Online Assessment of Motor, Cognitive, and Communicative Achievements in 4-Month-Old Infants

Remote methods for data collection allow us to quickly collect large amounts of data, offering several advantages as compared to in-lab administration. We investigated the applicability of an online assessment of motor, cognitive, and communicative development in 4-month-old infants based on several items of the Bayley Scales of Infant Development, 3rd edition (BSID-III). We chose a subset of items which were representative of the typical developmental achievements at 4 months of age and that we could administer online with the help of the infant’s caregiver using materials which were easily available at home. Results showed that, in a sample of infants tested live (N = 18), the raw scores of the BSID-III were significantly correlated with the raw scores of a subset of items corresponding to those administered to a sample of infants tested online (N = 53). Moreover, for the “online” participants, the raw scores of the online assessment did not significantly differ from the corresponding scores of the “live” participants. These findings suggest that the online assessment was to some extent comparable to the live administration of the same items, thus representing a viable opportunity to remotely evaluate infant development when in-person assessment is not possible.

Neural sampling of the speech signal at different timescales by children with dyslexia

Phonological difficulties characterize individuals with dyslexia across languages. Currently debated is whether these difficulties arise from atypical neural sampling of (or entrainment to) auditory information in speech at slow rates (<10 Hz, related to speech rhythm), faster rates, or neither. MEG studies with adults suggest that atypical sampling in dyslexia affects faster modulations in the neurophysiological gamma band, related to phoneme-level representation. However, dyslexic adults have had years of reduced experience in converting graphemes to phonemes, which could itself cause atypical gamma-band activity. The present study was designed to identify specific linguistic timescales at which English children with dyslexia may show atypical entrainment. Adopting a developmental focus, we hypothesized that children with dyslexia would show atypical entrainment to the prosodic and syllable-level information that is exaggerated in infant-directed speech and carried primarily by amplitude modulations <10 Hz. MEG was recorded in a naturalistic story-listening paradigm. The modulation bands related to different types of linguistic information were derived directly from the speech materials, and lagged coherence at multiple temporal rates spanning 0.9-40 Hz was computed. Group differences in lagged speech-brain coherence between children with dyslexia and control children were most marked in neurophysiological bands corresponding to stress and syllable-level information (<5 Hz in our materials), and phoneme-level information (12-40 Hz). Functional connectivity analyses showed network differences between groups in both hemispheres, with dyslexic children showing significantly reduced global network efficiency. Global network efficiency correlated with dyslexic children's oral language development and with control children's reading development. These developmental data suggest that dyslexia is characterized by atypical neural sampling of auditory information at slower rates. They also throw new light on the nature of the gamma band temporal sampling differences reported in MEG dyslexia studies with adults.

Zoom, Zoom, Baby! Assessing Mother-Infant Interaction During the Still Face Paradigm and Infant Language Development via a Virtual Visit Procedure

The COVID-19 pandemic has necessitated innovations in data collection protocols, including use of virtual or remote visits. Although developmental scientists used virtual visits prior to COVID-19, validation of virtual assessments of infant socioemotional and language development are lacking. We aimed to fill this gap by validating a virtual visit protocol that assesses mother and infant behavior during the Still Face Paradigm (SFP) and infant receptive and expressive communication using the Bayley-III Screening Test. Validation was accomplished through comparisons of data (i.e., proportions of missing data for a given task; observed infant and maternal behaviors) collected during in-person laboratory visits and virtual visits conducted via Zoom. Of the 119 mother-infant dyads who participated, 73 participated in lab visits only, 13 participated in virtual visits only, and 33 dyads participated in a combination of lab and virtual visits across four time points (3, 6, 9, and 12 months). Maternal perspectives of, and preferences for, virtual visits were also assessed. Proportions of missing data were higher during virtual visits, particularly for assessments of infant receptive communication. Nonetheless, comparisons of virtual and laboratory visits within a given time point (3, 6, or 9 months) indicated that mothers and infants showed similar proportions of facial expressions, vocalizations and directions of gaze during the SFP and infants showed similar and expected patterns of behavioral change across SFP episodes. Infants also demonstrated comparable expressive and receptive communicative abilities across virtual and laboratory assessments. Maternal reports of ease and preference for virtual visits varied by infant age, with mothers of 12-month-old infants reporting, on average, less ease of virtual visits and a preference for in-person visits. Results are discussed in terms of feasibility and validity of virtual visits for assessing infant socioemotional and language development, and broader advantages and disadvantages of virtual visits are also considered.

Exact Number Concepts Are Limited to the Verbal Count Range

Previous findings suggest that mentally representing exact numbers larger than four depends on a verbal count routine (e.g., "one, two, three . . ."). However, these findings are controversial because they rely on comparisons across radically different languages and cultures. We tested the role of language in number concepts within a single population-the Tsimane' of Bolivia-in which knowledge of number words varies across individual adults. We used a novel data-analysis model to quantify the point at which participants (N = 30) switched from exact to approximate number representations during a simple numerical matching task. The results show that these behavioral switch points were bounded by participants' verbal count ranges; their representations of exact cardinalities were limited to the number words they knew. Beyond that range, they resorted to numerical approximation. These results resolve competing accounts of previous findings and provide unambiguous evidence that large exact number concepts are enabled by language.

A Comparison of the Spatial Arrangement Method and the Total-Set Pairwise Rating Method for Obtaining Similarity Data in the Conceptual Domain

We compare two methods for obtaining similarity data in the conceptual domain. In the Spatial Arrangement Method (SpAM), participants organize stimuli on a computer screen so that the distance between stimuli represents their perceived dissimilarity. In Total-Set Pairwise Rating Method (PRaM), participants rate the (dis)similarity of all pairs of stimuli on a Likert scale. In each of three studies, we had participants indicate the similarity of four sets of conceptual stimuli with either PRaM or SpAM. Studies 1 and 2 confirm two caveats that have been raised for SpAM. (i) While SpAM takes significantly less time to complete than PRaM, it yields less reliable data than PRaM does. (ii) Because of the spatial manner in which similarity is measured in SpAM, the method is biased against feature representations. Despite these differences, averaging SpAM and PRaM dissimilarity data across participants yields comparable aggregate data. Study 3 shows that by having participants only judge half of the pairs in PRaM, its duration can be significantly reduced, without affecting the dissimilarity distribution, but at the cost of a smaller reliability. Having participants arrange multiple subsets of the stimuli does not do away with the spatial bias of SpAM.

