Effects of reward and punishment on learning from errors in smokers

People with a tobacco use disorder exhibit misaligned Bayesian belief updating by falsely attributing non-drug cues as worse predictors of positive outcomes compared to drug cues

Adaptive behaviours depend on dynamically updating internal representations of the world based on the ever-changing environmental contingencies. People with a substance use disorder (pSUD) show maladaptive behaviours with high persistence in drug-taking, despite severe negative consequences. We recently proposed a salience misattribution model for addiction (SMMA; Kalhan et al., 2021), arguing that pSUD have aberrations in their updating processes where drug cues are misattributed as strong predictors of positive outcomes, but weaker predictors of negative outcomes. We also argued that conversely, non-drug cues are misattributed as weak predictors of positive outcomes, but stronger predictors of negative outcomes. We tested these hypotheses using a multi-cue reversal learning task, with reversals in whether drug or non-drug cues are relevant in predicting the outcome (monetary win or loss). We show that people with a tobacco use disorder (pTUD), do form misaligned internal representations. We found that pTUD updated less towards learning the drug cue's relevance in predicting a loss. Further, when neither drug nor non-drug cue predicted a win, pTUD updated more towards the drug cue being relevant predictors of that win. Our Bayesian belief updating model revealed that pTUD had a low estimated likelihood of non-drug cues being predictors of wins, compared to drug cues, which drove the misaligned updating. Overall, several hypotheses of the SMMA were supported, but not all. Our results implicate that strengthening the non-drug cue association with positive outcomes may help restore the misaligned internal representation in pTUD, and offers a quantifiable, computational account of these updating processes.

Functional connectivity during feedback learning in smokers

BACKGROUND

Although it has been traditionally assumed that dysregulation of psychological processes in smokers results from activity within specific brain regions, an emerging view regards such dysregulation as attributable to aberrant communication between distinct brain regions. These processes can be measured during appropriate task paradigms such as the learning from errors task. This study aims to elucidate interactions between brain regions underlying the process of learning from errors, punishment and sensitivity to reward in dependent smokers.

METHODS

Functional MRI data from 23 age-matched dependent smokers (8 females, mean age = 25.48, SD = 4.46) and 23 controls (13 females, mean age = 24.83, SD = 5.99) were analysed during a feedback-based associative learning task. Functional connectivity between the dorsal anterior cingulate cortex, nucleus accumbens and reward/sensorimotor areas was investigated during a feedback learning task.

RESULTS

Behaviourally, smokers exhibited lower error correction rates and were less sensitive to punishment magnitude. Smokers showed increased functional connectivity between dorsal anterior cingulate cortex/nucleus accumbens seed regions and numerous reward-related target regions including the putamen, anterior cingulate and orbitofrontal cortex.

CONCLUSIONS

Reduced learning from errors and widespread aberrant functional connectivity contribute to the emerging functional characterisation of dependent smokers and may bear significant implications when considering the efficacy of smoking interventions.

A salience misattribution model for addictive-like behaviors

Adapting to the changing environment is a key component of optimal decision-making. Internal-models that accurately represent and selectively update from behaviorally relevant/salient stimuli may facilitate adaptive behaviors. Anterior cingulate cortex (ACC) and dopaminergic systems may produce these adaptive internal-models through selective updates from behaviorally relevant stimuli. Dysfunction of ACC and dopaminergic systems could therefore produce misaligned internal-models where updates are disproportionate to the salience of the cues. An aspect of addictive-like behaviors is reduced adaptation and, ACC and dopaminergic systems typically exhibit dysfunction in drug-dependents. We argue that ACC and dopaminergic dysfunction in dependents may produce misaligned internal-models such that drug-related stimuli are misattributed with a higher salience compared to non-drug related stimuli. Hence, drug-related rewarding stimuli generate over-weighted updates to the internal-model, while negative feedback and non-drug related rewarding stimuli generate down-weighted updates. This misaligned internal-model may therefore incorrectly reinforce maladaptive drug-related behaviors. We use the proposed framework to discuss ways behavior may be made more adaptive and how the framework may be supported or falsified experimentally.

