Social interactions are composed of coordinated, multimodal behaviors with each individual taking turns and sharing attention. By the second year of life, infants are able to engage in coordinated interactions with their caregivers. Although research has focused on the social behaviors that enable parent-infant dyads to engage in joint attention, little work has been done to understand the sensorimotor mechanisms underlying coordination. Using wireless head-mounted eye trackers and motion sensing, we recorded 31 dyads as they played freely in a home-like laboratory. We identified moments of visual joint attention, when parent and infant were looking at the same object, and then measured the dyad’s head and hand movements during and around joint attention. We found evidence that both parents and infants still their bodies during joint attention. We also compared instances of joint attention that were led by the parent or by the infant and identified different sensorimotor pathways that support the two types of joint attention. These results provide the foundation for continued exploration of the critical role of sensorimotor processes on coordinated social behavior and its development.

The input for early language learning is often viewed as a landscape of ambiguity with the occasional high-quality naming event providing resources to resolve uncertainty. Word learning from ambiguous naming events is often studied using screen-based cross-situational learning tasks. Little is known, however, on how ambiguity impacts real-time word learning in free-flowing interactions. To explore this question, we asked parent-infant dyads to play in a home-like environment with unfamiliar objects while wearing head-mounted eye trackers. After the play session, we tested whether infants learned any of the object-label mappings and categorized individual words as learned or not learned. Dyadic behaviors and the visual information available to infants during the naming moments of learned and not learned words were analyzed. The results show that infants’ embodied attention during ambiguous naming moments was the key to predicting learning outcomes. Specifically, infants held and looked at the target object longer in ambiguous instances that led to learning. Our results emphasize the importance of studying word learning in naturalistic environments to better understand the cues infants use to resolve ambiguity in everyday learning contexts.

Infants’ ability to anticipate the actions they observe is thought to be a critical skill in early social-cognitive development. A considerable body of research has demonstrated that infants can anticipate observed actions from a variety of cues in different kinds of visual contexts. However, most of this work has relied on screen-based eye-tracking paradigm using highly controlled computer stimuli. Less is known is known about whether and how infants anticipate live actions in natural settings. One prior study demonstrated that infants did anticipate their parents’ actions during live, free-flowing parent-infant play, though they did so infrequently. Using head-mounted eye-tracking, the current study aimed to build upon this work by exploring whether infants make gaze predictions while observing their parents perform an everyday activity in a home-like environment—assembling several peanut-butter and jelly sandwiches. Preliminary findings reveal that infants anticipate their parents’ actions at relatively high rates, indicating a close coupling between parent actions and infant gaze. Rates of prediction did not change over the course of the observation, suggesting that infants already possess prior knowledge of the action sequence structure that they utilize to successfully predict their parents’ ongoing actions.

Early language learning relies on statistical regularities that exist across timescales in infants’ lives. Two types of these statistical regularities are the routine activities that make up their day, such as mealtime and play, and the real-time repeated behaviors that make up the moment-by-moment dynamics of those routines. These two types of regularities are different in nature and are embedded at two different temporal scales, which led to divergent research in the literature – those who collect long-form recordings and observations of at-home behavior and those who use eye trackers and micro-level analyses to quantify real-time behavior in laboratories. The goal of present paper is to jointly examine and connect the statistical regularities at these two timescales. Towards this goal, we brought wearable eye trackers to English- and Spanish-speaking families’ homes to record parent and toddler visual attention during daily routines. We transcribed parent speech during object play and mealtime and coded toddler visual attention during naming moments. We found that parents and toddlers jointly interacted with the unique vocabularies of the two activities. Although naming and attention were more coordinated during object play, mealtime still afforded opportunities for high-quality naming moments. Our results lay the building blocks for connecting these two lines of research and demonstrate the feasibility of at-home data collection with eye trackers.

Parental input in the form of visual joint attention is hypothesized to serve a critical role in the development of infant attention, acting as a training ground by scaffolding an infant’s ability to sustain visual attention in real-time. We extended this hypothesis by studying the effects of parent speech on infant visual and manual attention. Thirty-four toddlers and their parents participated in a free-play study while wearing head-mounted eye trackers. Infant multimodal behaviors were measured in four ways: visual attention, manual action, hand-eye coordination, and joint visual attention with their parent. Overall, we found that longer durations of attention were accompanied by parent speech. Moreover, sustained attention, defined as behaviors lasting 3s or more, almost always occurred with parent speech. Individual differences in parent-infant coordination were also explored. These results suggest that parent-infant interactions create multimodal opportunities for infants to practice sustaining attention.

Numerous studies in cognitive development have provided converging evidence that Joint Attention (JA) is crucial for children to learn about the world together with their parents. However, a closer look reveals that, in the literature, JA has been operationally defined in different ways. For example, some definitions require explicit signals of “awareness” of being in JA—such as gaze following, while others simply define JA as shared gaze to an object or activity. But what if “awareness” is possible without gaze following? The present study examines egocentric images collected via head-mounted eye-trackers during parent-child toy play. A Convolutional Neural Network model was used to process and learn to classify raw egocentric images as JA vs not JA. We demonstrate individual child and parent egocentric views can be classified as being part of a JA bout at above chance levels. This provides new evidence that an individual can be “aware” they are in JA based solely on the in-the-moment visual information. Moreover, both models trained on child views and those trained on parent views leveraged the visual properties associated with visual object holding to improve classification accuracy—suggesting a critical role for object handling in not only establishing JA, as shown in previous research, but also in inferring the social partner’s attentional state during JA.

Infants learn the meaning of words from accumulated experiences of real-time interactions with their caregivers. To study the effects of visual sensory input on word learning, we recorded infant's view of the world using head-mounted eye trackers during free-flowing play with a caregiver. While playing, infants were exposed to novel label-object mappings and later learning outcomes for these items were tested after the play session. In this study we use a classification based approach to link properties of infants' visual scenes during naturalistic labeling moments to their word learning outcomes. We find that a model which integrates both highly informative and ambiguous sensory evidence is a better fit to infants' individual learning outcomes than models where either type of evidence is taken alone, and that raw labeling frequency is unable to account for the word learning differences we observe. Here we demonstrate how a computational model, using only raw pixels taken from the egocentric scene image, can derive insights on human language learning.