Infants rationally infer the goals of other people's reaches in the absence of first-person experience with reaching actions.

Does knowledge of other people's minds grow from concrete experience to abstract concepts? Cognitive scientists have hypothesized that infants' first-person experience, acting on their own goals, leads them to understand others' actions and goals. Indeed, classic developmental research suggests that before infants reach for objects, they do not see others' reaches as goal-directed. In five experiments (N = 117), we test an alternative hypothesis: Young infants view reaching as undertaken for a purpose but are open-minded about the specific goals that reaching actions are aimed to achieve. We first show that 3-month-old infants, who cannot reach for objects, lack the expectation that observed acts of reaching will be directed to objects rather than to places. Infants at the same age learned rapidly, however, that a specific agent's reaching action was directed either to an object or to a place, after seeing the agent reach for the same object regardless of where it was, or to the same place regardless of what was there. In a further experiment, 3-month-old infants did not demonstrate such inferences when they observed an actor engaging in passive movements. Thus, before infants have learned to reach and manipulate objects themselves, they infer that reaching actions are goal-directed, and they are open to learning that the goal of an action is either an object or a place. RESEARCH HIGHLIGHTS: In the present experiments, 3-month-old prereaching infants learned to attribute either object goals or place goals to other people's reaching actions. Prereaching infants view agents' actions as goal-directed, but do not expect these acts to be directed to specific objects, rather than to specific places. Prereaching infants are open-minded about the specific goal states that reaching actions aim to achieve.

Origins of the concepts cause, cost, and goal in prereaching infants.

We investigated the origins and interrelations of causal knowledge and knowledge of agency in 3-month-old infants, who cannot yet effect changes in the world by reaching for, grasping, and picking up objects. Across 5 experiments, n = 152 prereaching infants viewed object-directed reaches that varied in efficiency (following the shortest physically possible path vs. a longer path), goal (lifting an object vs. causing a change in its state), and causal structure (action on contact vs. action at a distance and after a delay). Prereaching infants showed no strong looking preference between a person's efficient and inefficient reaches when the person grasped and displaced an object. When the person reached for and caused a change in the state of the object on contact, however, infants looked longer when this action was inefficient than when it was efficient. Three-month-old infants also showed a key signature of adults' and older infants' causal inferences: This looking preference was abolished if a short spatial and temporal gap separated the action from its effect. The basic intuition that people are causal agents, who navigate around physical constraints to change the state of the world, may be one important foundation for infants' ability to plan their own actions and learn from the acts of others.

Worth the wait: Children trade off delay and reward in self- and other-benefiting decisions.

Human prosocial behaviors are supported by early-emerging psychological processes that detect and fulfill the needs of others. However, little is known about the mechanisms that enable children to deliver benefits to others at costs to the self, which requires weighing other-regarding and self-serving preferences. We used an intertemporal choice paradigm to systematically study and compare these behaviors in 5-year-old children. Our results show that other-benefiting and self-benefiting behavior share a common decision-making process that integrates delay and reward. Specifically, we found that children sought to minimize delay and maximize reward, and traded off delays against rewards, regardless of whether these rewards were for the children themselves or another child. However, we found that children were more willing to invest their time to benefit themselves than someone else. Together, these findings show that from childhood, other- and self-serving decisions are supported by a general mechanism that flexibly integrates information about the magnitude of rewards, and the opportunity costs of pursuing them. A video abstract of this article can be viewed at: https://youtu.be/r8S0DGe7f8Q.

A common cortical metric for spatial, temporal, and social distance.

Distance describes more than physical space: we speak of close friends and distant relatives, and of the near future and distant past. Did these ubiquitous spatial metaphors arise in language coincidentally or did they arise because they are rooted in a common neural computation? To address this question, we used statistical pattern recognition techniques to analyze human fMRI data. First, a machine learning algorithm was trained to discriminate patterns of fMRI responses based on relative egocentric distance within trials from one distance domain (e.g., photographs of objects relatively close to or far away from the viewer in spatial distance trials). Next, we tested whether the decision boundary generated from this training could distinguish brain responses according to relative egocentric distance within each of two separate distance domains (e.g., phrases referring to the immediate or more remote future within temporal distance trials; photographs of participants' friends or acquaintances within social distance trials). This procedure was repeated using all possible combinations of distance domains for training and testing the classifier. In all cases, above-chance decoding across distance domains was possible in the right inferior parietal lobule (IPL). Furthermore, the representational similarity structure within this brain area reflected participants' own judgments of spatial distance, temporal soon-ness, and social familiarity. Thus, the right IPL may contain a parsimonious encoding of proximity to self in spatial, temporal, and social frames of reference.

Toddlers Prefer Agents Who Help Those Facing Harder Tasks.

