Altered Neural Processing of the Need to Stop in Young Adults at Risk for Stimulant Dependence

作者：Harle Katia M; Shenoy Pradeep; Stewart Jennifer L; Tapert Susan F; Yu Angela J; Paulus Martin P^*

来源：Journal of Neuroscience, 2014, 34(13): 4567-4580.

DOI：10.1523/JNEUROSCI.2297-13.2014

• Bayesian model
• cognitive control
• ideal observer model
• inhibitory control
• stimulants

Identification of neurocognitive predictors of substance dependence is an important step in developing approaches to prevent addiction. Given evidence of inhibitory control deficits in substance abusers (Monterosso et al., 2005; Fu et al., 2008; Lawrence et al., 2009; Tabibnia et al., 2011), we examined neural processing characteristics in human occasional stimulant users (OSU), a population at risk for dependence. A total of 158 nondependent OSU and 47 stimulant-naive control subjects (CS) were recruited and completed a stop signal task while undergoing functional magnetic resonance imaging (fMRI). A Bayesian ideal observer model was used to predict probabilistic expectations of inhibitory demand, P(stop), on a trial-to-trial basis, based on experienced trial history. Compared with CS, OSU showed attenuated neural activation related to P(stop) magnitude in several areas, including left prefrontal cortex and left caudate. OSU also showed reduced neural activation in the dorsal anterior cingulate cortex (dACC) and right insula in response to an unsigned Bayesian prediction error representing the discrepancy between stimulus outcome and the predicted probability of a stop trial. These results indicate that, despite minimal overt behavioral manifestations, OSU use fewer brain processing resources to predict and update the need for response inhibition, processes that are critical for adjusting and optimizing behavioral performance, which may provide a biomarker for the development of substance dependence.

• 出版日期2014-3-26