Poster F24, Tuesday, March 27, 8:00-10:00 am, Exhibit Hall C
Characterizing the neural basis of adolescent cognitive control using connectome-based predictive modeling
Raihyung Lee1, Seyul Kwak1, Dasom Lee1, Jeanyung Chey1; 1Seoul National University
The ability to exert cognitive control is linked to crucial life outcomes such as risk-taking behavior, substance abuse, and mental disorders in adolescence. Understanding the neural basis of adolescent cognitive control is thus critical for investigating the vulnerabilities of this period. Here, using connectome-based predictive modeling, we identified functional brain networks whose strength during a cognitive control task predicted individual differences in performance. We first built the network model relating connectivity strength to task performance as 58 adolescents performed the Multi-Source Interference Task (MSIT), an established cognitive control fMRI paradigm. To determine whether network strength predicts task performance in novel subjects, a leave-one-out cross-validation procedure was applied. We demonstrated that our network model predicted the interference reaction time (RT) of novel individuals from their task-based connectivity. The model also generalized to the resting state, predicting novel individuals’ performance from connectivity observed during rest alone. As a stronger test of generalizability, we showed that our network model could also predict the performance of individuals on the Stroop task, another cognitive control test performed outside the MRI scanner, based on their resting connectivity. To characterize functional anatomy of the network, we summarized connectivity patterns that were primarily predictors of better cognitive control.
Topic Area: EXECUTIVE PROCESSES: Development & aging