According to the results of a new study, craving may alter decision-making processes in addiction. The research study, published in the journal Nature Mental Health, included 132 adult participants who reported engaging in moderate to heavy alcohol or cannabis use. The work was a collaboration between researchers from the Icahn School of Medicine at Mount Sinai and theYale School of Medicine and Yale University.
As part of the study, participants completed a task involving two slot machines, aiming to maximize rewards while the higher-probability “winning” machine (80% vs. 20%) switched unpredictably and was not identified in advance. Moreover, the rewards consisted of either monetary images or substance-related cues, and researchers assessed how craving, mood, and outcomes (wins or losses) influenced decision-making.
The study results revealed that when rewards were monetary, participants quickly learned to select the higher-probability slot machine, repeating choices after wins and switching after losses. However, when rewards were substance-related cues, craving altered this learning process. In addition, computational modeling showed that higher craving accelerated learning in alcohol users but slowed it in cannabis users, suggesting different mechanisms and a potential role of craving in shaping learning and reinforcing addictive behavior.
“There’s something that distinguishes the mechanism of alcohol use vs. cannabis use,” said Dr. Kaustubh R. Kulkarni, the study’s first author and psychiatry resident in the Yale School of Medicine Neuroscience Research Training Program, in his interview with Medical Xpress. “It could be the actual pharmacologic effect of alcohol on the brain, which is pretty different from cannabis, or it could be something else entirely.”
The research team is now conducting follow-up studies using brain scans in order to determine which neural circuits are involved. “We need to understand not just the computational, but the neurocomputational framework of how particular parts of the disorder are implicated,” said Dr. Kulkani. “Then we can use our understanding of current pharmacologic treatments, brain stimulation treatments, or even psychotherapy to tailor those to particularly target the circuits that are implicated.”
The researchers have also noted that their long-term goal is to use computational markers as biomarkers to assess patients and predict treatment outcomes. “My hope is that these gamified behavioral assays will be used to assess patients in the clinic,” said the study’s senior Dr. Xiaosi Gu, professor of psychiatry and director of the Computational Psychiatry Unit at Yale School of Medicine. “Unlike brain imaging, which requires expensive equipment, behavioral tasks can be administered anywhere, even remotely during telemedicine visits.”