Using a Developmental-Ecological Approach to Understand the Relation Between Language and Music

Neurocognitive and genetic approaches have made progress in understanding language-music interaction in the adult brain. Although there is broad agreement that learning processes affect how we represent, comprehend, and produce language and music, there is little understanding of the content and dynamics of the early language-music environment in the first years of life. A developmental-ecological approach sees learning and development as fundamentally embedded in a child's environment, and thus requires researchers to move outside of the lab to understand what children are seeing, hearing, and doing in their daily lives. In this paper, after first reviewing the limitations of traditional developmental approaches to understanding language-music interaction, we describe how a developmental-ecological approach can not only inform developmental theories of language-music learning, but also address challenges inherent to neurocognitive and genetic approaches. We then make suggestions for how researchers can best use the developmental-ecological approach to understand the similarities, differences, and co-occurrences in early music and language input.

Unilateral resection of both cortical visual pathways in a pediatric patient alters action but not perception

The human cortical visual system consists of two major pathways, a ventral pathway that subserves perception and a dorsal pathway that primarily subserves visuomotor control. Previous studies have found that children with cortical resections of the ventral visual pathway retain largely normal visuoperceptual abilities. Whether visually guided actions, supported by computations carried out by the dorsal pathway, follow a similar pattern of preservation remains unknown. To address this question, we examined visuoperceptual and visuomotor behaviors in a pediatric patient, TC, who underwent a cortical resection that included portions of the left ventral and dorsal pathways. We collected kinematic data when TC used her right and left hands to perceptually estimate the width of blocks that varied in width and length, and, separately, to grasp the same blocks. TC's perceptual estimation performance was comparable to that of controls, independent of the hand used. In contrast, relative to controls, she showed reduced visuomotor sensitivity to object shape and this was more evident when she grasped the objects with her contralesional right hand. These results provide novel evidence for a striking difference in the competence of the two visual pathways to cortical injuries acquired in childhood.

Natural Infant-Directed Speech Facilitates Neural Tracking of Prosody

Infants prefer to be addressed with infant-directed speech (IDS). IDS benefits language acquisition through amplified low-frequency amplitude modulations. It has been reported that this amplification increases electrophysiological tracking of IDS compared to adult-directed speech (ADS). It is still unknown which particular frequency band triggers this effect. Here, we compare tracking at the rates of syllables and prosodic stress, which are both critical to word segmentation and recognition. In mother-infant dyads (n=30), mothers described novel objects to their 9-month-olds while infants' EEG was recorded. For IDS, mothers were instructed to speak to their children as they typically do, while for ADS, mothers described the objects as if speaking with an adult. Phonetic analyses confirmed that pitch features were more prototypically infant-directed in the IDS-condition compared to the ADS-condition. Neural tracking of speech was assessed by speech-brain coherence, which measures the synchronization between speech envelope and EEG. Results revealed significant speech-brain coherence at both syllabic and prosodic stress rates, indicating that infants track speech in IDS and ADS at both rates. We found significantly higher speech-brain coherence for IDS compared to ADS in the prosodic stress rate but not the syllabic rate. This indicates that the IDS benefit arises primarily from enhanced prosodic stress. Thus, neural tracking is sensitive to parents' speech adaptations during natural interactions, possibly facilitating higher-level inferential processes such as word segmentation from continuous speech.

Citizen science can help to alleviate the generalizability crisis

Improving generalization in psychology will require more expansive data collection to fuel more expansive statistical models, beyond the scale of traditional lab research. We argue that citizen science is uniquely positioned to scale up data collection and, that in spite of certain limitations, can help to alleviate the generalizability crisis.

Category Clustering and Morphological Learning

Inflectional affixes expressing the same grammatical category (e.g., subject agreement) tend to appear in the same morphological position in the word. We hypothesize that this cross-linguistic tendency toward category clustering is at least partly the result of a learning bias, which facilitates the transmission of morphology from one generation to the next if each inflectional category has a consistent morphological position. We test this in an online artificial language experiment, teaching adult English speakers a miniature language consisting of noun stems representing shapes and suffixes representing the color and number features of each shape. In one experimental condition, each suffix category has a fixed position, with color in the first position and number in the second position. In a second condition, each specific combination of suffixes has a fixed order, but some combinations have color in the first position, and some have number in the first position. In a third condition, suffixes are randomly ordered on each presentation. While the language in the first condition is consistent with the category clustering principle, those in the other conditions are not. Our results indicate that category clustering of inflectional affixes facilitates morphological learning, at least in adult English speakers. Moreover, we found that languages that violate category clustering but still follow fixed affix ordering patterns are more learnable than languages with random ordering. Altogether, our results provide evidence for individual biases toward category clustering; we suggest that this bias may play a causal role in shaping the typological regularities in affix order we find in natural language.

A self-supervised domain-general learning framework for human ventral stream representation

Anterior regions of the ventral visual stream encode substantial information about object categories. Are top-down category-level forces critical for arriving at this representation, or can this representation be formed purely through domain-general learning of natural image structure? Here we present a fully self-supervised model which learns to represent individual images, rather than categories, such that views of the same image are embedded nearby in a low-dimensional feature space, distinctly from other recently encountered views. We find that category information implicitly emerges in the local similarity structure of this feature space. Further, these models learn hierarchical features which capture the structure of brain responses across the human ventral visual stream, on par with category-supervised models. These results provide computational support for a domain-general framework guiding the formation of visual representation, where the proximate goal is not explicitly about category information, but is instead to learn unique, compressed descriptions of the visual world.

