Bayesian neural adjustment of inhibitory control predicts emergence of problem stimulant use
Journal
Brain
Journal Volume
138
Journal Issue
11
Pages
3413-3426
Date Issued
2015
Author(s)
Abstract
Bayesian ideal observer models quantify individuals' context- and experience-dependent beliefs and expectations about their environment, which provides a powerful approach (i) to link basic behavioural mechanisms to neural processing; and (ii) to generate clinical predictors for patient populations. Here, we focus on (ii) and determine whether individual differences in the neural representation of the need to stop in an inhibitory task can predict the development of problem use (i.e. abuse or dependence) in individuals experimenting with stimulants. One hundred and fifty-seven non-dependent occasional stimulant users, aged 18-24, completed a stop-signal task while undergoing functional magnetic resonance imaging. These individuals were prospectively followed for 3 years and evaluated for stimulant use and abuse/dependence symptoms. At follow-up, 38 occasional stimulant users met criteria for a stimulant use disorder (problem stimulant users), while 50 had discontinued use (desisted stimulant users). We found that those individuals who showed greater neural responses associated with Bayesian prediction errors, i.e. the difference between actual and expected need to stop on a given trial, in right medial prefrontal cortex/anterior cingulate cortex, caudate, anterior insula, and thalamus were more likely to exhibit problem use 3 years later. Importantly, these computationally based neural predictors outperformed clinical measures and non-model based neural variables in predicting clinical status. In conclusion, young adults who show exaggerated brain processing underlying whether to 'stop' or to 'go' are more likely to develop stimulant abuse. Thus, Bayesian cognitive models provide both a computational explanation and potential predictive biomarkers of belief processing deficits in individuals at risk for stimulant addiction. © 2015 The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Subjects
addiction; Bayesian model; inhibitory control; stimulant
SDGs
Other Subjects
biological marker; central stimulant agent; central stimulant agent; accuracy; adult; anterior cingulate; anterior insula; Article; Bayes theorem; behavior; caudate nucleus; correlation analysis; drug abuse; drug dependence; female; follow up; functional magnetic resonance imaging; functional neuroimaging; high risk population; human; human experiment; male; medial prefrontal cortex; nerve cell network; nerve potential; neurobiology; priority journal; probability; prospective study; statistical analysis; symptom; task performance; thalamus; young adult; adolescent; amphetamine dependence; Bayes theorem; brain; brain cortex; cannabis smoking; cingulate gyrus; cocaine dependence; cohort analysis; drug dependence; inhibition (psychology); longitudinal study; nerve cell inhibition; nuclear magnetic resonance imaging; pathophysiology; prefrontal cortex; statistical model; Adolescent; Adult; Amphetamine-Related Disorders; Bayes Theorem; Brain; Caudate Nucleus; Central Nervous System Stimulants; Cerebral Cortex; Cocaine-Related Disorders; Cohort Studies; Female; Functional Neuroimaging; Gyrus Cinguli; Humans; Inhibition (Psychology); Logistic Models; Longitudinal Studies; Magnetic Resonance Imaging; Male; Marijuana Smoking; Neural Inhibition; Prefrontal Cortex; Prospective Studies; Substance-Related Disorders; Thalamus; Young Adult
Type
journal article