No abstract

For years, adult psychological research has benefitted from web-based data collection. There is growing interest in harnessing this approach to facilitate data collection from children and adolescents to address foundational questions about cognitive development. To date, however, few studies have directly tested whether findings from in-lab developmental psychology tasks can be replicated online, particularly in the domain of value-based learning and decision-making. To address this question, we set up a pipeline for online data collection with children, adolescents, and adults, and conducted a replication of Decker et al. (2016). The original in-lab study employed a sequential decision-making paradigm to examine shifts in value-learning strategies from childhood to adulthood. Here, we used the same paradigm in a sample of 151 children (N = 50; ages 8 - 12 years), adolescents (N = 50; ages 13 - 17 years), and adults (N = 51; ages 18 - 25 years) and replicated the main finding that the use of a “model-based” learning strategy increases with age. In addition, we adapted a new index of abstract reasoning (MaRs-IB; Chierchia et al. 2019) for use online, and replicated a key result from Potter et al. (2017), which found that abstract reasoning ability mediated the relation between age and model-based learning. Our re-analyses of two previous in-lab datasets alongside our analysis of our online dataset revealed few qualitative differences across task administrations. These findings suggest that with appropriate precautions, researchers can effectively examine developmental differences in learning computations through unmoderated, online experiments.

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 realworld 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.

Beliefs about the controllability of positive or negative events in the environment can shape learning throughout the lifespan. Previous research has shown that adults’ learning is modulated by beliefs about the causal structure of the environment such that they update their value estimates to a lesser extent when the outcomes can be attributed to hidden causes. This study examined whether external causes similarly influenced outcome attributions and learning across development. Ninety participants, ages 7 to 25 years, completed a reinforcement learning task in which they chose between two options with fixed reward probabilities. Choices were made in three distinct environments in which different hidden agents occasionally intervened to generate positive, negative, or random outcomes. Participants’ beliefs about hidden-agent intervention aligned with the true probabilities of the positive, negative, or random outcome manipulation in each of the three environments. Computational modeling of the learning data revealed that while the choices made by both adults (ages 18–25) and adolescents (ages 13–17) were best fit by Bayesian reinforcement learning models that incorporate beliefs about hidden-agent intervention, those of children (ages 7–12) were best fit by a one learning rate model that updates value estimates based on choice outcomes alone. Together, these results suggest that while children demonstrate explicit awareness of the causal structure of the task environment, they do not implicitly use beliefs about the causal structure of the environment to guide reinforcement learning in the same manner as adolescents and adults.

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 links 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.