Remote Data Collection During a Pandemic: A New Approach for Assessing and Coding Multisensory Attention Skills in Infants and Young Children

In early 2020, in-person data collection dramatically slowed or was completely halted across the world as many labs were forced to close due to the COVID-19 pandemic. Developmental researchers who assess looking time (especially those who rely heavily on in-lab eye-tracking or live coding techniques) were forced to re-think their methods of data collection. While a variety of remote or online platforms are available for gathering behavioral data outside of the typical lab setting, few are specifically designed for collecting and processing looking time data in infants and young children. To address these challenges, our lab developed several novel approaches for continuing data collection and coding for a remotely administered audiovisual looking time protocol. First, we detail a comprehensive approach for successfully administering the Multisensory Attention Assessment Protocol (MAAP), developed by our lab to assess multisensory attention skills (MASks; duration of looking, speed of shifting/disengaging, accuracy of audiovisual matching). The MAAP is administered from a distance (remotely) by using Zoom, Gorilla Experiment Builder, an internet connection, and a home computer. This new data collection approach has the advantage that participants can be tested in their homes. We discuss challenges and successes in implementing our approach for remote testing and data collection during an ongoing longitudinal project. Second, we detail an approach for estimating gaze direction and duration collected remotely from webcam recordings using a post processing toolkit (OpenFace) and demonstrate its effectiveness and precision. However, because OpenFace derives gaze estimates without translating them to an external frame of reference (i.e., the participant's screen), we developed a machine learning (ML) approach to overcome this limitation. Thus, third, we trained a ML algorithm [(artificial neural network (ANN)] to classify gaze estimates from OpenFace with respect to areas of interest (AOI) on the participant's screen (i.e., left, right, and center). We then demonstrate reliability between this approach and traditional coding approaches (e.g., coding gaze live). The combination of OpenFace and ML will provide a method to automate the coding of looking time for data collected remotely. Finally, we outline a series of best practices for developmental researchers conducting remote data collection for looking time studies.

Early concepts of intimacy: Young humans use saliva sharing to infer close relationships

Across human societies, people form "thick" relationships characterized by strong attachments, obligations, and mutual responsiveness. People in thick relationships share food utensils, kiss, or engage in other distinctive interactions that involve sharing saliva. We found that children, toddlers, and infants infer that dyads who share saliva (as opposed to other positive social interactions) have a distinct relationship. Children expect saliva sharing to happen in nuclear families. Toddlers and infants expect that people who share saliva will respond to one another in distress. Parents confirm that saliva sharing is a valid cue of relationship thickness in their children's social environments. The ability to use distinctive interactions to infer categories of relationships thus emerges early in life, without explicit teaching; this enables young humans to rapidly identify close relationships, both within and beyond families.

Reduced Theta Sampling in Infants at Risk for Dyslexia across the Sensitive Period of Native Phoneme Learning

Research on children and adults with developmental dyslexia-a specific difficulty in learning to read and spell-suggests that phonological deficits in dyslexia are linked to basic auditory deficits in temporal sampling. However, it remains undetermined whether such deficits are already present in infancy, especially during the sensitive period when the auditory system specializes in native phoneme perception. Because dyslexia is strongly hereditary, it is possible to examine infants for early predictors of the condition before detectable symptoms emerge. This study examines low-level auditory temporal sampling in infants at risk for dyslexia across the sensitive period of native phoneme learning. Using magnetoencephalography (MEG), we found deficient auditory sampling at theta in at-risk infants at both 6 and 12 months, indicating atypical auditory sampling at the syllabic rate in those infants across the sensitive period for native-language phoneme learning. This interpretation is supported by our additional finding that auditory sampling at theta predicted later vocabulary comprehension, nonlinguistic communication and the ability to combine words. Our results indicate a possible early marker of risk for dyslexia.

The effects of information utility and teachers' knowledge on evaluations of under-informative pedagogy across development

Teaching is a powerful way to transmit knowledge, but with this power comes a hazard: When teachers fail to select the best set of evidence for the learner, learners can be misled to draw inaccurate inferences. Evaluating others' failures as teachers, however, is a nontrivial problem; people may fail to be informative for different reasons, and not all failures are equally blameworthy. How do learners evaluate the quality of teachers, and what factors influence such evaluations? Here, we present a Bayesian model of teacher evaluation that considers the utility of a teacher's pedagogical sampling given their prior knowledge. In Experiment 1 (N=1168), we test the model predictions against adults' evaluations of a teacher who demonstrated all or a subset of the functions on a novel device. Consistent with the model predictions, participants' ratings integrated information about the number of functions taught, their values, as well as how much the teacher knew. Using a modified paradigm for children, Experiments 2 (N=48) and 3 (N=40) found that preschool-aged children (2a, 3) and adults (2b) make nuanced judgments of teacher quality that are well predicted by the model. However, after an unsuccessful attempt to replicate the results with preschoolers (Experiment 4, N=24), in Experiment 5 (N=24) we further investigate the development of teacher evaluation in a sample of seven- and eight-year-olds. These older children successfully distinguished teachers based on the amount and value of what was demonstrated, and their ability to evaluate omissions relative to the teacher's knowledge state was related to their tendency to spontaneously reference the teacher's knowledge when explaining their evaluations. In sum, our work illustrates how the human ability to learn from others supports not just learning about the world but also learning about the teachers themselves. By reasoning about others' informativeness, learners can evaluate others' teaching and make better learning decisions.

Comparing Online Webcam- and Laboratory-Based Eye-Tracking for the Assessment of Infants' Audio-Visual Synchrony Perception

Online data collection with infants raises special opportunities and challenges for developmental research. One of the most prevalent methods in infancy research is eye-tracking, which has been widely applied in laboratory settings to assess cognitive development. Technological advances now allow conducting eye-tracking online with various populations, including infants. However, the accuracy and reliability of online infant eye-tracking remain to be comprehensively evaluated. No research to date has directly compared webcam-based and in-lab eye-tracking data from infants, similarly to data from adults. The present study provides a direct comparison of in-lab and webcam-based eye-tracking data from infants who completed an identical looking time paradigm in two different settings (in the laboratory or online at home). We assessed 4-6-month-old infants (n = 38) in an eye-tracking task that measured the detection of audio-visual asynchrony. Webcam-based and in-lab eye-tracking data were compared on eye-tracking and video data quality, infants' viewing behavior, and experimental effects. Results revealed no differences between the in-lab and online setting in the frequency of technical issues and participant attrition rates. Video data quality was comparable between settings in terms of completeness and brightness, despite lower frame rate and resolution online. Eye-tracking data quality was higher in the laboratory than online, except in case of relative sample loss. Gaze data quantity recorded by eye-tracking was significantly lower than by video in both settings. In valid trials, eye-tracking and video data captured infants' viewing behavior uniformly, irrespective of setting. Despite the common challenges of infant eye-tracking across experimental settings, our results point toward the necessity to further improve the precision of online eye-tracking with infants. Taken together, online eye-tracking is a promising tool to assess infants' gaze behavior but requires careful data quality control. The demographic composition of both samples differed from the generic population on caregiver education: our samples comprised caregivers with higher-than-average education levels, challenging the notion that online studies will per se reach more diverse populations.

