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. 2017 Jan 15:317:122-131.
doi: 10.1016/j.bbr.2016.09.033. Epub 2016 Sep 15.

Learning and generalization from reward and punishment in opioid addiction

Affiliations

Learning and generalization from reward and punishment in opioid addiction

Catherine E Myers et al. Behav Brain Res. .

Abstract

This study adapts a widely-used acquired equivalence paradigm to investigate how opioid-addicted individuals learn from positive and negative feedback, and how they generalize this learning. The opioid-addicted group consisted of 33 participants with a history of heroin dependency currently in a methadone maintenance program; the control group consisted of 32 healthy participants without a history of drug addiction. All participants performed a novel variant of the acquired equivalence task, where they learned to map some stimuli to correct outcomes in order to obtain reward, and to map other stimuli to correct outcomes in order to avoid punishment; some stimuli were implicitly "equivalent" in the sense of being paired with the same outcome. On the initial training phase, both groups performed similarly on learning to obtain reward, but as memory load grew, the control group outperformed the addicted group on learning to avoid punishment. On a subsequent testing phase, the addicted and control groups performed similarly on retention trials involving previously-trained stimulus-outcome pairs, as well as on generalization trials to assess acquired equivalence. Since prior work with acquired equivalence tasks has associated stimulus-outcome learning with the nigrostriatal dopamine system, and generalization with the hippocampal region, the current results are consistent with basal ganglia dysfunction in the opioid-addicted patients. Further, a selective deficit in learning from punishment could contribute to processes by which addicted individuals continue to pursue drug use even at the cost of negative consequences such as loss of income and the opportunity to engage in other life activities.

Keywords: Acquired equivalence; Generalization; Heroin; Opioid addiction; Punishment learning; Reward learning.

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Figures

Figure 1
Figure 1
The four cartoon characters that served as antecedents and the four food items that served as consequents.
Figure 2
Figure 2
Example screen events on the computer-based task. (A) On each trial, the screen shows one antecedent and two consequents, and asks the subject to guess which food that person prefers. (B) On reward-based trials, correct responses are reinforced with feedback and point gain, while (C) incorrect responses trigger no feedback or points. (D) On punishment-based trials, incorrect responses trigger corrective feedback (“Incorrect – Lose 10 points!”) and point loss, while correct responses trigger no feedback or point loss.
Figure 3
Figure 3
Performance on the training phase in terms of (A) mean trials at each training stage, and (B) mean total errors on reward-based and punishment-based trials, across the three stages. Asterisks indicate significant differences between opioid-addicted and control groups (p<.05 in A, p<.008 in B).
Figure 4
Figure 4
Performance on the testing phase, including (A) retention of old (previously-trained) pairs and (B) generalization to new pairs, plotted separately for reward-based and punishment-based trials.

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