Evidence accumulation and associated error-related brain activity as computationally-informed prospective predictors of substance use in emerging adulthood.

ABSTRACT:

Rationale

Substance use peaks during the developmental period known as emerging adulthood (ages 18-25), but not every individual who uses substances during this period engages in frequent or problematic use. Although individual differences in neurocognition appear to predict use severity, mechanistic neurocognitive risk factors with clear links to both behavior and neural circuitry have yet to be identified. Here, we aim to do so with an approach rooted in computational psychiatry, an emerging field in which formal models are used to identify candidate biobehavioral dimensions that confer risk for psychopathology.

Objectives

We test whether lower efficiency of evidence accumulation (EEA), a computationally characterized individual difference variable that drives performance

SUBMITTER: Weigard AS 

PROVIDER: S-EPMC8452274 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature