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Optimal integration of positive and negative outcomes during learning varies depending on an environment's reward statistics. The present study investigated the extent to which children, adolescents, and adults (N = 142 8-25 year-olds, 55% female, 42% White, 31% Asian, 17% mixed race, and 8% Black; data collected in 2021) adapt their weighting of better-than-expected and worse-than-expected outcomes when learning from reinforcement. Participants made choices across two contexts: one in which weighting positive outcomes more heavily than negative outcomes led to better performance, and one in which the reverse was true. Reinforcement learning modeling revealed that across age, participants shifted their valence biases in accordance with environmental structure. Exploratory analyses revealed strengthening of context-dependent flexibility with increasing age.

Across development, people tend to demonstrate a preference for contexts in which they have the opportunity to make choices. However, it is not clear how children, adolescents, and adults learn to calibrate this preference based on the costs and benefits of agentic choice. Here, in both a primary, in-person, reinforcement-learning experiment (N = 92; age range = 10–25 years) and a preregistered online replication study (N = 150; age range = 8–25 years), we found that participants overvalued agentic choice but also calibrated their agency decisions to the reward structure of the environment, increasingly selecting agentic choice when choice had greater instrumental value. Regression analyses and computational modeling of participant choices revealed that participants' bias toward agentic choice—reflecting its intrinsic value—remained consistent across age, whereas sensitivity to the instrumental value of agentic choice increased from childhood to early adulthood. [ABSTRACT FROM AUTHOR]

Intervening on causal systems can illuminate their underlying structures. Past work has shown that, relative to adults, young children often make intervention decisions that appear to confirm a single hypothesis rather than those that optimally discriminate alternative hypotheses. Here, we investigated how the ability to make informative causal interventions changes across development. Ninety participants between the ages of 7 and 25 completed 40 different puzzles in which they had to intervene on various causal systems to determine their underlying structures. Each puzzle comprised a three- or four-node computer chip with hidden wires. On each trial, participants viewed two possible arrangements of the chip's hidden wires and had to select a single node to activate. After observing the outcome of their intervention, participants selected a wire configuration and rated their confidence in their selection. We characterized participant choices with a Bayesian measurement model that indexed the extent to which participants selected nodes that would best disambiguate the two possible causal structures versus those that had high causal centrality in one of the two causal hypotheses but did not necessarily discriminate between them. Our model estimates revealed that the use of a discriminatory strategy increased through early adolescence. Further, developmental improvements in intervention strategy were related to changes in the ability to accurately judge the strength of evidence that interventions revealed, as indexed by participants' confidence in their selections. Our results suggest that improvements in causal information-seeking extend into adolescence and may be driven by metacognitive sensitivity to the efficacy of previous interventions in discriminating competing ideas.

Across the lifespan, individuals frequently choose between exploiting known rewarding options or exploring unknown alternatives. A large body of work has suggested that children may explore more than adults. However, because novelty and reward uncertainty are often correlated, it is unclear how they differentially influence decision-making across development. Here, children, adolescents, and adults (ages 8-27 years, N = 122) completed an adapted version of a recently developed value-guided decision-making task that decouples novelty and uncertainty. In line with prior studies, we found that exploration decreased with increasing age. Critically, participants of all ages demonstrated a similar bias to select choice options with greater novelty, whereas aversion to reward uncertainty increased into adulthood. Computational modeling of participant choices revealed that whereas adolescents and adults demonstrated attenuated uncertainty aversion for more novel choice options, children's choices were not influenced by reward uncertainty. [ABSTRACT FROM AUTHOR]