Capacities to understand and evaluate others' actions are fundamental to human social life. Infants and toddlers are sensitive to the costs of others' actions, infer others' values from the costs of the actions they take, and prefer those who help others to those who hinder them, but it is largely unknown whether and how cost considerations inform early understanding of third-party prosocial actions. In three experiments (N = 94), we asked whether 16-month-old toddlers value agents who selectively help those who need it most. Presented with two agents who attempted two tasks, toddlers preferentially looked to and touched someone who helped the agent in greater need, both when one agent's task required more effort and when the tasks were the same but one agent was weaker. These results provide evidence that toddlers engage in need-based evaluations of helping, applying their understanding of action utilities to their social evaluations.

An asynchronous, hands-off workflow for looking time experiments with infants.

The study of infant gaze has long been a key tool for understanding the developing mind. However, labor-intensive data collection and processing limit the speed at which this understanding can be advanced. Here, we demonstrate an asynchronous workflow for conducting violation-of-expectation (VoE) experiments, which is fully "hands-off" for the experimenter. We first replicate four classic VoE experiments in a synchronous online setting, and show that VoE can generate highly replicable effects through remote testing. We then confirm the accuracy of a state-of-the-art gaze annotation software, iCatcher+ in a new setting. Third, we train parents to control the experiment flow based on the infant's gaze. Combining all three innovations, we then conduct an asynchronous automated infant-contingent VoE experiment. The hands-off workflow successfully replicates a classic VoE effect: infants look longer at inefficient actions than efficient ones. We compare the resulting effect size and statistical power to the same study run in-lab and synchronously via Zoom. The hands-off workflow significantly reduces the marginal cost and time per participant, enabling larger sample sizes. By enhancing the reproducibility and robustness of findings relying on infant looking, this workflow could help support a cumulative science of infant cognition. Tools to implement the workflow are openly available. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Knowing before doing: Review and mega-analysis of action understanding in prereaching infants.

The relationship between experience and knowledge is one of the oldest and deepest questions in psychology. In developmental science, research on this question has focused on prereaching infants who cannot yet retrieve objects by reaching for and grasping them. Over the past 2 decades, behavioral research in this population has produced two seemingly contradictory findings: After first-person experience with reaching via "sticky mittens" training, (a) infants come to expect that people reach efficiently, toward goal objects, but (b) under some conditions, they can express these expectations without training. We hypothesize that prereaching infants' understanding of other people's actions is driven by the representational demands of the tasks used to test their abilities, rather than by first-person motor experience per se. We conducted a qualitative review and a quantitative, preregistered "mega-analysis" of the original data from this past work (i.e., an analysis of looking responses from N = 650 infants, 30 conditions, and 8 articles). We found that the manipulations with the strongest effects (measured via effect sizes and Bayes factors) on infants' understanding of other people's goals and physical constraints, controlling for infant age, were abstract features of action: Whether the action produced an observable effect in the world on contact and provided unambiguous evidence for the actor's goal. We end by presenting a broad hypothesis about how young infants learn about other people's minds and actions, centered on an early intuitive theory of action planning, to be tested with future work. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

iCatcher+: Robust and Automated Annotation of Infants' and Young Children's Gaze Behavior From Videos Collected in Laboratory, Field, and Online Studies.

Technological advances in psychological research have enabled large-scale studies of human behavior and streamlined pipelines for automatic processing of data. However, studies of infants and children have not fully reaped these benefits because the behaviors of interest, such as gaze duration and direction, still have to be extracted from video through a laborious process of manual annotation, even when these data are collected online. Recent advances in computer vision raise the possibility of automated annotation of these video data. In this article, we built on a system for automatic gaze annotation in young children, iCatcher, by engineering improvements and then training and testing the system (referred to hereafter as iCatcher+) on three data sets with substantial video and participant variability (214 videos collected in U.S. lab and field sites, 143 videos collected in Senegal field sites, and 265 videos collected via webcams in homes; participant age range = 4 months-3.5 years). When trained on each of these data sets, iCatcher+ performed with near human-level accuracy on held-out videos on distinguishing "LEFT" versus "RIGHT" and "ON" versus "OFF" looking behavior across all data sets. This high performance was achieved at the level of individual frames, experimental trials, and study videos; held across participant demographics (e.g., age, race/ethnicity), participant behavior (e.g., movement, head position), and video characteristics (e.g., luminance); and generalized to a fourth, entirely held-out online data set. We close by discussing next steps required to fully automate the life cycle of online infant and child behavioral studies, representing a key step toward enabling robust and high-throughput developmental research.

What Could Go Wrong: Adults and Children Calibrate Predictions and Explanations of Others' Actions Based on Relative Reward and Danger.

