Verb Vocabulary Supports Event Probability Use in Developmental Language Disorder.

PURPOSE: Children with developmental language disorder (DLD) tend to interpret noncanonical sentences like passives using event probability (EP) information regardless of structure (e.g., by interpreting "The dog was chased by the squirrel" as "The dog chased the squirrel"). Verbs are a major source of EP information in adults and children with typical development (TD), who know that "chase" implies an unequal relationship among participants. Individuals with DLD have poor verb knowledge and verb-based sentence processing. Yet, they also appear to rely more on EP information than their peers. This paradox raises two questions: (a) How do children with DLD use verb-based EP information alongside other information in online passive sentence interpretation? (b) How does verb vocabulary knowledge support EP information use? METHOD: We created novel EP biases by showing animations of agents with consistent action tendencies (e.g., clumsy vs. helpful actions). We then used eye tracking to examine how this EP information was used during online passive sentence processing. Participants were 4- to 5-year-old children with DLD (n = 20) and same-age peers with TD (n = 20). RESULTS: In Experiment 1, children with DLD quickly integrated verb-based EP information with morphosyntax close to the verb but failed to do so with distant morphosyntax. In Experiment 2, the quality of children's sentence-specific verb vocabulary knowledge was positively associated with the use of EP information in both groups. CONCLUSION: Depending on the morphosyntactic context, children with DLD and TD used EP information differently, but verb vocabulary knowledge aided its use. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25491805.

Touch to learn: Multisensory input supports word learning and processing.

Infants experience language in rich multisensory environments. For example, they may first be exposed to the word applesauce while touching, tasting, smelling, and seeing applesauce. In three experiments using different methods we asked whether the number of distinct senses linked with the semantic features of objects would impact word recognition and learning. Specifically, in Experiment 1 we asked whether words linked with more multisensory experiences were learned earlier than words linked fewer multisensory experiences. In Experiment 2, we asked whether 2-year-olds' known words linked with more multisensory experiences were better recognized than those linked with fewer. Finally, in Experiment 3, we taught 2-year-olds labels for novel objects that were linked with either just visual or visual and tactile experiences and asked whether this impacted their ability to learn the new label-to-object mappings. Results converge to support an account in which richer multisensory experiences better support word learning. We discuss two pathways through which rich multisensory experiences might support word learning.

Feats: A database of semantic features for early produced noun concepts.

Semantic feature production norms have several desirable characteristics that have supported models of representation and processing in adults. However, several key challenges have limited the use of semantic feature norms in studies of early language acquisition. First, existing norms provide uneven and inconsistent coverage of early-acquired concepts that are typically produced and assessed in children under the age of three, which is a time of tremendous growth of early vocabulary skills. Second, it is difficult to assess the degree to which young children may be familiar with normed features derived from these adult-generated datasets. Third, it has been difficult to adopt standard methods to generate semantic network models of early noun learning. Here, we introduce Feats-a tool that was designed to make headway on these challenges by providing a database, the Language Learning and Meaning Acquisition (LLaMA) lab Noun Norms that extends a widely used set of feature norms McRae et al. Behavior Research Methods 37, 547-559, (2005) to include full coverage of noun concepts on a commonly used early vocabulary assessment. Feats includes several tools to facilitate exploration of features comprising early-acquired nouns, assess the developmental appropriateness of individual features using toddler-accessibility norms, and extract semantic network statistics for individual vocabulary profiles. We provide a tutorial overview of Feats. We additionally validate our approach by presenting an analysis of an overlapping set of concepts collected across prior and new data collection methods. Furthermore, using network graph analyses, we show that the extended set of norms provides novel, reliable results given their enhanced coverage.

Two pathways in vocabulary development: Large-scale differences in noun and verb semantic structure.

In adults, nouns and verbs have varied and multilevel semantic interrelationships. In children, evidence suggests that nouns and verbs also have semantic interrelationships, though the timing of the emergence of these relationships and their precise impact on later noun and verb learning are not clear. In this work, we ask whether noun and verb semantic knowledge in 16-30-month-old children tend to be semantically isolated from one another or semantically interacting from the onset of vocabulary development. Early word learning patterns were quantified using network science. We measured the semantic network structure for nouns and verbs in 3,804 16-30-month-old children at several levels of granularity using a large, open dataset of vocabulary checklist data. In a cross-sectional approach in Experiment 1, early nouns and verbs exhibited stronger network relationships with other nouns and verbs than expected across multiple network levels. Using a longitudinal approach in Experiment 2, we examined patterns of normative vocabulary development over time. Initial noun and verb learning was supported by strong semantic connections to other nouns, whereas later-learned words exhibited strong connections to verbs. Overall, these two experiments suggest that nouns and verbs demonstrate early semantic interactions and that these interactions impact later word learning. Early verb and noun learning is affected by the emergence of noun and verb semantic networks during early lexical development.

