The ICN is thrilled and excited to see the publication of its largest project so far, involving all of its members! Congratulations everyone!! 

Recent evidence indicates that reward value encoding in humans is highly context dependent, leading to suboptimal decisions in some cases, but whether this computational constraint on valuation is a shared feature of human cognition remains unknown. Here we studied the behaviour of n = 561 individuals from 11 countries of markedly different socioeconomic and cultural makeup. Our findings show that context sensitivity was present in all 11 countries. Suboptimal decisions generated by context manipulation were not explained by risk aversion, as estimated through a separate description-based choice task (that is, lotteries) consisting of matched decision offers. Conversely, risk aversion significantly differed across countries. Overall, our findings suggest that context-dependent reward value encoding is a feature of human cognition that remains consistently present across different countries, as opposed to description-based decision-making, which is more permeable to cultural factors.

 The ICN is thrilled to see the publication of one of its projects in Biological Psychiatry https://doi.org/10.1016/j.biopsych.2023.12.005 . Big shoutout to Maelle Gueguen, Hernán Anlló, Darla Bonagura, Stefano Palminteri and Ana Konova!

Background

Drugs like opioids are potent reinforcers thought to co-opt value-based decisions by overshadowing other rewarding outcomes, but how this happens at a neurocomputational level remains elusive. Range adaptation is a canonical process of fine-tuning representations of value based on reward context. Here, we tested whether recent opioid exposure impacts range adaptation in opioid use disorder, potentially explaining why shifting decision making away from drug taking during this vulnerable period is so difficult.

Methods

Participants who had recently (<90 days) used opioids (n = 34) or who had abstained from opioid use for ≥ 90 days (n = 20) and comparison control participants (n = 44) completed a reinforcement learning task designed to induce robust contextual modulation of value. Two models were used to assess the latent process that participants engaged while making their decisions: 1) a Range model that dynamically tracks context and 2) a standard Absolute model that assumes stationary, objective encoding of value.

Results

Control participants and ≥90-days-abstinent participants with opioid use disorder exhibited choice patterns consistent with range-adapted valuation. In contrast, participants with recent opioid use were more prone to learn and encode value on an absolute scale. Computational modeling confirmed the behavior of most control participants and ≥90-days-abstinent participants with opioid use disorder (75%), but a minority in the recent use group (38%), was better fit by the Range model than the Absolute model. Furthermore, the degree to which participants relied on range adaptation correlated with duration of continuous abstinence and subjective craving/withdrawal.

Conclusions

Reduced context adaptation to available rewards could explain difficulty deciding about smaller (typically nondrug) rewards in the aftermath of drug exposure.

 The ICN is immensely proud to present the (soon to be published) work of its members Dr. Maelle Gueguen, Dr. Hernán Anlló, Professor Stefano Palminteri and Professor Anna Konova, at not one but two conferences: RLDM and CPDD!!

 Here they evaluate the decision mechanisms behind relapse rates in OUD. Could this value-ecoding based explanation help solve the riddle? We certainly think so!! This is the first joint project from the ICN, and we couldn't be happier.

 We are most happy to now count Dr. Jian Li and the Learning & Decision Making lab (University of Peking) as a brand new member of the ICN! Looking forward to great work together!

 Dr. Maelle Guegen (PhD) gave a talk on her project "Sensitivity to contextual effects during reinforcement learning in human addiction" at the Society for Neuroeconomics meeting 2021. 

 Finds us at @interculturalCN !!