The effects of quercetin on nicotine-induced reward effects in mice

Objectives Tobacco smoking remains the primary cause of preventable mortality and morbidity in the world. The complexity of the nicotine dependency process included the withdrawal effect that triggers recurrence being the main problem. Quercetin, known as an antioxidant, binds free radicals and modulates endogenous antioxidants through Nrf2 activations is expected as a potential agent to reduce the risk of nicotine dependence. This research aims to evaluate quercetin’s effects on reducing the risk of nicotine addiction. Methods Conditioned Place Preference (CPP) with a biased design was used to evaluate nicotine’s reward effects in male Balb/C mice. Preconditioning test was performed on day 1; conditioning test was done twice daily on day 2–4 by administering quercetin (i.p.) 50 mg/kg along with nicotine (s.c.) 0.5 mg/kg or Cigarette Smoke Extract (CSE) (s.c.) contained nicotine 0.5 mg/kg; and postconditioning test was performed on day 5 continue with extinction test on day 6, 8, 10, 12, and reinstatement test on day 13. The duration spent in each compartment was recorded and analyzed. Results Nicotine 0.5 mg/kg and CSE 0.5 mg/kg significantly induced reward effects (p<0.05). There was no decrease of reward effect during the extinction-reinstatement stage of the postconditioning phase (p>0.05), while quercetin 50 mg/kg both induced along with nicotine or CSE was able to inhibit the reward effect of nicotine (p>0.05). Conclusions Quercetin reduced the risk of nicotine dependence and has a potential effect to use as a therapy for nicotine dependence, especially as a preventive agent.

The cognitive effects of a promised bonus do not depend on dopamine synthesis capacity

Reward motivation is known to enhance cognitive control. However, detrimental effects have also been observed, which have been attributed to overdosing of already high baseline dopamine levels by further dopamine increases elicited by reward cues. Aarts et al. (2014) indeed demonstrated, in 14 individuals, that reward effects depended on striatal dopamine synthesis capacity, measured with [18F]FMT-PET: promised reward improved Stroop control in low-dopamine individuals, while impairing it in high-dopamine individuals. Here, we aimed to assess this same effect in 44 new participants, who had previously undergone an [18F]DOPA-PET scan to quantify dopamine synthesis capacity. This sample performed the exact same rewarded Stroop paradigm as in the prior study. However, we did not find any correlation between reward effects on cognitive control and striatal dopamine synthesis capacity. Critical differences between the radiotracers [18F]DOPA and [18F]FMT are discussed, as the discrepancy between the current and our previous findings might reflect the use of the potentially less sensitive [18F]DOPA radiotracer in the current study.

The cognitive effects of a promised bonus do not depend on dopamine synthesis capacity

ABSTRACTReward motivation is known to enhance cognitive control. However, detrimental effects have also been observed, which have been attributed to overdosing of already high baseline dopamine levels by further dopamine increases elicited by reward cues. Aarts et al. (2014) indeed demonstrated, in 14 individuals, that reward effects depended on striatal dopamine synthesis capacity, measured with [18F]FMT-PET: promised reward improved Stroop control in low-dopamine individuals, while impairing it in high-dopamine individuals. Here, we aimed to assess this same effect in 44 new participants, who had previously undergone an [18F]DOPA-PET scan to quantify dopamine synthesis capacity. This sample performed the exact same rewarded Stroop paradigm as in the prior study. However, we did not find any correlation between reward effects on cognitive control and striatal dopamine synthesis capacity. The discrepancy between the current and our previous findings might reflect the use of different radiotracers for indexing dopamine synthesis capacity.STATEMENT OF RELEVANCEReward motivation is generally thought to enhance cognitive control, but paradoxical negative effects of rewards on cognitive control have also been observed. A previous PET study demonstrated that reward effects on Stroop control depended on baseline striatal dopamine synthesis capacity, indexed by uptake of the radiotracer [18F]FMT. The sample size is this study was very small for a between-subject correlational design. Replicating the exact same Stroop paradigm within a larger sample is therefore crucial to robustly establish the mechanistic link between incentive motivation and cognitive control and advancing our understanding of who chokes under pressure and why, a topic of great societal relevance today. The present study did not reveal any correlation between reward effects on cognitive control and striatal dopamine synthesis capacity, indexed with [18F]FDOPA-PET. Future studies might consider putative differential sensitivity of the radiotracer [18F]FMT and [18F]FDOPA, while also addressing other indices of dopamine transmission.