Implementing Remote Developmental Research: A Case Study of a Randomized Controlled Trial Language Intervention During COVID-19

Intervention studies with developmental samples are difficult to implement, in particular when targeting demographically diverse communities. Online studies have the potential to examine the efficacy of highly scalable interventions aimed at enhancing development, and to address some of the barriers faced by underrepresented communities for participating in developmental research. During the COVID-19 pandemic, we executed a fully remote randomized controlled trial (RCT) language intervention with third and fourth grade students (N = 255; age range 8.19-10.72 years, mean = 9.41, SD = 0.52) from diverse backgrounds across the United States. Using this as a case study, we discuss both challenges and solutions to conducting an intensive online intervention through the various phases of the study, including recruitment, data collection, and fidelity of intervention implementation. We provide comprehensive suggestions and takeaways, and conclude by summarizing some important tradeoffs for researchers interested in carrying out such studies.

Disruption Leads to Methodological and Analytic Innovation in Developmental Sciences: Recommendations for Remote Administration and Dealing With Messy Data

The COVID-19 pandemic has impacted data collection for longitudinal studies in developmental sciences to an immeasurable extent. Restrictions on conducting in-person standardized assessments have led to disruptive innovation, in which novel methods are applied to increase participant engagement. Here, we focus on remote administration of behavioral assessment. We argue that these innovations in remote assessment should become part of the new standard protocol in developmental sciences to facilitate data collection in populations that may be hard to reach or engage due to burdensome requirements (e.g., multiple in-person assessments). We present a series of adaptations to developmental assessments (e.g., Mullen) and a detailed discussion of data analytic approaches to be applied in the less-than-ideal circumstances encountered during the pandemic-related shutdown (i.e., missing or messy data). Ultimately, these remote approaches actually strengthen the ability to gain insight into developmental populations and foster pragmatic innovation that should result in enduring change.

Consistency and inconsistency in caregiver reporting of vocabulary

Vocabulary checklists completed by caregivers are a common way of measuring children's vocabulary knowledge. We provide evidence from checklist data from 31 children with and without autism spectrum disorder. When asked to report twice about whether or not their child produces a particular word, caregivers are largely consistent in their responses, but where they are inconsistent, these inconsistencies affect verbs more than nouns. This difference holds both for caregivers of children with autism spectrum disorder and caregivers of typically-developing children. We suggest that caregivers may be less sure of their child's knowledge about verbs than nouns. This data converges with prior evidence comparing language samples of words children produce in a recorded interaction with checklist data, and it has implications for how researchers use checklist data in cases where the reliability of estimates of verb knowledge is critical.

How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning?

Humans learn from visual inputs at multiple timescales, both rapidly and flexibly acquiring visual knowledge over short periods, and robustly accumulating online learning progress over longer periods. Modeling these powerful learning capabilities is an important problem for computational visual cognitive science, and models that could replicate them would be of substantial utility in real-world computer vision settings. In this work, we establish benchmarks for both real-time and life-long continual visual learning. Our real-time learning benchmark measures a model's ability to match the rapid visual behavior changes of real humans over the course of minutes and hours, given a stream of visual inputs. Our life-long learning benchmark evaluates the performance of models in a purely online learning curriculum obtained directly from child visual experience over the course of years of development. We evaluate a spectrum of recent deep self-supervised visual learning algorithms on both benchmarks, finding that none of them perfectly match human performance, though some algorithms perform substantially better than others. Interestingly, algorithms embodying recent trends in self-supervised learning - including BYOL, SwAV and MAE - are substantially worse on our benchmarks than an earlier generation of self-supervised algorithms such as SimCLR and MoCo-v2. We present analysis indicating that the failure of these newer algorithms is primarily due to their inability to handle the kind of sparse low-diversity datastreams that naturally arise in the real world, and that actively leveraging memory through negative sampling - a mechanism eschewed by these newer algorithms - appears useful for facilitating learning in such low-diversity environments. We also illustrate a complementarity between the short and long timescales in the two benchmarks, showing how requiring a single learning algorithm to be locally context-sensitive enough to match real-time learning changes while stable enough to avoid catastrophic forgetting over the long term induces a trade-off that human-like algorithms may have to straddle. Taken together, our benchmarks establish a quantitative way to directly compare learning between neural networks models and human learners, show how choices in the mechanism by which such algorithms handle sample comparison and memory strongly impact their ability to match human learning abilities, and expose an open problem space for identifying more flexible and robust visual self-supervision algorithms.

Intuitive physics learning in a deep-learning model inspired by developmental psychology

'Intuitive physics' enables our pragmatic engagement with the physical world and forms a key component of 'common sense' aspects of thought. Current artificial intelligence systems pale in their understanding of intuitive physics, in comparison to even very young children. Here we address this gap between humans and machines by drawing on the field of developmental psychology. First, we introduce and open-source a machine-learning dataset designed to evaluate conceptual understanding of intuitive physics, adopting the violation-of-expectation (VoE) paradigm from developmental psychology. Second, we build a deep-learning system that learns intuitive physics directly from visual data, inspired by studies of visual cognition in children. We demonstrate that our model can learn a diverse set of physical concepts, which depends critically on object-level representations, consistent with findings from developmental psychology. We consider the implications of these results both for AI and for research on human cognition.

The origins of trust: Humans' reliance on communicative cues supersedes firsthand experience during the second year of life

How do people learn about things that they have never perceived or inferred-like molecules, miracles or Marie-Antoinette? For many thinkers, trust is the answer. Humans rely on communicated information, sometimes even when it contradicts blatantly their firsthand experience. We investigate the early ontogeny of this trust using a non-verbal search paradigm in four main studies and three supplementary studies (N = 208). Infants and toddlers first see where a reward is, and then an informant communicates to them that it is in another location. We use this general experimental set-up to assess the role of age, informants' knowledge, cue's familiarity, and communicative context on trust in communicated information. Results reveal that infants and toddlers quickly trust familiar and novel communicative cues from well-informed adults. When searching for the reward, they follow a well-informed adults' communicative cue, even when it contradicts what they just saw. Furthermore, infants are less likely to be guided by familiar and novel cues from poorly informed adults than toddlers. Thus, reliance on communication is calibrated during early childhood, up to the point of overriding evidence about informants' knowledge. Moreover, toddlers trust much more strongly a novel cue when it is used in a communicative manner. Toddlers' trust cannot be explained by mere compliance: it is highly reduced when communicated information is pitted against what participants currently see. Thus, humans' strong tendency to rely on familiar and novel communicative cues emerges in infancy, and intensifies during the second year of life. This article is protected by copyright. All rights reserved.