Optimal integration of positive and negative outcomes during learning varies depending on an environment's reward statistics. The present study investigated the extent to which children, adolescents, and adults (N = 142 8–25 year‐olds, 55% female, 42% White, 31% Asian, 17% mixed race, and 8% Black; data collected in 2021) adapt their weighting of better‐than‐expected and worse‐than‐expected outcomes when learning from reinforcement. Participants made choices across two contexts: one in which weighting positive outcomes more heavily than negative outcomes led to better performance, and one in which the reverse was true. Reinforcement learning modeling revealed that across age, participants shifted their valence biases in accordance with environmental structure. Exploratory analyses revealed strengthening of context‐dependent flexibility with increasing age. [ABSTRACT FROM AUTHOR]

Prioritizing memory for valuable information can promote adaptive behavior across the lifespan, but it is unclear how the neurocognitive mechanisms that enable the selective acquisition of useful knowledge develop. Here, using a novel task coupled with functional magnetic resonance imaging, we examined how children, adolescents, and adults (N = 90) learn from experience what information is likely to be rewarding, and modulate encoding and retrieval processes accordingly. We found that the ability to use learned value signals to selectively enhance memory for useful information strengthened throughout childhood and into adolescence. Encoding and retrieval of high-vs. low-value information was associated with increased activation in striatal and prefrontal regions implicated in value processing and cognitive control. Age-related increases in value-based lateral prefrontal cortex modulation mediated the relation between age and memory selectivity. Our findings demonstrate that developmental increases in the strategic engagement of the prefrontal cortex support the emergence of adaptive memory. [ABSTRACT FROM AUTHOR]

Prioritizing memory for the information most likely to be useful in the future is critical to learning effectively in our complex world. Previous work has revealed that the ability to strategically encode high-value information may improve gradually over development, as the systems supporting cognitive control processes mature. However, studies of value-directed memory have relied on explicit cues that signal the importance of information, which are rarely present in real-world contexts. Here, we examined whether individuals across age groups could learn the relative frequency of items in their environment and prioritize memory for information associated with higher frequency items, which would ultimately enable them to earn more reward. We found that from childhood to early adulthood, individuals gained the ability to dynamically adjust memory based on the statistics of the environment (Experiment 1). In the absence of any relation between item frequency and the reward that could be earned for encoding related information, the increased exposure to higher frequency items did not facilitate associative memory (Experiment 2). Taken together, results from our two experiments suggest that the use of past experience to prioritize memory for high-value information strengthens with increasing age and is supported by the developing ability to derive explicit knowledge of the structure of the environment from experience. [ABSTRACT FROM AUTHOR]

Intervening on causal systems can illuminate their underlying structures. Past work has shown that, relative to adults, young children often make intervention decisions that appear to confirm a single hypothesis rather than those that optimally discriminate alternative hypotheses. Here, we investigated how the ability to make informative causal interventions changes across development. Ninety participants between the ages of 7 and 25 completed 40 different puzzles in which they had to intervene on various causal systems to determine their underlying structures. Each puzzle comprised a three‐ or four‐node computer chip with hidden wires. On each trial, participants viewed two possible arrangements of the chip's hidden wires and had to select a single node to activate. After observing the outcome of their intervention, participants selected a wire configuration and rated their confidence in their selection. We characterized participant choices with a Bayesian measurement model that indexed the extent to which participants selected nodes that would best disambiguate the two possible causal structures versus those that had high causal centrality in one of the two causal hypotheses but did not necessarily discriminate between them. Our model estimates revealed that the use of a discriminatory strategy increased through early adolescence. Further, developmental improvements in intervention strategy were related to changes in the ability to accurately judge the strength of evidence that interventions revealed, as indexed by participants' confidence in their selections. Our results suggest that improvements in causal information‐seeking extend into adolescence and may be driven by metacognitive sensitivity to the efficacy of previous interventions in discriminating competing ideas. [ABSTRACT FROM AUTHOR]

