The profile of abstract rule learning in infancy: Meta-analytic and experimental evidence

Is core knowledge a natural subdivision of infant cognition?

We examine Spelke's core knowledge taxonomy and test its boundaries. We ask whether Spelke's core knowledge is a distinct type of cognition in the sense that the cognitive processes it includes and excludes are biologically and mechanically coherent.

The developmental cognitive mechanism of learning algebraic rules from the dual-process theory perspective

Rule learning is an important ability that enables human beings to adapt to nature and develop civilizations. There have been many discussions on the mechanism and characteristics of algebraic rule learning, but there are still controversies due to the lack of theoretical guidance. Based on the dual-process theory, this study discussed the following arguments for algebraic rule learning across human and animal studies: whether algebraic rule learning is simply Type 1 processing, whether algebraic rule learning is a domain-general ability, whether algebraic rule learning is shared by humans and animals, and whether an algebraic rule is learned consciously. Moreover, we propose that algebraic rule learning is possibly a cognitive process that combines both Type 1 and Type 2 processing. Further exploration is required to establish the essence and neural basis of algebraic rule learning.

Individual differences in auditory perception predict learning of non-adjacent tone sequences in 3-year-olds

Auditory processing of speech and non-speech stimuli oftentimes involves the analysis and acquisition of non-adjacent sound patterns. Previous studies using speech material have demonstrated (i) children's early emerging ability to extract non-adjacent dependencies (NADs) and (ii) a relation between basic auditory perception and this ability. Yet, it is currently unclear whether children show similar sensitivities and similar perceptual influences for NADs in the non-linguistic domain. We conducted an event-related potential study with 3-year-old children using a sine-tone-based oddball task, which simultaneously tested for NAD learning and auditory perception by means of varying sound intensity. Standard stimuli were A × B sine-tone sequences, in which specific A elements predicted specific B elements after variable × elements. NAD deviants violated the dependency between A and B and intensity deviants were reduced in amplitude. Both elicited similar frontally distributed positivities, suggesting successful deviant detection. Crucially, there was a predictive relationship between the amplitude of the sound intensity discrimination effect and the amplitude of the NAD learning effect. These results are taken as evidence that NAD learning in the non-linguistic domain is functional in 3-year-olds and that basic auditory processes are related to the learning of higher-order auditory regularities also outside the linguistic domain.

Brain responses to repetition-based rule-learning do not exhibit sex differences: an aggregated analysis of infant fNIRS studies

Studies have repeatedly shown sex differences in some areas of language development, typically with an advantage for female over male children. However, the tested samples are typically small and the effects do not always replicate. Here, we used a meta-analytic approach to address this issue in a larger sample, combining seven fNIRS studies on the neural correlates of repetition- and non-repetition-based rule learning in newborns and 6-month-old infants. The ability to extract structural regularities from the speech input is fundamental for language development, it is therefore highly relevant to understand whether this ability shows sex differences. The meta-analysis tested the effect of Sex, as well as of other moderators on infants' hemodynamic responses to repetition-based (e.g. ABB: "mubaba") and non-repetition-based (e.g. ABC: "mubage") sequences in both anatomically and functionally defined regions of interests. Our analyses did not reveal any sex differences at birth or at 6 months, suggesting that the ability to encode these regularities is robust across sexes. Interestingly, the meta-analysis revealed other moderator effects. Thus in newborns, we found a greater involvement of the bilateral temporal areas compared to the frontal areas for both repetition and non-repetition sequences. Further, non-repetition sequences elicited greater responses in 6-month-olds than in newborns, especially in the bilateral frontal areas. When analyzing functional clusters of HbR timetraces, we found that a larger right-left asymmetry for newborn boys in brain responses compared to girls, which may be interpreted in terms of a larger right-left asymmetry in cerebral blood flow in boys than in girls early in life. We conclude that extracting repetition-based regularities from speech is a robust ability with a well-defined neural substrate present from birth and it does not exhibit sex differences.