Toward a “Standard Model” of Early Language Learning

A standard model is a theoretical framework that synthesizes observables into a quantitative consensus. Have researchers made progress toward this kind of synthesis for children’s early language learning? Many computational models of early vocabulary learning assume that individual words are learned through an accumulation of environmental input. This assumption is also implicit in empirical work that emphasizes links between language input and learning outcomes. However, models have typically focused on average performance, whereas empirical work has focused on variability. To model individual variability, we relate the tradition of research on accumulator models to item response theory models from psychometrics. This formal connection reveals that currently available data sets do not allow researchers to test the resulting models fully, illustrating a critical need for theory to contribute to shaping new data collection and creating and testing an eventual standard model.

Tonal Emergence: An agent-based model of tonal coordination

Humans have a remarkable capacity for coordination. Our ability to interact and act jointly in groups is crucial to our success as a species. Joint Action (JA) research has often concerned itself with simplistic behaviors in highly constrained laboratory tasks. But there has been a growing interest in understanding complex coordination in more open-ended contexts. In this regard, collective music improvisation has emerged as a fascinating model domain for studying basic JA mechanisms in an unconstrained and highly sophisticated setting. A number of empirical studies have begun to elucidate coordination mechanisms underlying joint musical improvisation, but these findings have yet to be cached out in a working computational model. The present work fills this gap by presenting Tonal Emergence, an idealized agent-based model of improvised musical coordination. Tonal Emergence models the coordination of notes played by improvisers to generate harmony (i.e., tonality), by simulating agents that stochastically generate notes biased towards maximizing harmonic consonance given their partner's previous notes. The model replicates an interesting empirical result from a previous study of professional jazz pianists: feedback loops of mutual adaptation between interacting agents support the production of consonant harmony. The model is further explored to show how complex tonal dynamics, such as the production and dissolution of stable tonal centers, are supported by agents that are characterized by (i) a tendency to strive toward consonance, (ii) stochasticity, and (iii) a limited memory for previously played notes. Tonal Emergence thus provides a grounded computational model to simulate and probe the coordination mechanisms underpinning one of the more remarkable feats of human cognition: collective music improvisation.

Bringing Home Baby Euclid: Testing Infants' Basic Shape Discrimination Online

Online developmental psychology studies are still in their infancy, but their role is newly urgent in the light of the COVID-19 pandemic and the suspension of in-person research. Are online studies with infants a suitable stand-in for laboratory-based studies? Across two unmonitored online experiments using a change-detection looking-time paradigm with 96 7-month-old infants, we found that infants did not exhibit measurable sensitivities to the basic shape information that distinguishes between 2D geometric forms, as had been observed in previous laboratory experiments. Moreover, while infants were distracted in our online experiments, such distraction was nevertheless not a reliable predictor of their ability to discriminate shape information. Our findings suggest that the change-detection paradigm may not elicit infants' shape discrimination abilities when stimuli are presented on small, personal computer screens because infants may not perceive two discrete events with only one event displaying uniquely changing information that draws their attention. Some developmental paradigms used with infants, even those that seem well-suited to the constraints and goals of online data collection, may thus not yield results consistent with the laboratory results that rely on highly controlled settings and specialized equipment, such as large screens. As developmental researchers continue to adapt laboratory-based methods to online contexts, testing those methods online is a necessary first step in creating robust tools and expanding the space of inquiry for developmental science conducted online.

Logical word learning: The case of kinship

We examine the conceptual development of kinship through the lens of program induction. We present a computational model for the acquisition of kinship term concepts, resulting in the first computational model of kinship learning that is closely tied to developmental phenomena. We demonstrate that our model can learn several kinship systems of varying complexity using cross-linguistic data from English, Pukapuka, Turkish, and Yanomamö. More importantly, the behavioral patterns observed in children learning kinship terms, under-extension and over-generalization, fall out naturally from our learning model. We then conducted interviews to simulate realistic learning environments and demonstrate that the characteristic-to-defining shift is a consequence of our learning model in naturalistic contexts containing abstract and concrete features. We use model simulations to understand the influence of logical simplicity and children’s learning environment on the order of acquisition of kinship terms, providing novel predictions for the learning trajectories of these words. We conclude with a discussion of how this model framework generalizes beyond kinship terms, as well as a discussion of its limitations.

Groupitizing modifies neural coding of numerosity

Numerical estimation of arrays of objects is faster and more accurate when items can be clustered into groups, a phenomenon termed “groupitizing.” Grouping can facilitate segregation into subitizable “chunks,” each easily estimated, then summed. The current study investigates whether spatial grouping of arrays drives specific neural responses during numerical estimation, reflecting strategies such as exact calculation and fact retrieval. Fourteen adults were scanned with fMRI while estimating either the numerosity or shape of arrays of items, either randomly distributed or spatially grouped. Numerosity estimation of both classes of stimuli elicited common activation of a right lateralized frontoparietal network. Grouped stimuli additionally recruited regions in the left hemisphere and bilaterally in the angular gyrus. Multivariate pattern analysis showed that classifiers trained with the pattern of neural activations read out from parietal regions, but not from the primary visual areas, can decode different numerosities both within and across spatial arrangements. The behavioral numerical acuity correlated with the decoding performance of the parietal but not with occipital regions. Overall, this experiment suggests that the estimation of grouped stimuli relies on the approximate number system for numerosity estimation, but additionally recruits regions involved in calculation.

The forms and meanings of grammatical markers support efficient communication

Functionalist accounts of language suggest that forms are paired with meanings in ways that support efficient communication. Previous work on grammatical marking suggests that word forms have lengths that enable efficient production, and work on the semantic typology of the lexicon suggests that word meanings represent efficient partitions of semantic space. Here we establish a theoretical link between these two lines of work and present an information-theoretic analysis that captures how communicative pressures influence both form and meaning. We apply our approach to the grammatical features of number, tense, and evidentiality and show that the approach explains both which systems of feature values are attested across languages and the relative lengths of the forms for those feature values. Our approach shows that general information-theoretic principles can capture variation in both form and meaning across languages.

