Connectome-Based Predictive Modeling of Concurrent and Prospective Substance Use in Adolescence

Area of Science:

• Neuroscience
• Developmental Psychology
• Public Health

Background:

• Adolescent substance use is a major public health concern.
• Understanding its neural basis is crucial for prevention and treatment.
• Existing methods struggle with the multi-faceted nature and developmental changes in substance use.

Purpose of the Study:

• To model adolescent substance use facets (intent, access, family history) using resting-state brain connectivity.
• To examine how these brain-behavior relationships change during adolescence.
• To investigate trait impulsivity as a risk factor.

Main Methods:

• Utilized resting-state functional connectivity data from the ABCD Bids Community Collection (ABCC).
• Trained predictive models for three dimensions of adolescent substance use: intent, access, and family-developmental history.
• Analyzed data at baseline and a 2-year follow-up to assess developmental shifts.

Main Results:

• Predictive accuracy for substance use facets increased significantly from baseline to follow-up.
• Intent to use was most predictable at baseline; access and family history were better predicted at follow-up.
• This indicates a developmental shift in the brain's mapping of substance use vulnerabilities.

Conclusions:

• Neurobiological correlates of substance use are dynamic throughout adolescence.
• Distinct facets of substance use and developmental timing are critical for understanding risk.
• Early individual differences predict later substance use outcomes, emphasizing the need for tailored interventions.