Adolescent Dopamine Neurons Represent Reward Differently during Action and State Guided Learning

Adolescents rats engage the orbitofrontal-striatal pathway differently than adults during impulsive actions

Adolescence is characterized by increased impulsive and risk-taking behaviors. To better understand the neural networks that subserves impulsivity in adolescents, we used a reward-guided behavioral model that quantifies age differences in impulsive actions in adult and adolescent rats of both sexes. Using chemogenetics, we identified orbitofrontal cortex (OFC) projections to the dorsomedial striatum (DMS) as a critical pathway for age-related execution of impulsive actions. Simultaneous recording of single units and local field potentials in the OFC and DMS during task performance revealed an overall muted response in adolescents during impulsive actions as well as age-specific differences in theta power and OFC-DMS functional connectivity. Collectively, these data reveal that the OFC-DMS pathway is critical for age-differences in reward-guided impulsive actions and provide a network mechanism to enhance our understanding of how adolescent and adult brains coordinate behavioral inhibition.

Propensity for risky choices despite lower cue reactivity in adolescent rats

Adolescence is a time of heightened risk-taking across species. Salient audiovisual cues associated with rewards are a common feature of gambling environments and have been connected to increased risky decision-making. We have previously shown that, in adult male rats, sign tracking - a behavioral measure of cue reactivity - predicts an individual's propensity for suboptimal risky choices in a rodent gambling task (rGT) with win-paired cues. However, adolescents perform less sign tracking than adult animals, suggesting that they are less cue-reactive than adults in some circumstances. Therefore, we investigated the performance of adolescent male rats on the rGT with win cues and examined its relationship with their sign-tracking behavior. We found that adolescents make more risky choices and fewer optimal choices on the rGT compared with adults, evidence of the validity of the rGT as a model of adolescent gambling behavior. We also confirmed that adolescents perform less sign tracking than adults, and we found that, unlike in adults, adolescents' sign tracking was unrelated to their risk-taking in the rGT. This implies that adolescent risk-taking is less likely than that of adults to be driven by reward-related cues. Finally, we found that adults trained on the rGT as adolescents retained an adolescent-like propensity toward risky choices, suggesting that early exposure to a gambling environment may have a long-lasting impact on risk-taking behavior.

Sensitivity and specificity in affective and social learning in adolescence

Adolescence is a period of heightened affective and social sensitivity. In this review we address how this increased sensitivity influences associative learning. Based on recent evidence from human and rodent studies, as well as advances in computational biology, we suggest that, compared to other age groups, adolescents show features of heightened Pavlovian learning but tend to perform worse than adults at instrumental learning. Because Pavlovian learning does not involve decision-making, whereas instrumental learning does, we propose that these developmental differences might be due to heightened sensitivity to rewards and threats in adolescence, coupled with a lower specificity of responding. We discuss the implications of these findings for adolescent mental health and education.

How a token-based game may elicit the reward prediction error and increase engagement of students in elementary school. A pilot study

Student engagement is essential to academic success and student-wellbeing. In the past, fostering engagement though extrinsic rewards has often been found to be of limited effectiveness over the long term. However, extrinsic rewards are important for improving engagement with non-intrinsically rewarding activities. Thus, in the present study a mechanism that is meant to prolong the effects of extrinsic rewards was investigated: the reward prediction error. This error occurs when rewards are awarded contrary to the awardee’s expectations. In a quasi-experiment, 39 elementary school students participated in a classroom-based game, which was supposed to motivate them to solve math exercises. It combined reinforcement with elements of luck, which were supposed to elicit the reward prediction error. After 2 weeks, the intervention group had completed significantly more math exercises compared to a pretest and, importantly, also more correctly solved exercises than a control group. This suggests that game-based reinforcement that elicits the reward prediction error might help to increase student engagement over the medium term. It furthermore highlights the importance of applying gamification elements not only digitally but also in analog settings.

The role of dopamine and endocannabinoid systems in prefrontal cortex development: Adolescence as a critical period

The prefrontal cortex plays a central role in the control of complex cognitive processes including action control and decision making. It also shows a specific pattern of delayed maturation related to unique behavioral changes during adolescence and allows the development of adult cognitive processes. The adolescent brain is extremely plastic and critically vulnerable to external insults. Related to this vulnerability, adolescence is also associated with the emergence of numerous neuropsychiatric disorders involving alterations of prefrontal functions. Within prefrontal microcircuits, the dopamine and the endocannabinoid systems have widespread effects on adolescent-specific ontogenetic processes. In this review, we highlight recent advances in our understanding of the maturation of the dopamine system and the endocannabinoid system in the prefrontal cortex during adolescence. We discuss how they interact with GABA and glutamate neurons to modulate prefrontal circuits and how they can be altered by different environmental events leading to long-term neurobiological and behavioral changes at adulthood. Finally, we aim to identify several future research directions to help highlight gaps in our current knowledge on the maturation of these microcircuits.

Adolescent reinforcement-learning trajectories predict cocaine-taking behaviors in adult male and female rats

The anatomical, structural, and functional adaptations that occur in the brain during adolescence are thought to facilitate improvements in decision-making functions that are known to occur during this stage of development. The mechanisms that underlie these neural adaptations are not known, but deviations in developmental trajectories have been proposed to contribute to the emergence of mental illness, including addiction. Direct evidence supporting this hypothesis, however, has been limited. Here, we used a recently developed reversal-learning protocol to investigate the predictive relationship between adolescent decision-making trajectories and cocaine-taking behaviors in adulthood. Decision-making functions in the reversal-learning task were assessed throughout adolescence and into adulthood in male and female Long-Evans rats. Trial-by-trial choice data was fitted with a reinforcement-learning model to quantify the degree to which choice behavior of individual rats was influenced by rewarded (e.g., ∆₊ parameter) and unrewarded (e.g., ∆₀ parameter) outcomes. We report that reversal-learning performance improved during adolescence and that this was due to an increase in value updating for rewarded outcomes (e.g., ∆₊ parameter). Furthermore, the rate of change in the ∆₊ parameter predicted individual differences in the ∆₊ parameter and, notably, cocaine-taking behaviors in adulthood: Rats that had a shallower adolescent trajectory were found to have a lower ∆₊ parameter and greater cocaine self-administration in adulthood. These data indicate that adolescent development plays a critical role in drug use susceptibility. Future studies aimed at understanding the neurobiological mechanisms that underlie these age-related changes in decision-making could provide new insights into the biobehavioral mechanisms mediating addiction susceptibility.

From Biological Synapses to “Intelligent” Robots

This selective review explores biologically inspired learning as a model for intelligent robot control and sensing technology on the basis of specific examples. Hebbian synaptic learning is discussed as a functionally relevant model for machine learning and intelligence, as explained on the basis of examples from the highly plastic biological neural networks of invertebrates and vertebrates. Its potential for adaptive learning and control without supervision, the generation of functional complexity, and control architectures based on self-organization is brought forward. Learning without prior knowledge based on excitatory and inhibitory neural mechanisms accounts for the process through which survival-relevant or task-relevant representations are either reinforced or suppressed. The basic mechanisms of unsupervised biological learning drive synaptic plasticity and adaptation for behavioral success in living brains with different levels of complexity. The insights collected here point toward the Hebbian model as a choice solution for “intelligent” robotics and sensor systems.