Public misconceptions about dyslexia: The role of intuitive psychology

Despite advances in its scientific understanding, dyslexia is still associated with rampant public misconceptions. Here, we trace these misconceptions to the interaction between two intuitive psychological principles: Dualism and Essentialism. We hypothesize that people essentialize dyslexia symptoms that they anchor in the body. Experiment 1 shows that, when dyslexia is associated with visual confusions (b/d reversals)—symptoms that are naturally viewed as embodied (in the eyes), laypeople consider dyslexia as more severe, immutable, biological, and heritable, compared to when dyslexia is linked to difficulties with phonological decoding (a symptom seen as less strongly embodied). Experiments 2–3 show that the embodiment of symptoms plays a causal role in promoting essentialist thinking. Experiment 2 shows that, when participants are provided evidence that the symptoms of dyslexia are embodied (i.e., they “show up” in a brain scan), people are more likely to consider dyslexia as heritable compared to when the same symptoms are diagnosed behaviorally (without any explicit evidence for the body). Finally, Experiment 3 shows that reasoning about the severity of dyslexia symptoms can be modulated by manipulating people’s attitudes about the mind/body links, generally. These results show how public attitudes towards psychological disorders arise from the very principles that make the mind tick.

Mapping Word to World in ASL: Evidence from a Human Simulation Paradigm

Across languages, children map words to meaning with great efficiency, despite a seemingly unconstrained space of potential mappings. The literature on how children do this is primarily limited to spoken language. This leaves a gap in our understanding of sign language acquisition, because several of the hypothesized mechanisms that children use are visual (e.g., visual attention to the referent), and sign languages are perceived in the visual modality. Here, we used the Human Simulation Paradigm in American Sign Language (ASL) to determine potential cues to word learning. Sign-naïve adult participants viewed video clips of parent-child interactions in ASL, and at a designated point, had to guess what ASL sign the parent produced. Across two studies, we demonstrate that referential clarity in ASL interactions is characterized by access to information about word class and referent presence (for verbs), similarly to spoken language. Unlike spoken language, iconicity is a cue to word meaning in ASL, although this is not always a fruitful cue. We also present evidence that verbs are highlighted well in the input, relative to spoken English. The results shed light on both similarities and differences in the information that learners may have access to in acquiring signed versus spoken languages.

Translating RDoC to Real-World Impact in Developmental Psychopathology: A Neurodevelopmental Framework for Application of Mental Health Risk Calculators

The National Institute of Mental Health Research Domain Criteria's (RDoC) has prompted a paradigm shift from categorical psychiatric disorders to considering multiple levels of vulnerability for probabilistic risk of disorder. However, the lack of neurodevelopmentally-based tools for clinical decision-making has limited RDoC's real-world impact. Integration with developmental psychopathology principles and statistical methods actualize the clinical implementation of RDoC to inform neurodevelopmental risk. In this conceptual paper, we introduce the probabilistic mental health risk calculator as an innovation for such translation and lay out a research agenda for generating an RDoC- and developmentally-informed paradigm that could be applied to predict a range of developmental psychopathologies from early childhood to young adulthood. We discuss methods that weigh the incremental utility for prediction based on intensity and burden of assessment, the addition of developmental change patterns, considerations for assessing outcomes, and integrative data approaches. Throughout, we illustrate the risk calculator approach with different neurodevelopmental pathways and phenotypes. Finally, we discuss real-world implementation of these methods for improving early identification and prevention of developmental psychopathology. We propose that mental health risk calculators can build a needed bridge between RDoC's multiple units of analysis and developmental science.

Steps towards a computational ethology: an automatized, interactive setup to investigate filial imprinting and biological predispositions

Soon after hatching, the young of precocial species, such as domestic chicks or ducklings, learn to recognize their social partner by simply being exposed to it (imprinting process). Even artificial objects or stimuli displayed on monitor screens can effectively trigger filial imprinting, though learning is canalized by spontaneous preferences for animacy signals, such as certain kinds of motion or a face-like appearance. Imprinting is used as a behavioural paradigm for studies on memory formation, early learning and predispositions, as well as number and space cognition, and brain asymmetries. Here, we present an automatized setup to expose and/or test animals for a variety of imprinting experiments. The setup consists of a cage with two high-frequency screens at the opposite ends where stimuli are shown. Provided with a camera covering the whole space of the cage, the behaviour of the animal is recorded continuously. A graphic user interface implemented in Matlab allows a custom configuration of the experimental protocol, that together with Psychtoolbox drives the presentation of images on the screens, with accurate time scheduling and a highly precise framerate. The setup can be implemented into a complete workflow to analyse behaviour in a fully automatized way by combining Matlab (and Psychtoolbox) to control the monitor screens and stimuli, DeepLabCut to track animals' behaviour, Python (and R) to extract data and perform statistical analyses. The automated setup allows neuro-behavioural scientists to perform standardized protocols during their experiments, with faster data collection and analyses, and reproducible results.

How do we interpret questions? Simplified representations of knowledge guide humans' interpretation of information requests

This paper investigates the cognitive mechanisms supporting humans' interpretation of requests for information. Learners can only search for a piece of information if they know that they are ignorant about it. Thus, in principle, the interpretation of requests for information could be guided by representations of Socratic ignorance (tracking what people know that they do not know). Alternatively, the interpretation of requests for information could be simplified by relying primarily on simple knowledge tracking (i.e., merely tracking what people know). We judged these hypotheses by testing two-and-a-half-year-old toddlers (N = 18), five- to seven-year-old children (N = 72), and adults (N = 384). In our experiments, a speaker asked a question that could be disambiguated by tracking her state of knowledge. We manipulated the speakers' visuals to modulate the complexity of the ignorance representation required to disambiguate their questions. Toddlers showed no tendency to appeal to representations of Socratic ignorance when disambiguating questions (Pilot S1). Five- to seven-year-olds exhibited a similar pattern of results, and they performed better when information requests could be disambiguated using simple knowledge tracking (Studies 1a-1b). Adults used representations of Socratic ignorance to interpret questions, but were more confident when simple knowledge tracking was sufficient to disambiguate information requests (Studies 2-3). Moreover, adults disambiguated questions as if speakers could request information about things that they were ignorant of, even when speakers had no reason to know about their ignorance (Studies 3-4). Thus, the interpretation of requests for information rests primarily on simple knowledge tracking-and not on representations of Socratic ignorance-a heuristic that reduces processing costs.

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.

Creating a Corpus of Multilingual Parent-Child Speech Remotely: Lessons Learned in a Large-Scale Onscreen Picturebook Sharing Task

With lockdowns and social distancing measures in place, research teams looking to collect naturalistic parent-child speech interactions have to develop alternatives to in-lab recordings and observational studies with long-stretch recordings. We designed a novel micro-longitudinal study, the Talk Together Study, which allowed us to create a rich corpus of parent-child speech interactions in a fully online environment (N participants = 142, N recordings = 410). In this paper, we discuss the methods we used, and the lessons learned during adapting and running the study. These lessons learned cover nine domains of research design, monitoring and feedback: Recruitment strategies, Surveys and Questionnaires, Video-call scheduling, Speech elicitation tools, Videocall protocols, Participant remuneration strategies, Project monitoring, Participant retention, and Data Quality, and may be used as a primer for teams planning to conduct remote studies in the future.