Influence of Expected Reward on Temporal Order Judgment

Perceptual decision-making has been shown to be influenced by reward expected from alternative options or actions, but the underlying neural mechanisms are currently unknown. More specifically, it is debated whether reward effects are mediated through changes in sensory processing, later stages of decision-making, or both. To address this question, we conducted two experiments in which human participants made saccades to what they perceived to be either the first or second of two visually identical but asynchronously presented targets while we manipulated expected reward from correct and incorrect responses on each trial. By comparing reward-induced bias in target selection (i.e., reward bias) during the two experiments, we determined whether reward caused changes in sensory or decision-making processes. We found similar reward biases in the two experiments indicating that reward information mainly influenced later stages of decision-making. Moreover, the observed reward biases were independent of the individual's sensitivity to sensory signals. This suggests that reward effects were determined heuristically via modulation of decision-making processes instead of sensory processing. To further explain our findings and uncover plausible neural mechanisms, we simulated our experiments with a cortical network model and tested alternative mechanisms for how reward could exert its influence. We found that our experimental observations are more compatible with reward-dependent input to the output layer of the decision circuit. Together, our results suggest that, during a temporal judgment task, reward exerts its influence via changing later stages of decision-making (i.e., response bias) rather than early sensory processing (i.e., perceptual bias).

Influence of expected reward on perceptual decision making

Perceptual decision making is influenced by reward expected from alternative options or actions, but the underlying neural mechanisms are currently unknown. More specifically, it is debated whether reward effects are mediated through changes in sensory processing and/or later stages of decision making. To address this question, we conducted two experiments in which human subjects made saccades to what they perceived to be the first or second of two visually identical but asynchronously presented targets, while we manipulated expected reward from correct and incorrect responses on each trial. We found that unequal reward caused similar shifts in target selection (reward bias) between the two experiments. Moreover, observed reward biases were independent of the individual’s sensitivity to sensory signals. These findings suggest that the observed reward effects were determined heuristically via modulation of decision-making processes instead of sensory processing and thus, are more compatible with response bias rather than perceptual bias. To further explain our findings and uncover plausible neural mechanisms, we simulated our experiments with a cortical network model and tested alternative mechanisms for how reward could exert its influence. We found that our observations are more compatible with reward-dependent input to the output layer of the decision circuit. Together, our results suggest that during a temporal judgment task, the influence of reward information on perceptual choice is more compatible with changing later stages of decision making rather than early sensory processing.

Predictiveness and Reward Effects on Attention can be Explained by a Single Mechanism

In order to learn efficiently, organisms must learn how to distribute their attention to the available cues. Traditionally, most experiments on attention learning have involved discrete outcomes (e.g. no food vs. one food pellet, or category A vs. category B). A basic finding is that cues receive attention in proportion to how well they predict such outcomes. However, more recent research has shown an apparently independent effect of outcome value on attention (Le Pelley, Mitchell, & Johnson, 2013), in which cues associated with large rewards receive more attention than those associated with small rewards. It has been suggested that a separate derived attention mechanism - in which attention is based directly on association strength - is necessary to explain this result (Le Pelley, Mitchell, Beesley, George, & Wills, 2016). As our primary experimental contribution, we use modified versions of this design to replicate the value effect and show that it can be reversed by manipulating the rewards given for incorrect choices. Our simulations show that CompAct - a model in which cues compete for attention on the basis of their relative predictiveness - can account for both of our empirical results. The derived attention theory, in contrast, incorrectly predicts that cues associated with large rewards will always receive more attention. We conclude that we do not need separate mechanisms to account for predictiveness effects and value effects on attention.