Both salient visual events and scene-based memories can influence attention, but it is unclear how they interact in children and adults. In Experiment 1, children (N = 27; ages 7-12) were faster to discriminate targets when they appeared at the same versus different location as they had previously learned or as a salient visual event. In contrast, adults (N = 30; ages 18-31) responded faster only when cued by visual events. While Experiment 2 confirmed that adults (N = 27) can use memories to orient attention, Experiment 3 showed that, even in the absence of visual events, the effects of memories on attention were larger in children (N = 27) versus adults (N = 28). These findings suggest that memories may be a robust source of influence on children's attention. [ABSTRACT FROM AUTHOR]

Socioeconomic status (SES) has a documented impact on brain and cognitive development. We demonstrate that engaging spatial selective attention mechanisms may counteract this negative influence of impoverished environments on early learning. We previously used a spatial cueing task to compare target object encoding in the context of basic orienting (“facilitation”) versus a spatial selective attention orienting mechanism that engages distractor suppression (“IOR”). This work showed that object encoding in the context of IOR boosted 9-month-old infants’ recognition memory relative to facilitation ( Markant and Amso, 2013 ). Here we asked whether this attention-memory link further interacted with SES in infancy. Results indicated that SES was related to memory but not attention orienting efficacy. However, the correlation between SES and memory performance was moderated by the attention mechanism engaged during encoding. SES predicted memory performance when objects were encoded with basic orienting processes, with infants from low-SES environments showing poorer memory than those from high-SES environments. However, SES did not predict memory performance among infants who engaged selective attention during encoding. Spatial selective attention engagement mitigated the effects of SES on memory and may offer an effective mechanism for promoting learning among infants at risk for poor cognitive outcomes related to SES. [ABSTRACT FROM AUTHOR]

Television can be a powerful education tool; however, content makers must understand the factors that engage attention and promote learning from screen media. Prior research has suggested that social engagement is critical for learning and that interactivity may enhance the educational quality of children’s media. The present study examined the effects of increasing the social interactivity of television on children’s visual attention and word learning. Three- to 5-year-old (Mage= 4;5,SD= 9 months) children completed a task in which they viewed videos of an actress teaching them the Swahili label for an on-screen image. Each child viewed these video clips in 4 conditions that parametrically manipulated social engagement and interactivity. We then tested whether each child had successfully learned the Swahili labels. Though 5-year-old children were able to learn words in all conditions, we found that there was an optimal level of social engagement that best supported learning for all participants, defined by engaging the child but not distracting from word labeling. Our eye-tracking data indicated that children in this condition spent more time looking at the target image and less time looking at the actress’s face as compared with the most interactive condition. These findings suggest that social interactivity is critical to engaging attention and promoting learning from screen media up until a certain point, after which social stimuli may draw attention away from target images and impair children’s word learning. [ABSTRACT FROM PUBLISHER]

The past decade has seen the emergence of the use of reinforcement learning models to study developmental change in value-based learning. It is unclear, however, whether these computational modeling studies, which have employed a wide variety of tasks and model variants, have reached convergent conclusions. In this review, we examine whether the tuning of model parameters that govern different aspects of learning and decision-making processes vary consistently as a function of age, and what neurocognitive developmental changes may account for differences in these parameter estimates across development. We explore whether patterns of developmental change in these estimates are better described by differences in the extent to which individuals adapt their learning processes to the statistics of different environments, or by more static learning biases that emerge across varied contexts. We focus specifically on learning rates and inverse temperature parameter estimates, and find evidence that from childhood to adulthood, individuals become better at optimally weighting recent outcomes during learning across diverse contexts and less exploratory in their value-based decision-making. We provide recommendations for how these two possibilities — and potential alternative accounts — can be tested more directly to build a cohesive body of research that yields greater insight into the development of core learning processes. [ABSTRACT FROM AUTHOR]

Binz et al. argue that meta-learned models are essential tools for understanding adult cognition. Here, we propose that these models are particularly useful for testing hypotheses about why learning processes change across development. By leveraging their ability to discover optimal algorithms and account for capacity limitations, researchers can use these models to test competing theories of developmental change in learning.