Remote Research Methods: Considerations for Work With Children

The growing shift to online research provides numerous potential opportunities, including greater sample diversity and more efficient data collection. While online methods and recruitment platforms have gained popularity in research with adults, there is relatively little guidance on best practices for how to conduct remote research with children. The current review discusses how to conduct remote behavioral research with children and adolescents using moderated (i.e., real-time interactions between the experimenter and child) and unmoderated (i.e., independent completion of study without experimenter interaction) methods. We examine considerations regarding sample diversity and provide recommendations on implementing remote research with children, including discussions about remote software, study design, and data quality. These recommendations can promote the use of remote research amongst developmental psychologists by contributing to our knowledge of effective online research practices and helping to build standardized guidelines when working with children.

Graspability Modulates the Stronger Neural Signature of Motor Preparation for Real Objects vs. Pictures

The cognitive and neural bases of visual perception are typically studied using pictures rather than real-world stimuli. Unlike pictures, real objects are actionable solids that can be manipulated with the hands. Recent evidence from human brain imaging suggests that neural responses to real objects differ from responses to pictures; however, little is known about the neural mechanisms that drive these differences. Here, we tested whether brain responses to real objects versus pictures are differentially modulated by the "in-the-moment" graspability of the stimulus. In human dorsal cortex, electroencephalographic responses show a "real object advantage" in the strength and duration of mu (μ) and low beta (β) rhythm desynchronization-well-known neural signatures of visuomotor action planning. We compared desynchronization for real tools versus closely matched pictures of the same objects, when the stimuli were positioned unoccluded versus behind a large transparent barrier that prevented immediate access to the stimuli. We found that, without the barrier in place, real objects elicited stronger μ and β desynchronization compared to pictures, both during stimulus presentation and after stimulus offset, replicating previous findings. Critically, however, with the barrier in place, this real object advantage was attenuated during the period of stimulus presentation, whereas the amplification in later periods remained. These results suggest that the "real object advantage" is driven initially by immediate actionability, whereas later differences perhaps reflect other, more inherent properties of real objects. The findings showcase how the use of richer multidimensional stimuli can provide a more complete and ecologically valid understanding of object vision.

Children's Learning of Non-adjacent Dependencies Using a Web-Based Computer Game Setting

Infants show impressive speech decoding abilities and detect acoustic regularities that highlight the syntactic relations of a language, often coded via non-adjacent dependencies (NADs, e.g., is singing). It has been claimed that infants learn NADs implicitly and associatively through passive listening and that there is a shift from effortless associative learning to a more controlled learning of NADs after the age of 2 years, potentially driven by the maturation of the prefrontal cortex. To investigate if older children are able to learn NADs, Lammertink et al. (2019) recently developed a word-monitoring serial reaction time (SRT) task and could show that 6-11-year-old children learned the NADs, as their reaction times (RTs) increased then they were presented with violated NADs. In the current study we adapted their experimental paradigm and tested NAD learning in a younger group of 52 children between the age of 4-8 years in a remote, web-based, game-like setting (whack-a-mole). Children were exposed to Italian phrases containing NADs and had to monitor the occurrence of a target syllable, which was the second element of the NAD. After exposure, children did a "Stem Completion" task in which they were presented with the first element of the NAD and had to choose the second element of the NAD to complete the stimuli. Our findings show that, despite large variability in the data, children aged 4-8 years are sensitive to NADs; they show the expected differences in r RTs in the SRT task and could transfer the NAD-rule in the Stem Completion task. We discuss these results with respect to the development of NAD dependency learning in childhood and the practical impact and limitations of collecting these data in a web-based setting.

Baby's Online Live Database: An Open Platform for Developmental Science

Efficient data collection in developmental studies is facing challenges due to the decreased birth rates in many regions, reproducibility problems in psychology research, and the COVID-19 pandemic. Here, we propose a novel platform for online developmental science research, the Baby’s Online Live Database (BOLD), which extends the scope of the accessible participant pool, simplifies its management, and enables participant recruitment for longitudinal studies. Through BOLD, researchers can conduct online recruitment of participants preregistered to BOLD simply by specifying their attributes, such as gender and age, and direct the participants to dedicated webpages for each study. Moreover, BOLD handles participant recruitment and reward payment, thereby freeing researchers from the labor of participant management. BOLD also allows researchers the opportunity to access data that were collected from participants in previous research studies. This enables researchers to carry out longitudinal analyses at a relatively low cost. To make BOLD widely accessible, a consortium was formed within the Japan Society of Baby Science, where members from diverse research groups discussed the blueprint of this system. Once in full-scaled operation, BOLD is expected to serve as a platform for various types of online studies and facilitate international collaboration among developmental scientists in the near future.

Online Testing Yields the Same Results as Lab Testing: A Validation Study With the False Belief Task

Recently, online testing has become an increasingly important instrument in developmental research, in particular since the COVID-19 pandemic made in-lab testing impossible. However, online testing comes with two substantial challenges. First, it is unclear how valid results of online studies really are. Second, implementing online studies can be costly and/or require profound coding skills. This article addresses the validity of an online testing approach that is low-cost and easy to implement: The experimenter shares test materials such as videos or presentations via video chat and interactively moderates the test session. To validate this approach, we compared children’s performance on a well-established task, the change-of-location false belief task, in an in-lab and online test setting. In two studies, 3- and 4-year-old received online implementations of the false belief version (Study 1) and the false and true belief version of the task (Study 2). Children’s performance in these online studies was compared to data of matching tasks collected in the context of in-lab studies. Results revealed that the typical developmental pattern of performance in these tasks found in in-lab studies could be replicated with the novel online test procedure. These results suggest that the proposed method, which is both low-cost and easy to implement, provides a valid alternative to classical in-person test settings.