Of words and whistles: Statistical learning operates similarly for identical sounds perceived as speech and non-speech

Statistical learning is an ability that allows individuals to effortlessly extract patterns from the environment, such as sound patterns in speech. Some prior evidence suggests that statistical learning operates more robustly for speech compared to non-speech stimuli, supporting the idea that humans are predisposed to learn language. However, any apparent statistical learning advantage for speech could be driven by signal acoustics, rather than the subjective perception per se of sounds as speech. To resolve this issue, the current study assessed whether there is a statistical learning advantage for ambiguous sounds that are subjectively perceived as speech-like compared to the same sounds perceived as non-speech, thereby controlling for acoustic features. We first induced participants to perceive sine-wave speech (SWS)-a degraded form of speech not immediately perceptible as speech-as either speech or non-speech. After this induction phase, participants were exposed to a continuous stream of repeating trisyllabic nonsense words, composed of SWS syllables, and then completed an explicit familiarity rating task and an implicit target detection task to assess learning. Critically, participants showed robust and equivalent performance on both measures, regardless of their subjective speech perception. In contrast, participants who perceived the SWS syllables as more speech-like showed better detection of individual syllables embedded in speech streams. These results suggest that speech perception facilitates processing of individual sounds, but not the ability to extract patterns across sounds. Our findings suggest that statistical learning is not influenced by the perceived linguistic relevance of sounds, and that it may be conceptualized largely as an automatic, stimulus-driven mechanism.

Exploring Abstract Pattern Representation in The Brain and Non-symbolic Neural Networks

Human cognitive and linguistic generativity depends on the ability to identify abstract relationships between perceptually dissimilar items. Marcus et al. (1999) found that human infants can rapidly discover and generalize patterns of syllable repetition (reduplication) that depend on the abstract property of identity, but simple recurrent neural networks (SRNs) could not. They interpreted these results as evidence that purely associative neural network models provide an inadequate framework for characterizing the fundamental generativity of human cognition. Here, we present a series of deep long short-term memory (LSTM) models that identify abstract syllable repetition patterns and words based on training with cochleagrams that represent auditory stimuli. We demonstrate that models trained to identify individual syllable trigram words and models trained to identify reduplication patterns discover representations that support classification of abstract repetition patterns. Simulations examined the effects of training categories (words vs. patterns) and pretraining to identify syllables, on the development of hidden node representations that support repetition pattern discrimination. Representational similarity analyses (RSA) comparing patterns of regional brain activity based on MRI-constrained MEG/EEG data to patterns of hidden node activation elicited by the same stimuli showed a significant correlation between brain activity localized in primarily posterior temporal regions and representations discovered by the models. These results suggest that associative mechanisms operating over discoverable representations that capture abstract stimulus properties account for a critical example of human cognitive generativity.

The language-of-thought as a working hypothesis for developmental cognitive science

A science of prelinguistic infant cognition must take seriously the language-of-thought (LoT) hypothesis. I show how the LoT framework enables us to identify the representational and computational capacities of infant minds and the developmental factors that act on these capacities, and explain how Quilty-Dunn et al.'s take on LoT has important upshots for developmental theory-building.

Dynamic Motion and Human Agents Facilitate Visual Nonadjacent Dependency Learning

Many events that humans and other species experience contain regularities in which certain elements within an event predict certain others. While some of these regularities involve tracking the co-occurrences between temporally adjacent stimuli, others involve tracking the co-occurrences between temporally distant stimuli (i.e., nonadjacent dependencies, NADs). Prior research shows robust learning of adjacent dependencies in humans and other species, whereas learning NADs is more difficult, and often requires support from properties of the stimulus to help learners notice the NADs. Here, we report on seven experiments that examined NAD learning from various types of visual stimuli, exploring the effects of dynamic motion on adults' NAD learning from visual sequences involving human and nonhuman agents. We tested adults' NAD learning from visual sequences of human actions, object transformations, static images of human postures, and static images of an object in different postures. We found that dynamic motion aids the acquisition of NADs. We also found that learning NADs in sequences involving human agents is more robust compared to sequences involving nonhuman objects. We propose that dynamic motion and human agents both independently result in richer representations that provide a stronger signal for NAD learning.

Six-month-old infants' perception of structural regularities in speech

In order to acquire grammar, infants need to extract regularities from the linguistic input. From birth, infants can detect regularities in speech based on identity relations, and show strong neural activation to syllable sequences containing adjacent repetitions of identical syllables (e.g. ABB: mubaba). Meanwhile, newborns' neural responses to sequences of different syllables (e.g. ABC: mubage, i.e. diversity-based relations) do not differ from baseline. However, this latter ability needs to emerge during development, as most linguistic units, such as words, are composed of highly variable sequences. As infants begin to learn their first word forms at 6 months, we hypothesize that the ability to represent sequences of different syllables might become important for them at this age. Using near-infrared spectroscopy (NIRS), we measured 6-month-old infants' brain responses to repetition- and diversity-based sequences in the bilateral temporal, parietal and frontal areas. We found that 6-month-olds discriminated the repetition- and diversity-based structures in frontal and parietal regions, and exhibited equally strong activation to both grammars as compared to baseline. These results show that by 6 months of age, infants encode sequences with diversity-based structures. They thus provide the earliest evidence that prelexical infants represent difference in speech stimuli, which behavioral studies first attest at 11 months of age.

