensation seeking data, and the model's predicted and actual held-out sensation seeking scores were correlated. The null distribution of the permuted model's Rs was then compared to the actual model's R to determine model significance. We also assessed whether sensation seeking at baseline is related to number of self-reported past-year alcohol sips a participant reported at the 4-year timepoint. A two-way ANOVA was conducted between two groups: 0 sips of alcohol and > 2 sips of alcohol at the 4-year timepoint, with sensation seeking at baseline as the outcome variable.
Results:
The trained model successfully predicted sensation seeking scores using rsFC data (R = 0.111). Permutation testing revealed no null permutations with an R-value greater than the actual observed R (P < .0001). These sensation seeking scores (at baseline) were significantly lower in children who had no sips of alcohol 4 years later vs. children who had more than 2 sips of alcohol 4 years later (F = 21.17, P = 4.28e-06, ω2= 3.01e-03), suggesting that this trait indeed predicts later alcohol use in children of this age range.
Conclusions:
Sensation seeking is a trait that can be effectively characterized by the brain's function at rest. Ongoing work investigates the relationship between resting state connectivity at baseline and initiation of alcohol use at the 4-year timepoint.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Lifespan Development:
Early life, Adolescence, Aging
Modeling and Analysis Methods:
Classification and Predictive Modeling 1
fMRI Connectivity and Network Modeling
Task-Independent and Resting-State Analysis
Keywords:
Addictions
Psychiatric Disorders
1|2Indicates the priority used for review
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Provide references using APA citation style.
Casey, B. J., Cannonier, T., Conley, M. I., Cohen, A. O., Barch, D. M., Heitzeg, M. M., Soules, M. E., Teslovich, T., Dellarco, D. V., Garavan, H., Orr, C. A., Wager, T. D., Banich, M. T., Speer, N. K., Sutherland, M. T., Riedel, M. C., Dick, A. S., Bjork, J. M., Thomas, K. M., … Dale, A. M. (2018). The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites. Developmental Cognitive Neuroscience, 32, 43–54.
Tanaree, A., Assanangkornchai, S., & Kittirattanapaiboon, P. (2017). Pattern and risk of developing alcohol use disorders, illegal substance use and psychiatric disorders after early onset of alcohol use: Results of the Thai National Mental Health Survey 2013. Drug and Alcohol Dependence, 170, 102–111.
Whiteside, S. P., & Lynam, D. R. (2001). The Five Factor Model and impulsivity: Using a structural model of personality to understand impulsivity. Personality and Individual Differences, 30(4), 669–689.