Blunted expected reward value signals in binge alcohol drinkers

Serenella Tolomeo (Lead / Corresponding author), Alex Baldacchino, J. Douglas Steele

Research output: Contribution to journalArticlepeer-review

Abstract

Alcohol-related morbidities and mortality are highly prevalent increasing the burden to societies and health systems, with three million deaths globally each year in young adults directly attributable to alcohol. Cue induced alcohol craving has been formulated as a type of aberrant associative learning, modelled using temporal difference theory with expected reward value (ERV) linked to craving. Clinically, whilst harmful use of alcohol is associated with increased time spent obtaining and using alcohol, it is also associated with self-neglect. The latter implies that the motivational aspects of non-alcohol stimuli are blunted. Using an instrumental learning task with non-alcohol related stimuli, here we tested hypotheses that the encoding of cue signals (ERV) predicting reward delivery would be blunted in binge alcohol drinkers in both sexes. We also predicted that for the binge drinking group alone, ratings of problematic alcohol use would correlate with abnormal ERV signals consistent with between groups (i.e. binge drinkers vs controls) abnormalities. Our results support our hypotheses with the ERV (non-alcohol cue) signal blunted in binge drinkers and with the magnitude of the abnormality correlating with ratings of problematic alcohol use. This implies that consistent with hypotheses, the motivational aspects of non-alcohol related stimuli are blunted in binge drinkers. Better understanding of the mechanisms of harmful alcohol use will, in time, facilitate the development of more effective interventions, which should aim to decrease the motivational value of alcohol and increase the motivational value of non-alcohol related stimuli.
Original languageEnglish
JournalJournal of Neuroscience
Publication statusAccepted/In press - 16 Nov 2022

Keywords

  • Amygdala-hippocampal complex
  • binge drinking
  • model-based fMRI
  • prediction error signal
  • orbitofrontal
  • reinforcement learning
  • value

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