Reproducibility of infant fNIRS studies: a meta-analytic approach

SIGNIFICANCE

Concerns about the reproducibility of experimental findings have recently emerged in many disciplines, from psychology to medicine and neuroscience. As NIRS is a relatively recent brain imaging technique, the question of reproducibility has not yet been systematically addressed.

AIM

The current study seeks to test the replicability of effects observed in NIRS experiments assessing young infants' rule-learning ability.

APPROACH

We conducted meta-analyses and mixed-effects modeling-based inferential statistics to determine whether effect sizes were replicable and comparable in a sample of 23 NIRS studies investigating infants' abilities to process repetition- and diversity-based regularities in linguistic and nonlinguistic auditory and visual sequences. Additionally, we tested whether effect sizes were modulated by different factors such as the age of participants or the laboratory. We obtained NIRS data from 12 published and 11 unpublished studies. The 23 studies involved a total of 487 infants, aged between 0 and 9 months, tested in four different countries (Canada, France, Italy, and USA).

RESULTS

Our most important finding is that study and laboratory were never significant moderators of variation in effect sizes, indicating that results replicated reliably across the different studies and labs included in the sample. We observed small-to-moderate effect sizes, similar to effect sizes found with other neuroimaging and behavioral techniques in the developmental literature. In line with existing findings, effect sizes were modulated by the participants' age and differed across the different regularities tested, with repetition-based regularities giving rise to the strongest effects; in particular, the overall magnitude of this effect in the left temporal region was 0.27 when analyzing the entire dataset.

CONCLUSIONS

Meta-analysis is a useful tool for assessing replicability and cross-study variability. Here, we have shown that infant NIRS studies in the language domain replicate robustly across various NIRS machines, testing sites, and developmental populations.

Robustness of the rule-learning effect in 7-month-old infants: A close, multicenter replication of Marcus et al. (1999)

We conducted a close replication of the seminal work by Marcus and colleagues from 1999, which showed that after a brief auditory exposure phase, 7-month-old infants were able to learn and generalize a rule to novel syllables not previously present in the exposure phase. This work became the foundation for the theoretical framework by which we assume that infants are able to learn abstract representations and generalize linguistic rules. While some extensions on the original work have shown evidence of rule learning, the outcomes are mixed, and an exact replication of Marcus et al.'s study has thus far not been reported. A recent meta-analysis by Rabagliati and colleagues brings to light that the rule-learning effect depends on stimulus type (e.g., meaningfulness, speech vs. nonspeech) and is not as robust as often assumed. In light of the theoretical importance of the issue at stake, it is appropriate and necessary to assess the replicability and robustness of Marcus et al.'s findings. Here we have undertaken a replication across four labs with a large sample of 7-month-old infants (N = 96), using the same exposure patterns (ABA and ABB), methodology (Headturn Preference Paradigm), and original stimuli. As in the original study, we tested the hypothesis that infants are able to learn abstract "algebraic" rules and apply them to novel input. Our results did not replicate the original findings: infants showed no difference in looking time between test patterns consistent or inconsistent with the familiarization pattern they were exposed to.

Learning and generalization of repetition-based rules in autism

Rule Learning (RL) allows us to extract and generalize high-order rules from a sequence of elements. Despite the critical role of RL in the acquisition of linguistic and social abilities, no study has investigated RL processes in Autism Spectrum Disorder (ASD). Here, we investigated RL in high-functioning autistic adolescents with ASD, examining whether their ability to extract and generalize rules from a sequence of visual elements is affected by the social vs. non-social nature of the stimulus and by visual working memory (WM). Using a forced-choice paradigm, ASD adolescents and typically developing (TD) peers were tested for their ability to detect and generalize high-order, repetition-based rules from visual sequences of simple non-social stimuli (shapes), complex non-social stimuli (inverted faces), and social stimuli (upright face). Both ASD and TD adolescents were able to generalize the rule they had learned to new stimuli, and their ability was modulated by the social nature of the stimuli and the complexity of the rule. Moreover, an association between RL and WM was found in the ASD, but not TD group, suggesting that ASD might have used additional or alternative strategies that relied on visual WM resources.

