4.1 Article

Neural mechanisms of high-risk decisions-to-drink in alcohol-dependent women

Journal

ADDICTION BIOLOGY
Volume 20, Issue 2, Pages 390-406

Publisher

WILEY
DOI: 10.1111/adb.12121

Keywords

Alcohol dependence; central executive network; default-mode network; reward; risk; salience network

Funding

  1. NIH [AA017638]
  2. Indiana METACyt Initiative of Indiana University

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A hallmark of alcohol dependence (AD) is continually drinking despite the risk of negative consequences. Currently, it is not known if the pattern of disordered activation in AD is more compatible with an over-sensitive reward system, a deficit in control systems or a combination of both to produce the high risk-taking behavior observed in alcohol dependents (ADs). Here, alcohol cues were used in an ecological decisions-to-drink task that involved high- and low-risk scenarios where the chance of serious negative imagined consequences was varied. Non-alcohol cues were included as control stimuli. Functional magnetic resonance imaging (fMRI) was used to measure blood oxygen level-dependent (BOLD) signal change in 15 alcohol-dependent and 16 control women. This design allowed us to address two major questions concerning AD: first, is there a specific pattern of disordered activation that drives the heightened endorsement of high-risk decisions-to-drink in ADs? And, second, is that pattern specific to decisions-to-drink or does it generalize to other appetitive and/or neutral cues? The results showed that, during high-risk decisions-to-drink, alcohol-dependent women activated reward circuits, cognitive control circuits and regions of the default-mode network (DMN), while control women deactivated approach circuits and showed enhanced activation in regions of the DMN. Group differences were found only for decisions-to-drink, suggesting that they are specific to alcohol cues. Simultaneous activation of reward networks, cognitive control networks and the DMN in alcohol-dependent women suggests that over-endorsement of high-risk drinking decisions by alcohol-dependent women may be due to a problem with switching between different neural networks.

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