When human adults make decisions (e.g., wearing a seat belt), we often consider the negative consequences that would ensue if our actions were to fail, even if we have never experienced such a failure. Do the same considerations guide our understanding of other people's decisions? In this paper, we investigated whether adults, who have many years of experience making such decisions, and 6- and 7-year-old children, who have less experience and are demonstrably worse at judging the consequences of their own actions, conceive others' actions as motivated both by reward (how good reaching one's intended goal would be), and by what we call "danger" (how badly one's action could end). In two pre-registered experiments, we tested whether adults and 6- and 7-year-old children tailor their predictions and explanations of an agent's action choices to the specific degree of danger and reward entailed by each action. Across four different tasks, we found that children and adults expected others to negatively appraise dangerous situations and minimize the danger of their actions. Children's and adults' judgments varied systematically in accord with both the degree of danger the agent faced and the value the agent placed on the goal state it aimed to achieve. However, children did not calibrate their inferences about how much an agent valued the goal state of a successful action in accord with the degree of danger the action entailed, and adults calibrated these inferences more weakly than inferences concerning the agent's future action choices. These results suggest that from childhood, people use a degree of danger and reward to make quantitative, fine-grained explanations and predictions about other people's behavior, consistent with computational models on theory of mind that contain continuous representations of other agents' action plans.

Dangerous Ground: One-Year-Old Infants are Sensitive to Peril in Other Agents' Action Plans.

Do infants appreciate that other people's actions may fail, and that these failures endow risky actions with varying degrees of negative utility (i.e., danger)? Three experiments, including a pre-registered replication, addressed this question by presenting 12- to 15-month-old infants (N = 104, 52 female, majority White) with an animated agent who jumped over trenches of varying depth towards its goals. Infants expected the agent to minimize the danger of its actions, and they learned which goal the agent preferred by observing how much danger it risked to reach each goal, even though the agent's actions were physically identical and never failed. When we tested younger, 10-month-old infants (N = 102, 52 female, majority White) in a fourth experiment, they did not succeed consistently on the same tasks. These findings provide evidence that one-year-old infants use the height that other agents could fall from in order to explain and predict those agents' actions.

Moderated Online Data-Collection for Developmental Research: Methods and Replications.

Online data collection methods are expanding the ease and access of developmental research for researchers and participants alike. While its popularity among developmental scientists has soared during the COVID-19 pandemic, its potential goes beyond just a means for safe, socially distanced data collection. In particular, advances in video conferencing software has enabled researchers to engage in face-to-face interactions with participants from nearly any location at any time. Due to the novelty of these methods, however, many researchers still remain uncertain about the differences in available approaches as well as the validity of online methods more broadly. In this article, we aim to address both issues with a focus on moderated (synchronous) data collected using video-conferencing software (e.g., Zoom). First, we review existing approaches for designing and executing moderated online studies with young children. We also present concrete examples of studies that implemented choice and verbal measures (Studies 1 and 2) and looking time (Studies 3 and 4) across both in-person and online moderated data collection methods. Direct comparison of the two methods within each study as well as a meta-analysis of all studies suggest that the results from the two methods are comparable, providing empirical support for the validity of moderated online data collection. Finally, we discuss current limitations of online data collection and possible solutions, as well as its potential to increase the accessibility, diversity, and replicability of developmental science.

Six-month-old infants expect agents to minimize the cost of their actions.

Substantial evidence indicates that infants expect agents to move directly to their goals when no obstacles block their paths, but the representations that articulate this expectation and its robustness have not been characterized. Across three experiments (total N=60), 6-month-old infants responded to a novel, curvilinear action trajectory on the basis of its efficiency, in accord with the expectation that an agent will move to its goal on the least costly path that the environment affords. Infants expected minimally costly action when presented with a novel constraint, and extended this expectation to agents who had previously acted inefficiently. Infants' understanding of goal-directed action cannot be explained alone by sensitivity to specific features of agent's actions (e.g. agents tend to move on straight paths, along supporting surfaces, when facing their goals directly) or extrapolations of agents' past actions to their future ones (e.g. if an agent took the shortest path to an object in the past, it will continue to do so in the future). Instead, infants' reasoning about efficiency accords with the overhypothesis that agents minimize the cost of their actions.

Ten-month-old infants infer the value of goals from the costs of actions.

Infants understand that people pursue goals, but how do they learn which goals people prefer? We tested whether infants solve this problem by inverting a mental model of action planning, trading off the costs of acting against the rewards actions bring. After seeing an agent attain two goals equally often at varying costs, infants expected the agent to prefer the goal it attained through costlier actions. These expectations held across three experiments that conveyed cost through different physical path features (height, width, and incline angle), suggesting that an abstract variable-such as "force," "work," or "effort"-supported infants' inferences. We modeled infants' expectations as Bayesian inferences over utility-theoretic calculations, providing a bridge to recent quantitative accounts of action understanding in older children and adults.