Abstract representations of small sets in newborns

From the very first days of life, newborns are not tied to represent narrow, modality- and object-specific aspects of their environment. Rather, they sometimes react to abstract properties shared by stimuli of very different nature, such as approximate numerosity or magnitude. As of now, however, there is no evidence that newborns possess abstract representations that apply to small sets: in particular, while newborns can match large approximate numerosities across senses, this ability does not extend to small numerosities. In two experiments, we presented newborn infants (N = 64, age 17 to 98 h) with patterned sets AB or ABB simultaneously in the auditory and visual modalities. Auditory patterns were presented as periodic sequences of sounds (AB: triangle-drum-triangle-drum-triangle-drum …; ABB: triangle-drum-drum-triangle-drum-drum-triangle-drum-drum …), and visual patterns as arrays of 2 or 3 shapes (AB: circle-diamond; ABB: circle-diamond-diamond). In both experiments, we found that participants reacted and looked longer when the patterns matched across the auditory and visual modalities – provided that the first stimulus they received was congruent. These findings uncover the existence of yet another type of abstract representations at birth, applying to small sets. As such, they bolster the hypothesis that newborns are endowed with the capacity to represent their environment in broad strokes, in terms of its most abstract properties. This capacity for abstraction could later serve as a scaffold for infants to learn about the particular entities surrounding them.

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Newborns were presented with auditory and visual patterns (AB vs. ABB).

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Participants reacted when the patterns presented were congruent across modalities.

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Newborns possess abstract representations applying to small sets.

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These representations may encode numerosity and/or repetitions.

Statistical Learning in Vision

Vision and learning have long been considered to be two areas of research linked only distantly. However, recent developments in vision research have changed the conceptual definition of vision from a signal-evaluating process to a goal-oriented interpreting process, and this shift binds learning, together with the resulting internal representations, intimately to vision. In this review, we consider various types of learning (perceptual, statistical, and rule/abstract) associated with vision in the past decades and argue that they represent differently specialized versions of the fundamental learning process, which must be captured in its entirety when applied to complex visual processes. We show why the generalized version of statistical learning can provide the appropriate setup for such a unified treatment of learning in vision, what computational framework best accommodates this kind of statistical learning, and what plausible neural scheme could feasibly implement this framework. Finally, we list the challenges that the field of statistical learning faces in fulfilling the promise of being the right vehicle for advancing our understanding of vision in its entirety. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Ten easy steps to conducting transparent, reproducible meta-analyses for infant researchers

Meta-analyses provide researchers with an overview of the body of evidence in a topic, with quantified estimates of effect sizes and the role of moderators, and weighting studies according to their precision. We provide a guide for conducting a transparent and reproducible meta-analysis in the field of developmental psychology within the framework of the MetaLab platform, in 10 steps: (1) Choose a topic for your meta-analysis, (2) Formulate your research question and specify inclusion criteria, (3) Preregister and document all stages of your meta-analysis, (4) Conduct the literature search, (5) Collect and screen records, (6) Extract data from eligible studies, (7) Read the data into analysis software and compute effect sizes, (8) Visualize your data, (9) Create meta-analytic models to assess the strength of the effect and investigate possible moderators, (10) Write up and promote your meta-analysis. Meta-analyses can inform future studies, through power calculations, by identifying robust methods and exposing research gaps. By adding a new meta-analysis to MetaLab, datasets across multiple topics of developmental psychology can be synthesized, and the dataset can be maintained as a living, community-augmented meta-analysis to which researchers add new data, allowing for a cumulative approach to evidence synthesis.

Children's value-based decision making

To effectively navigate their environments, infants and children learn how to recognize events predict salient outcomes, such as rewards or punishments. Relatively little is known about how children acquire this ability to attach value to the stimuli they encounter. Studies often examine children’s ability to learn about rewards and threats using either classical conditioning or behavioral choice paradigms. Here, we assess both approaches and find that they yield different outcomes in terms of which individuals had efficiently learned the value of information presented to them. The findings offer new insights into understanding how to assess different facets of value learning in children.