A Tale of Three Platforms: Investigating Preschoolers' Second-Order Inferences Using In-Person, Zoom, and Lookit Methodologies

As a result of the COVID-19 pandemic, online methodologies for developmental research have become an essential norm. Already, there are numerous options for recruiting and testing developmental participants, and they differ from each other in a variety of ways. While recent research has discussed the potential benefits and practical trade-offs of these different platforms, the potential empirical consequences of choosing among them are still unknown. It is critical for the field to understand not only how children's performance in an online context compares to traditional settings, but also how it differs across online platforms. This study offers the first comparative look at the same developmental task across different online research methodologies, allowing for direct comparison and critical examination of each. We conducted three versions of a test of preschoolers' ability to generate and apply second-order inferences to predict novel outcomes. Experiment 1 is an in-person task conducted at public testing sites in the vicinity of the university. In Experiment 2, we conducted an online-moderated version of the same task, in which an experimenter presented a recording of the procedure during a live video call with families over Zoom. Finally, Experiment 3 is an online-unmoderated version of the task, in which the same videos were presented entirely asynchronously using the Lookit platform. Results suggest that online methodologies may introduce difficulties and age-related differences in young children's performance not observed in person. We consider these results in light of the previous online developmental replications, suggest possible interpretations, and offer initial recommendations to help future developmental scientists make informed choices about whether and how to conduct their research online.

Parent-Infant Interaction Tasks Adapted for Remote Testing: Strengths, Challenges, and Recommendations

The closure of in-person laboratories and decreased safety of face-to-face interactions resulting from the COVID-19 pandemic jeopardized the ability of many developmental researchers to continue data collection during this time. Disruptions in data collection are particularly damaging to longitudinal studies, in which the testing of different age groups occurs on a continuous basis, and data loss at one time point can have cascading effects across subsequent time points and threaten the viability of the study. In an effort to continue collecting data for a longitudinal study on emotion development started in-person pre-pandemic, we adapted two parent-infant interaction tasks (free-play task and toy removal task) for a remote testing framework. Our procedure for pivoting these tasks to a supervised, remote online testing framework is outlined and the associated strengths and challenges of testing in this format (e.g., feasibility and implementation, testing environment and task setup validity, and accessibility, recruitment, and diversity) are critically evaluated. Considerations for applying this framework to other behavioral tasks are discussed and recommendations are provided.

A Contactless Method for Measuring Full-Day, Naturalistic Motor Behavior Using Wearable Inertial Sensors

How can researchers best measure infants' motor experiences in the home? Body position-whether infants are held, supine, prone, sitting, or upright-is an important developmental experience. However, the standard way of measuring infant body position, video recording by an experimenter in the home, can only capture short instances, may bias measurements, and conflicts with physical distancing guidelines resulting from the COVID-19 pandemic. Here, we introduce and validate an alternative method that uses machine learning algorithms to classify infants' body position from a set of wearable inertial sensors. A laboratory study of 15 infants demonstrated that the method was sufficiently accurate to measure individual differences in the time that infants spent in each body position. Two case studies showed the feasibility of applying this method to testing infants in the home using a contactless equipment drop-off procedure.

Finding the subitizing in groupitizing: Evidence for parallel subitizing of dots and groups in grouped arrays

‘Groupitizing’ refers to the observation that visually grouped arrays can be accurately enumerated much faster than can unstructured arrays. Previous research suggests that visual grouping allows participants to draw on arithmetic abilities and possibly use mental calculations to enumerate grouped arrays quickly and accurately. Here, we address how subitizing might be involved in finding the operands for mental calculations in grouped dot arrays. We investigated whether participants can use multiple subitizing processes to enumerate both the number of dots and the number of groups in a grouped array. We found that these multiple subitizing processes can take place within 150 ms and that dots and groups seem to be subitized in parallel and with equal priority. Implications for research on mechanisms of groupitizing are discussed.

Advances in Behavioral Remote Data Collection in the Home Setting: Assessing the Mother-Infant Relationship and Infant's Adaptive Behavior via Virtual Visits

Psychological science is struggling with moving forward in the midst of the COVID-19 pandemic, especially due to the halting of behavioral data collection in the laboratory. Safety barriers to assessing psychological behavior in person increased the need for remote data collection in natural settings. In response to these challenges, researchers, including our team, have utilized this time to advance remote behavioral methodology. In this article, we provide an overview of our group’s strategies for remote data collection methodology and examples from our research in collecting behavioral data in the context of psychological functioning. Then, we describe the design and development of our strategies for remote data collection of mother-infant interactions, with the goal being to assess maternal sensitivity and intrusiveness, as well as infants’ adaptive behaviors in several developmental domains. During these virtual visits over Zoom, mother-infant dyads watched a book-reading video and were asked to participate in peek-a-boo, toy play, and toy removal tasks. After the behavioral tasks, a semi-structured interview (Vineland Adaptive Behavior Scale – VABS III) was conducted to assess the infant’s adaptive behavior in communication, socialization, daily living skills, and motor domains. We delineate the specific strategies we applied to integrate laboratory tasks and a semi-structured interview into remote data collection in home settings with mothers and infants. We also elaborate on issues encountered during remote data collection and how we resolved these challenges. Lastly, to inform protocols for future remote data collection, we address considerations and recommendations, as well as benefits and future directions for behavioral researchers in developmental psychology research.

Mini managers: Children strategically divide cognitive labor among collaborators, but with a self-serving bias

Strategic collaboration according to the law of comparative advantage involves dividing tasks based on the relative capabilities of group members. Three experiments (N = 405, primarily White and Asian, 45% female, collected 2016-2019 in Canada) examined how this strategy develops in children when dividing cognitive labor. Children divided questions about numbers between two partners. By 7 years, children allocated difficult questions to the skilled partner (Experiment 1, d = 1.42; Experiment 2, d = 0.87). However, younger children demonstrated a self-serving bias, choosing the easiest questions for themselves. Only when engaging in a third-party collaborative task did 5-year-olds assign harder questions to the more skilled individual (Experiment 3, d = 0.55). These findings demonstrate early understanding of strategic collaboration subject to a self-serving bias.

Predicting Trustworthiness Across Cultures: An Experiment

We contribute to the ongoing debate in the psychological literature on the role of “thin slices” of observable information in predicting others' social behavior, and its generalizability to cross-cultural interactions. We experimentally assess the degree to which subjects, drawn from culturally different populations (France and Japan), are able to predict strangers' trustworthiness based on a set of visual stimuli (mugshot pictures, neutral videos, loaded videos, all recorded in an additional French sample) under varying cultural distance to the target agent in the recording. Our main finding is that cultural distance is not detrimental for predicting trustworthiness in strangers, but that it may affect the perception of different components of communication in social interactions.