Reduced Neural Recruitment for Bayesian Adjustment of Inhibitory Control in Methamphetamine Dependence
Journal
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
Journal Volume
1
Journal Issue
5
Pages
448-459
Date Issued
2016
Author(s)
Abstract
BACKGROUND Delineating the processes that contribute to the progression and maintenance of substance dependence is critical to understanding and preventing addiction. Several previous studies have shown inhibitory control deficits in individuals with stimulant use disorder. We used a Bayesian computational approach to examine potential neural deficiencies in the dynamic predictive processing underlying inhibitory function among recently abstinent methamphetamine-dependent individuals (MDIs), a population at high risk of relapse. METHODS Sixty-two MDIs were recruited from a 28-day inpatient treatment program at the San Diego Veterans Affairs Medical Center and compared with 34 healthy comparison subjects. They completed a stop-signal task during functional magnetic resonance imaging. A Bayesian ideal observer model was used to predict individuals’ trial-to-trial probabilistic expectations of inhibitory response, P(stop), to identify group differences specific to Bayesian expectation and prediction error computation. RESULTS Relative to comparison subjects, MDIs were more likely to make stop errors on difficult trials and had attenuated slowing following stop errors. MDIs further exhibited reduced sensitivity as measured by the neural tracking of a Bayesian measure of surprise (unsigned prediction error), which was evident across all trials in the left posterior caudate and orbitofrontal cortex (Brodmann area 11), and selectively on stop error trials in the right thalamus and inferior parietal lobule. CONCLUSIONS MDIs are less sensitive to surprising task events, both across trials and upon making commission errors, which may help explain why these individuals may not engage in switching strategy when the environment changes, leading to adverse consequences. © 2016 Society of Biological Psychiatry
Subjects
Addiction; Bayesian model; fMRI; Inhibitory control; Methamphetamine dependence; Prediction error
SDGs
Other Subjects
methamphetamine; adult; adverse outcome; Article; Bayes theorem; caudate nucleus; controlled study; female; functional magnetic resonance imaging; high risk population; human; inferior parietal lobule; major clinical study; male; methamphetamine dependence; neurophysiological recruitment; orbital cortex; predictive value; priority journal; relapse; task performance; thalamus
Type
journal article