Infants differentially extract rules from language

Infants readily extract linguistic rules from speech. Here, we ask whether this advantage extends to linguistic stimuli that do not rely on the spoken modality. To address this question, we first examine whether infants can differentially learn rules from linguistic signs. We show that, despite having no previous experience with a sign language, six-month-old infants can extract the reduplicative rule (AA) from dynamic linguistic signs, and the neural response to reduplicative linguistic signs differs from reduplicative visual controls, matched for the dynamic spatiotemporal properties of signs. We next demonstrate that the brain response for reduplicative signs is similar to the response to reduplicative speech stimuli. Rule learning, then, apparently depends on the linguistic status of the stimulus, not its sensory modality. These results suggest that infants are language-ready. They possess a powerful rule system that is differentially engaged by all linguistic stimuli, speech or sign.

Quantifying the syntactic bootstrapping effect in verb learning: A meta-analytic synthesis

How do children infer the meaning of a novel verb? One prominent proposal is that children rely on syntactic information in the linguistic context, a phenomenon known as "syntactic bootstrapping". For example, given the sentence "The bunny is gorping the duck," a child could use knowledge of English syntactic roles to infer that "gorping" refers to an action where the bunny is acting in some way on a duck. Here, we examine the strength of the syntactic bootstrapping effect, its developmental trajectory and generalizability using meta-analytic methods. Across 60 experiments in the literature (N = 849 participants), we find a reliable syntactic bootstrapping effect (d = 0.24). Yet, despite its theoretical prominence, the syntactic bootstrapping effect is relatively small, comparable in size to cross-situational learning and sound symbolism, but smaller than mutual-exclusivity and gaze-following. Further, we find that the effect does not strengthen over development, and is present only for studies that use transitive sentences. An examination of a range of methodological factors suggests that the effect is not strongly influenced by methodological implementation. In the General Discussion, we consider implications of our findings for theories of verb learning and make recommendations for future research.

Space modulates cross-domain transfer of abstract rules in infants

Developmental studies have shown that infants exploit ordinal information to extract and generalize repetition-based rules from a sequence of items. Within the visual modality, this ability is constrained by the spatial layout within which items are delivered given that a left-to-right orientation boosts infants' rule learning, whereas a right-to-left orientation hinders this ability. Infants' rule learning operates across different domains and can also be transferred across modalities when learning is triggered by speech. However, no studies have investigated whether the transfer of rule learning occurs across different domains when language is not involved. Using a visual habituation procedure, we tested 7-month-old infants' ability to extract rule-like patterns from numerical sequences and generalize them to non-numerical sequences of visual shapes and whether this ability is affected by the spatial orientation. Infants were first habituated to left-to-right or right-to-left oriented numerical sequences instantiating an ABB rule and were then tested with the familiar rule instantiated across sequences of single geometrical shapes and a novel (ABA) rule. Results showed a transfer of learning from number to visual shapes for left-to-right oriented sequences but not for right-to-left oriented ones (Experiment 1) even when the direction of the numerical change (increasing vs. decreasing) within the habituation sequences violated a small-left/large-right number-space association (Experiment 2). These results provide the first demonstration that visual rule learning mechanisms in infancy operate at a high level of abstraction and confirm earlier findings that left-to-right oriented directional cues facilitate infants' representation of order.

Learning non-adjacent rules and non-adjacent dependencies from human actions in 9-month-old infants

Seven month old infants can learn simple repetition patterns, such as we-fo-we, and generalize the rules to sequences of new syllables, such as ga-ti-ga. However, repetition rule learning in visual sequences seems more challenging, leading some researchers to claim that this type of rule learning applies preferentially to communicative stimuli. Here we demonstrate that 9-month-old infants can learn repetition rules in sequences of non-communicative dynamic human actions. We also show that when primed with these non-adjacent repetition patterns, infants can learn non-adjacent dependencies that involve memorizing the dependencies between specific human actions-patterns that prior research has shown to be difficult for infants in the visual domain and in speech. We discuss several possible mechanisms that account for the apparent advantage stimuli involving human action sequences has over other kinds of stimuli in supporting non-adjacent dependency learning. We also discuss possible implications for theories of language acquisition.

