Individual differences in learning from probabilistic reward and punishment predicts smoking status

Influence of reinforcement learning on the inhibitory control of Internet gaming disorder

Reward processing dysfunction and inhibition control deficiency have been observed in Internet gaming disorder (IGD). However, it is still unclear whether the previous reinforcement learning depends on reward/punishment feedback influences on the cognitive inhibitory control of IGD. This study compared the differences between an IGD group and healthy people without game experiences in the probability selection task and the subsequent stop signal task by the method of behavioral experiments, in order to explore whether the reward learning ability is impaired in the IGD group. We also discuss the influence of previous reward learning on subsequent inhibition control. The results showed that (1) during the reward learning phase, the IGD group's accuracy was significantly lower than that of the control group; (2) compared with the control group, the IGD group's reaction times were longer in the transfer phase; (3) for no-go trials of the inhibitory control phase after reward learning, the accuracy of the reward-related stimulation in the IGD group was lower than that of punishment-related or neutral stimulation, but there was no significant difference among the three conditions in the control group. These findings indicated that the reinforcement learning ability of the IGD group was impaired, which further caused the abnormal response to reinforcement stimuli.

Dysfunctional feedback processing in male methamphetamine abusers: Evidence from neurophysiological and computational approaches

Methamphetamine use disorder (MUD) as a major public health risk is associated with dysfunctional neural feedback processing. Although dysfunctional feedback processing in people who are substance dependent has been explored in several behavioral, computational, and electrocortical studies, this mechanism in MUDs requires to be well understood. Furthermore, the current understanding of latent components of their behavior such as learning speed and exploration-exploitation dilemma is still limited. In addition, the association between the latent cognitive components and the related neural mechanisms also needs to be explored. Therefore, in this study, the underlying neurocognitive mechanisms of feedback processing of such impairment, and age/gender-matched healthy controls are evaluated within a probabilistic learning task with rewards and punishments. Mathematical modeling results based on the Q-learning paradigm suggested that MUDs show less sensitivity in distinguishing optimal options. Additionally, it may be worth noting that MUDs exhibited a slight decrease in their ability to learn from negative feedback compared to healthy controls. Also through the lens of underlying neural mechanisms, MUDs showed lower theta power at the medial-frontal areas while responding to negative feedback. However, other EEG measures of reinforcement learning including feedback-related negativity, parietal-P300, and activity flow from the medial frontal to lateral prefrontal regions, remained intact in MUDs. On the other hand, the elimination of the linkage between value sensitivity and medial-frontal theta activity in MUDs was observed. The observed dysfunction could be due to the adverse effects of methamphetamine on the cortico-striatal dopamine circuit, which is reflected in the anterior cingulate cortex activity as the most likely region responsible for efficient behavior adjustment. These findings could help us to pave the way toward tailored therapeutic approaches.

Learning bias predicts fear acquisition under stress but not cognitive flexibility

Individuals differ in their ability to learn from reinforcement and in avoiding punishment, which can be measured by the Probabilistic Selection Task (PST). Recently, some studies have demonstrated that this learning bias is regulated by the dopaminergic system, and that stress can differentially affect the use of positive (i.e., reinforcement) and negative (i.e., avoiding punishment) feedback. The current two studies examined whether performance on the PST can predict measures of goal-directed behaviour as assessed by a cognitive flexibility task (Wisconsin Card Sorting Test) and the acquisition of fear responses, when individuals are exposed to a stressor (Socially Evaluated Cold Pressor Test). A total of 26 and 59 healthy participants completed Experiments I and II, respectively. In those who were best at learning from reinforcement, stress increased the processing (i.e., higher skin conductance responses) of non-threatening stimuli during fear acquisition compared to the non-stressful condition, which was not recapitulated in those who were best at avoiding punishment. Additionally, PST performance did not interact with stress to modulate cognitive flexibility, although stress negatively impaired this domain, consistent with previous findings. Furthermore, independent of stress, both positive and negative learning biases were correlated with cognitive flexibility errors. Our results demonstrate that the PST has predictive value for better understanding the determinants of reinforcement and avoidance learning.

Computational analysis of probabilistic reversal learning deficits in male subjects with alcohol use disorder

BACKGROUND

Alcohol use disorder is characterized by perseverative alcohol use despite negative consequences. This hallmark feature of addiction potentially relates to impairments in behavioral flexibility, which can be measured by probabilistic reversal learning (PRL) paradigms. We here aimed to examine the cognitive mechanisms underlying impaired PRL task performance in patients with alcohol use disorder (AUDP) using computational models of reinforcement learning.

METHODS

Twenty-eight early abstinent AUDP and 27 healthy controls (HC) performed an extensive PRL paradigm. We compared conventional behavioral variables of choices (perseveration; correct responses) between groups. Moreover, we fitted Bayesian computational models to the task data to compare differences in latent cognitive variables including reward and punishment learning and choice consistency between groups.

RESULTS

AUDP and HC did not significantly differ with regard to direct perseveration rates after reversals. However, AUDP made overall less correct responses and specifically showed decreased win-stay behavior compared to HC. Interestingly, AUDP showed premature switching after no or little negative feedback but elevated proneness to stay when accumulation of negative feedback would make switching a more optimal option. Computational modeling revealed that AUDP compared to HC showed enhanced learning from punishment, a tendency to learn less from positive feedback and lower choice consistency.

CONCLUSION

Our data do not support the assumption that AUDP are characterized by increased perseveration behavior. Instead our findings provide evidence that enhanced negative reinforcement and decreased non-drug-related reward learning as well as diminished choice consistency underlie dysfunctional choice behavior in AUDP.

Altered Neural Processing of Reward and Punishment in Women With Methamphetamine Use Disorder

It has been suggested that the altered function of reward and punishment is an important vulnerability factor leading to the development of drug use disorders. Previous studies have identified evidence of neurophysiological dysfunction in the reward process of individuals with substance use disorders. To date, only a few event-related potential (ERP) studies have examined the neural basis of reward and punishment processing in women with methamphetamine (MA) use disorders. The current ERP research aims to investigate the neurophysiological mechanisms of reward and punishment in women with MA use disorder using a monetary incentive delay task. Nineteen women with MA use disorder (MA group) and 20 healthy controls (HC group) were recruited in this study. The behavioral data showed that the reaction time (RT) was faster and the response accuracy (ACC) was higher for the potential reward and punishment conditions compared to neutral conditions. During the monetary incentive anticipation stage, the Cue-P3, and stimulus-preceding negativity (SPN) were larger in the MA group than in the HC group. The SPN under the potential reward condition was larger than that under the neutral condition in the MA group but not in the HC group. During the monetary incentive consummation stage, the feedback-related negativity and feedback P3 (FB-P3) following positive feedback were significantly larger than negative feedback in the potential reward condition for the HC group, but not for the MA group. However, the FB-P3 following negative feedback was significantly larger than positive feedback in the potential punishment condition for the MA group, but not the HC group. The results suggest that women with MUD have stronger expectations of generic reward and stronger response of generic harm avoidance, which could be targeted in designing interventions for women with MA use disorder.