Predictive language comprehension in Parkinson's disease.

Verb and action knowledge deficits are reported in persons with Parkinson's disease (PD), even in the absence of dementia or mild cognitive impairment. However, the impact of these deficits on combinatorial semantic processing is less well understood. Following on previous verb and action knowledge findings, we tested the hypothesis that PD impairs the ability to integrate event-based thematic fit information during online sentence processing. Specifically, we anticipated persons with PD with age-typical cognitive abilities would perform more poorly than healthy controls during a visual world paradigm task requiring participants to predict a target object constrained by the thematic fit of the agent-verb combination. Twenty-four PD and 24 healthy age-matched participants completed comprehensive neuropsychological assessments. We recorded participants' eye movements as they heard predictive sentences (The fisherman rocks the boat) alongside target, agent-related, verb-related, and unrelated images. We tested effects of group (PD/control) on gaze using growth curve models. There were no significant differences between PD and control participants, suggesting that PD participants successfully and rapidly use combinatory thematic fit information to predict upcoming language. Baseline sentences with no predictive information (e.g., Look at the drum) confirmed that groups showed equivalent sentence processing and eye movement patterns. Additionally, we conducted an exploratory analysis contrasting PD and controls' performance on low-motion-content versus high-motion-content verbs. This analysis revealed fewer predictive fixations in high-motion sentences only for healthy older adults. PD participants may adapt to their disease by relying on spared, non-action-simulation-based language processing mechanisms, although this conclusion is speculative, as the analyses of high- vs. low-motion items was highly limited by the study design. These findings provide novel evidence that individuals with PD match healthy adults in their ability to use verb meaning to predict upcoming nouns despite previous findings of verb semantic impairment in PD across a variety of tasks.

The role of semantic similarity in verb learning events: Vocabulary-related changes across early development.

Verb meaning is challenging for children to learn across varied events. This study examined how the taxonomic semantic similarity of the nouns in novel verb learning events in a progressive alignment learning condition differed from the taxonomic dissimilarity of nouns in a dissimilar learning condition in supporting near (similar) and far (dissimilar) verb generalization to novel objects in an eye-tracking task. A total of 48 children in two age groups (23 girls; younger: 21-24 months, Mage = 22.1 months; older: 27-30 months: Mage = 28.3 months) who differed in taxonomic vocabulary size were tested. There were no group or learning condition differences in near generalization. The younger group demonstrated better far generalization of verbs learned with semantically dissimilar nouns. The older group demonstrated the opposite pattern, with better far generalization of verbs learned with semantically similar nouns in the progressive alignment condition. These patterns were associated with children's in-category vocabulary knowledge more than other vocabulary measures, including verb vocabulary size. Taxonomic vocabulary knowledge differentially affects verb learning and generalization across development.

Difference or delay? Syntax, semantics, and verb vocabulary development in typically developing and late-talking toddlers.

While semantic and syntactic properties of verb meaning can impact the success of verb learning at a single age, developmental changes in how these factors influence acquisition are largely unexplored. We ask whether the impact of syntactic and semantic properties on verb vocabulary development varies with age and language ability for toddlers aged 16 to 30 months in a large sample (N = 5520, N Late Talkers = 821; N Typically Developing = 4699, cutoff = 15th percentile) of vocabulary checklist data from the MacArthur- Bates Communicative Development Inventory (MBCDI). Verbs from the MBCDI were coded for their syntactic and semantic properties, including manner/result meanings, durative/punctual events, and syntactic complexity. Both late talkers and typically developing children were less likely to produce syntactically complex verbs at younger ages as compared to older ages. Group differences emerged for manner/result: Typically developing children were more likely to produce manner verbs at all ages, but late talkers were more likely to produce result verbs. Regardless of group, children who produced more manner versus result verbs also had larger verb vocabulary sizes overall. These results suggest that late talkers and typically developing toddlers differ in how they build their verb vocabularies.

Developmental changes in how children generalize from their experience to support predictive linguistic processing.