Quantifying the role of rhythm in infants' language discrimination abilities: A meta-analysis

More than 30 years have passed since Mehler et al. (1988) proposed that newborns can discriminate between languages that belong to different rhythm classes: stress-, syllable- or mora-timed. Thereupon they developed the hypothesis that infants are sensitive to differences in vowel and consonant interval durations as acoustic correlates of rhythm classes. It remains unknown exactly which durational computations infants use when perceiving speech for the purposes of distinguishing languages. Here, a meta-analysis of studies on infants' language discrimination skills over the first year of life was conducted, aiming to quantify how language discrimination skills change with age and are modulated by rhythm classes or durational metrics. A systematic literature search identified 42 studies that tested infants' (birth to 12 months) discrimination or preference of two language varieties, by presenting infants with auditory or audio-visual continuous speech. Quantitative data synthesis was conducted using multivariate random effects meta-analytic models with the factors rhythm class difference, age, stimulus manipulation, method, and metrics operationalising proportions of and variability in vowel and consonant interval durations, to explore which factors best account for language discrimination or preference. Results revealed that smaller differences in vowel interval variability (△V) and larger differences in successive consonantal interval variability (rPVI-C) were associated with more successful language discrimination, and better accounted for discrimination results than the factor rhythm class. There were no effects of age for discrimination but results on preference studies were affected by age: the older infants get, the more they prefer non-native languages that are rhythmically similar to their native language, but not non-native languages that are rhythmically distinct. These findings can inform theories on language discrimination that have previously focussed on rhythm class, by providing a novel way to operationalise rhythm in language in the extent to which it accounts for infants' language discrimination abilities.

Rule learning transfer across linguistic and visual modalities in 7-month-old infants

Rule learning (RL) refers to infants' ability to extract high-order, repetition-based rules from a sequence of elements and to generalize them to new items. RL has been demonstrated in both the auditory and the visual modality, but no studies have investigated infants' transfer of learning across these two modalities, a process that is fundamental for the development of many complex cognitive skills. Using a visual habituation procedure within a cross-modal RL task, we tested 7-month-old infants' transfer of learning both from speech to vision (auditory-visual-AV-condition) and from vision to speech (visual-auditory-VA-condition). Results showed a transfer of learning in the AV condition, but only for those infants who were able to efficiently extract the rule during the learning (habituation) phase. In contrast, in the VA condition infants provided no evidence of RL. Overall, this study indicates that 7-month-old infants can transfers high-order rules across modalities with an advantage for transferring from speech to vision, and that this ability is constrained by infants' individual differences in the way they process the to-be-learned rules.

Estimating publication bias in meta-analyses of peer-reviewed studies: A meta-meta-analysis across disciplines and journal tiers

Selective publication and reporting in individual papers compromise the scientific record, but are meta-analyses as compromised as their constituent studies? We systematically sampled 63 meta-analyses (each comprising at least 40 studies) in PLoS One, top medical journals, top psychology journals, and Metalab, an online, open-data database of developmental psychology meta-analyses. We empirically estimated publication bias in each, including only the peer-reviewed studies. Across all meta-analyses, we estimated that "statistically significant" results in the expected direction were only 1.17 times more likely to be published than "nonsignificant" results or those in the unexpected direction (95% CI: [0.93, 1.47]), with a confidence interval substantially overlapping the null. Comparable estimates were 0.83 for meta-analyses in PLoS One, 1.02 for top medical journals, 1.54 for top psychology journals, and 4.70 for Metalab. The severity of publication bias did differ across individual meta-analyses; in a small minority (10%; 95% CI: [2%, 21%]), publication bias appeared to favor "significant" results in the expected direction by more than threefold. We estimated that for 89% of meta-analyses, the amount of publication bias that would be required to attenuate the point estimate to the null exceeded the amount of publication bias estimated to be actually present in the vast majority of meta-analyses from the relevant scientific discipline (exceeding the 95th percentile of publication bias). Study-level measures ("statistical significance" with a point estimate in the expected direction and point estimate size) did not indicate more publication bias in higher-tier versus lower-tier journals, nor in the earliest studies published on a topic versus later studies. Overall, we conclude that the mere act of performing a meta-analysis with a large number of studies (at least 40) and that includes non-headline results may largely mitigate publication bias in meta-analyses, suggesting optimism about the validity of meta-analytic results.

Experience with research paradigms relates to infants' direction of preference

Interpreting and predicting direction of preference in infant research has been a thorny issue for decades. Several factors have been proposed to account for familiarity versus novelty preferences, including age, length of exposure, and task complexity. The current study explores an additional dimension: experience with the experimental paradigm. We reanalyzed the data from 4 experiments on artificial grammar learning in 12-month-old infants run using the head-turn preference procedure (HPP). Participants in these studies varied substantially in their number of laboratory visits. Results show that the number of HPP studies is related to direction of preference: Infants with limited experience with the HPP setting were more likely to show familiarity preferences than infants who had amassed more experience with this paradigm. This evidence has important implications for the interpretation of experimental results: Experience with a given method or, more broadly, with the laboratory environment may affect infants' patterns of preferences.