Negative affect among daily smokers: A systematic review and meta-analysis

BACKGROUND

Negative Affect (NA), as a personality trait is a tendency towards experiencing a more negative emotion. The body of research suggests that NA encourages smoking relapse and smoking as a reason for NA reduction, though. The likelihood of this connection does not seem to be bright yet. The present study critically reviews researches to synthesize the existing literature to determine the strength of this linkage.

METHODS

Key-word related research was systematically searched in PubMed, PsychINFO, Science Direct and Google Scholar for studies conducted from 1980 to 2019, followed by, the assessment and selection of retrieved studies based on defined inclusion criteria. A random-effects meta-analysis model was used to examine the prospective relationship between NA and smoking. Meta-regression was also used to dig for possible explanations of heterogeneity. Furthermore a multi-moderators model and sub-group analyses examined the moderating factors.

RESULTS

Forty effect-sizes comprising 12 cross-sectional studies, 28 longitudinal studies and 24,913 participants were included in the meta-analysis. The forest plot of the pooled correlation effect size in the random model indicates a significant effect size of the relationship between NA and smoking (r = 0.11; 95%CI 0.071-0.15, P = 0.001) in the meta-analysis with high heterogeneity (Q = 473.916; df=39; P = 0.001; I²=91.77%). Also, the pooled effect size was obtained as 0.143 (95%CI 0.071-0.214) for light-to-moderate and 0.112 (95%CI 0.057-0.166) for moderate-to-heavy smokers, with the effect size ranging from 0.061 to 0.195 which was significant among all subtypes, though this trend seem higher among adolescents, males, and longitudinal studies than in adults, females, and cross-sectional studies.

LIMITATIONS

The review was limited to English articles, and the heterogeneity of the studies were high.

CONCLUSION

These results support the notion that NA was positively and weakly linked to smoking and this linkage is stronger in light-to-moderate smokers, males, and adolescents. Theoretical and clinical implications are discussed with the aim of extending future directions on NA and smoking.

Impaired learning from punishment of errors in smokers: Differences in dorsolateral prefrontal cortex and sensorimotor cortex blood-oxygen-level dependent responses

Cigarette smokers have shown hypersensitivity to reward and hyposensitivity to punishment, along with impairments in learning from errors. The underlying neural mechanism for this failure to adapt performance following an error, particularly when receiving negative feedback, are unclear. Smokers were hypothesized to have poorer error-learning following monetary punishment, associated with hypoactivation in the insula, dorsal anterior cingulate, and hippocampal cortical regions. Twenty-three smokers (8 females, mean age = 25.48, SD = 4.46) and twenty-three healthy controls (13 females, mean age = 24.83, SD = 5.99) were administered an associative learning task, providing monetary reward and punishment for recall performance, during fMRI data collection. Compared with controls, smokers had a lower error-correction rate and were less sensitive to punishment magnitude. Hyperactivity during recall was independent of future error correction, but smokers' successful re-encoding appeared related to higher dorsolateral prefrontal cortex activity while controls had equivalent activation for corrected and repeated errors. While controls showed higher deactivation of the sensorimotor cortex during high punishment, smokers showed higher deactivation during low punishment. The present results support smokers having poorer learning from errors and decreased attentional control associated with hyperactivity in the dorsolateral prefrontal cortex. Additionally, smokers exhibited decreased punishment sensitivity that appeared to limit their ability to adapt learning in the face of repeated negative feedback.

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Smokers show impaired learning from punished errors.

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Controls are more sensitive to differences in punishment magnitude than smokers.

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Smokers show dorsolateral prefrontal cortex hyperactivity during recall.

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Smokers rely more on dorsolateral prefrontal cortex for correct re-encoding than controls.

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Smokers show aberrant sensorimotor cortex deactivation compared with controls.