Revisiting the Neural Architecture of Adolescent Decision-Making: Univariate and Multivariate Evidence for System-Based Models

Abstract

System-based theories are a popular approach to explaining the psychology of human decision making. Such theories posit that decision-making is governed by interactions between different psychological processes that arbitrate amongst each other for control over behavior. To date, system-based theories have received inconsistent support at the neural level, leading some to question their veracity. Here we examine the possibility that prior attempts to evaluate system-based theories have been limited by their reliance on predicting brain activity from behavior, and seek to advance evaluations of system-based models through modeling approaches that predict behavior from brain activity. Using within-subject decision-level modeling of fMRI data from a risk-taking task in a sample of over 2000 decisions across 51 adolescents—a population in which decision-making processes are particularly dynamic and consequential—we find support for system-based theories of decision-making. In particular, neural activity in lateral prefrontal cortex and a multivariate pattern of cognitive control both predicted a reduced likelihood of making a risky decision, whereas increased activity in the ventral striatum—a region typically associated with valuation processes—predicted a greater likelihood of engaging in risk-taking. These results comprise the first formalized within-subjects neuroimaging test of system-based theories, garnering support for the notion that competing systems drive decision behaviors.Significance StatementDecision making is central to adaptive behavior. While dominant psychological theories of decision-making behavior have found empirical support, their neuroscientific implementations have received inconsistent support. This may in part be due to statistical approaches employed by prior neuroimaging studies of system-based theories. Here we use brain modeling—an approach that predicts behavior from brain activity—of univariate and multivariate neural activity metrics to better understand how neural components of psychological systems guide decision behavior. We found broad support for system-based theories such that that neural systems involved in cognitive control predicted a reduced likelihood to make risky decisions, whereas value-based systems predicted greater risk-taking propensity.

Risk‐taking in the human brain: An activation likelihood estimation meta‐analysis of the balloon analog risk task (BART)

“…Contradictory to the neurodevelopmental imbalance models, a meta-study exploring the age difference did not observe risk-taking differences between early adolescents (11-13 years) and children (5-10 years). A recent study further challenged this model, showing that multivariate brain activity metrics of dlPFC can predict adolescent risk decision tendencies (Moreira et al, 2021).…”

“…Contradictory to the neurodevelopmental imbalance models, a meta‐study exploring the age difference did not observe risk‐taking differences between early adolescents (11–13 years) and children (5–10 years). A recent study further challenged this model, showing that multivariate brain activity metrics of dlPFC can predict adolescent risk decision tendencies (Moreira et al, 2021 ). Unlike the neurodevelopment imbalance models, these results demonstrated that adolescent dlPFC did not crucially have fewer effects on risk‐taking behavior than their reward systems.…”