The development of infants' responses to mispronunciations: A meta-analysis

As they develop into mature speakers of their native language, infants must not only learn words but also the sounds that make up those words. To do so, they must strike a balance between accepting speaker-dependent variation (e.g., mood, voice, accent) but appropriately rejecting variation when it (potentially) changes a word's meaning (e.g., cat vs. hat). This meta-analysis focuses on studies investigating infants' ability to detect mispronunciations in familiar words, or mispronunciation sensitivity. Our goal was to evaluate the development of infants' phonological representations for familiar words as well as explore the role of experimental manipulations related to theoretical questions and of analysis choices. The results show that although infants are sensitive to mispronunciations, they still accept these altered forms as labels for target objects. Interestingly, this ability is not modulated by age or vocabulary size, suggesting that a mature understanding of native language phonology may be present in infants from an early age, possibly before the vocabulary explosion. These results support several theoretical assumptions made in the literature, such as sensitivity to mispronunciation size and position of the mispronunciation. We also shed light on the impact of data analysis choices that may lead to different conclusions regarding the development of infants' mispronunciation sensitivity. Our article concludes with recommendations for improved practice in testing infants' word and sentence processing online. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Specificity of representations in infants' visual statistical learning

Past work has demonstrated infants' robust statistical learning across visual and auditory modalities. However, the specificity of representations produced via visual statistical learning has not been fully explored. The current study addressed this by investigating infants' abilities to identify previously learned object sequences when some object features (e.g., shape, face) aligned with prior learning and other features did not. Experiment 1 replicated past work demonstrating that infants can learn statistical regularities across sequentially presented objects and extended this finding to 16-month-olds. In Experiment 2, infants viewed test sequences in which one object feature (e.g., face) had been removed but the other feature (e.g., shape) was maintained, resulting in failure to identify familiar sequences. We further probed learning specificity by assessing infants' recognition of sequences when one feature was altered rather than removed (Experiment 3) and when one feature was uncorrelated with the original sequence structure (Experiment 4). In both cases, infants failed to identify sequences in which object features were not identical between learning and test. These findings suggest that infants are limited in their ability to generalize the statistical structure of an object sequence when the objects' features do not align between learning and test.

Addressing Publication Bias in Meta-Analysis

Abstract. Meta-analyses are an indispensable research synthesis tool for characterizing bodies of literature and advancing theories. One important open question concerns the inclusion of unpublished data into meta-analyses. Finding such studies can be effortful, but their exclusion potentially leads to consequential biases like overestimation of a literature’s mean effect. We address two questions about unpublished data using MetaLab, a collection of community-augmented meta-analyses focused on developmental psychology. First, we assess to what extent MetaLab datasets include gray literature, and by what search strategies they are unearthed. We find that an average of 11% of datapoints are from unpublished literature; standard search strategies like database searches, complemented with individualized approaches like including authors’ own data, contribute the majority of this literature. Second, we analyze the effect of including versus excluding unpublished literature on estimates of effect size and publication bias, and find this decision does not affect outcomes. We discuss lessons learned and implications.

A Simple, Biologically Plausible Feature Detector for Language Acquisition

Language has a complex grammatical system we still have to understand computationally and biologically. However, some evolutionarily ancient mechanisms have been repurposed for grammar so that we can use insight from other taxa into possible circuit-level mechanisms of grammar. Drawing upon recent evidence for the importance of disinhibitory circuits across taxa and brain regions, I suggest a simple circuit that explains the acquisition of core grammatical rules used in 85% of the world's languages: grammatical rules based on sameness/difference relations. This circuit acts as a sameness detector. “Different” items are suppressed through inhibition, but presenting two “identical” items leads to inhibition of inhibition. The items are thus propagated for further processing. This sameness detector thus acts as a feature detector for a grammatical rule. I suggest that having a set of feature detectors for elementary grammatical rules might make language acquisition feasible based on relatively simple computational mechanisms.

Infants' Learning of Rule-Based Visual Sequences Predicts Language Outcome at 2 Years

The ability to learn and generalize abstract rules from sensory input - i.e., Rule Learning (RL) - is seen as pivotal to language development, and specifically to the acquisition of the grammatical structure of language. Although many studies have shown that RL in infancy is operating across different perceptual domains, including vision, no studies have directly investigated the link between infants' visual RL and later language acquisition. Here, we conducted a longitudinal study to investigate whether 7-month-olds' ability to detect visual structural regularities predicts linguistic outcome at 2 years of age. At 7 months, infants were tested for their ability to extract and generalize ABB and ABA structures from sequences of visual shapes, and at 24 months their lexical and grammatical skills were assessed using the MacArthur-Bates CDI. Regression analyses showed that infants' visual RL abilities selectively predicted early grammatical abilities, but not lexical abilities. These results may provide the first evidence that RL mechanisms are involved in language acquisition, and suggest that RL abilities may act as an early neurocognitive marker for language impairments.

Statistical Learning, Implicit Learning, and First Language Acquisition: A Critical Evaluation of Two Developmental Predictions

The role of distributional information in language learning, and learning more generally, has been studied extensively in both the statistical learning and the implicit learning literatures. Despite the similarity in research questions, the two literatures have remained largely separate. Here, we draw on findings from the two traditions to critically evaluate two developmental predictions that are central to both. The first is the question of age invariance: Does learning improve during development or is it fully developed in infancy? The combined findings suggest that both implicit and statistical learning improve during childhood, contra the age invariance prediction. This raises questions about the role of implicit statistical learning (ISL) in explaining the age-related deterioration in language learning: Children's better language learning abilities cannot be attributed to their improved distributional learning skills. The second issue we examine is the predictive relation to language outcomes: Does variation in learning predict variation in language outcomes? While there is evidence for such links, there is concern in both research traditions about the reliability of the tasks used with children. We present data suggesting that commonly used statistical learning measures may not capture stable individual differences in children, undermining their utility for assessing the link to language outcomes in developmental samples. The evaluation of both predictions highlights the empirical parallels between the implicit and statistical learning literatures, and the need to better integrate their developmental investigation. We go on to discuss several of the open challenges facing the study of ISL during development.

Infants' selective use of reliable cues in multidimensional language input

Learning always happens from input that contains multiple structures and multiple sources of variability. Though infants possess learning mechanisms to locate structure in the world, lab-based experiments have rarely probed how infants contend with input that contains many different structures and cues. Two experiments explored infants' use of two naturally occurring sources of variability-different sounds and different people-to detect regularities in language. Monolingual infants (9-10 months) heard a male and female talker produce two different speech streams, one of which followed a deterministic pattern (e.g., AAB, le-le-di) and one of which did not. For half of the infants, each speaker produced only one of the streams; for the other half of the infants, each speaker produced 50% of each stream. In Experiment 1, each stream consisted of distinct sounds, and infants successfully demonstrated learning regardless of the correspondence between speaker and stream. In Experiment 2, each stream consisted of the same sounds, and infants failed to show learning, even when speakers provided a perfect cue for separating each stream. Thus, monolingual infants can learn in the presence of multiple speech streams, but these experiments suggest that infants may rely more on sound-based rather than speaker-based distinctions when breaking into the structure of incoming information. This selective use of some cues over others highlights infants' ability to adaptively focus on distinctions that are most likely to be useful as they sort through their inherently multidimensional surroundings. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The profile of abstract rule learning in infancy: Meta-analytic and experimental evidence

Everyone agrees that infants possess general mechanisms for learning about the world, but the existence and operation of more specialized mechanisms is controversial. One mechanism-rule learning-has been proposed as potentially specific to speech, based on findings that 7-month-olds can learn abstract repetition rules from spoken syllables (e.g. ABB patterns: wo-fe-fe, ga-tu-tu…) but not from closely matched stimuli, such as tones. Subsequent work has shown that learning of abstract patterns is not simply specific to speech. However, we still lack a parsimonious explanation to tie together the diverse, messy, and occasionally contradictory findings in that literature. We took two routes to creating a new profile of rule learning: meta-analysis of 20 prior reports on infants' learning of abstract repetition rules (including 1,318 infants in 63 experiments total), and an experiment on learning of such rules from a natural, non-speech communicative signal. These complementary approaches revealed that infants were most likely to learn abstract patterns from meaningful stimuli. We argue that the ability to detect and generalize simple patterns supports learning across domains in infancy but chiefly when the signal is meaningfully relevant to infants' experience with sounds, objects, language, and people.