Prediction is posited to support fluent comprehension of speech-but how and when do young listeners, who encounter unfamiliar and novel events with high frequency, learn to deploy predictive processing strategies in these unfamiliar circumstances? The current work used a discourse-based event teaching paradigm to explore how English-speaking school-aged children (aged 5;0-8;11 [years;months]; N = 92) generalize from their (experimentally controlled) experience to generate real-time linguistic predictions about novel events during an eye-tracked sentence recognition task. The findings reveal developmental differences in how the initial structure of event exposure supports generalization. Specifically, real-time extension was supported by viewing multiple instances of events involving varied agents in the younger children (5-6 years), whereas older children (7-8 years) extended when they experienced repetition of events with identical agents. The findings support accounts of predictive processing suggesting that learners generate predictions in a variety of less predictable circumstances and suggest practical directions to support early learning and language processing skills.

Lexico-semantic structure in vocabulary and its links to lexical processing in toddlerhood and language outcomes at age three.

Toddlerhood is marked by advances in several lexico-semantic skills, including improvements in the size and structure of the lexicon and increased efficiency in lexical processing. This project seeks to delineate how early changes in vocabulary size and vocabulary structure support lexical processing (Experiment 1), and how these three skills together (vocabulary size, structure, and lexical processing) relate to later language outcomes at age 3 (Experiment 2). Experiment 1 explored how the size and semantic structure of toddlers' vocabulary from 18 to 24 months (N = 61) predicted performance on two lexical processing tasks (semantically related and semantically unrelated trials). Denser semantic connectivity (i.e., global level connectivity between near and far neighbors) positively associated with semantic interference during semantically related lexical processing, whereas denser category structure (i.e., lower-level connectivity between near neighbors) facilitated lexical processing in semantically unrelated trials. In Experiment 2, a subset of the same children (N = 49) returned at age 36 months and completed a comprehensive assessment of their language skills using the Clinical Evaluation of Language Fundamental, Preschool 2 (CELF-P2). Here, earlier measures of lexico-semantic connectivity and lexical processing best predicted age 3 language skill. The findings support accounts that early vocabulary structure and lexical processing skills promote continued growth in language. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Do Children Use Multi-Word Information in Real-Time Sentence Comprehension?

Meaning in language emerges from multiple words, and children are sensitive to multi-word frequency from infancy. While children successfully use cues from single words to generate linguistic predictions, it is less clear whether and how they use multi-word sequences to guide real-time language processing and whether they form predictions on the basis of multi-word information or pairwise associations. We address these questions in two visual-world eye-tracking experiments with 5- to 8-year-old children. In Experiment 1, we asked whether children generate more robust predictions for the sentence-final object of highly frequent sequences (e.g., "Throw the ball"), compared to less frequent sequences (e.g., "Throw the book"). We further examined if gaze patterns reflect event knowledge or phrasal frequency by comparing the processing of phrases that have the same event structure but differ in multi-word content (e.g., "Brush your teeth" vs. "Brush her teeth"). In the second study, we employed a training paradigm to ask if children are capable of generating predictio.ns from novel multi-word associations while controlling for the overall frequency of the sequences. While the results of Experiment 1 suggested that children primarily relied on event associations to generate real-time predictions, those of Experiment 2 showed that the same children were able to use recurring novel multi-word sequences to generate real-time linguistic predictions. Together, these findings suggest that children can draw on multi-word information to generate linguistic predictions, in a context-dependent fashion, and highlight the need to account for the influence of multi-word sequences in models of language processing.

Flexible fast-mapping: Deaf children dynamically allocate visual attention to learn novel words in American Sign Language.

Word learning in young children requires coordinated attention between language input and the referent object. Current accounts of word learning are based on spoken language, where the association between language and objects occurs through simultaneous and multimodal perception. In contrast, deaf children acquiring American Sign Language (ASL) perceive both linguistic and non-linguistic information through the visual mode. In order to coordinate attention to language input and its referents, deaf children must allocate visual attention optimally between objects and signs. We conducted two eye-tracking experiments to investigate how young deaf children allocate attention and process referential cues in order to fast-map novel signs to novel objects. Participants were deaf children learning ASL between the ages of 17 and 71 months. In Experiment 1, participants (n = 30) were presented with a novel object and a novel sign, along with a referential cue that occurred either before or after the sign label. In Experiment 2, a new group of participants (n = 32) were presented with two novel objects and a novel sign, so that the referential cue was critical for identifying the target object. Across both experiments, participants showed evidence for fast-mapping the signs regardless of the timing of the referential cue. Individual differences in children's allocation of attention during exposure were correlated with their ability to fast-map the novel signs at test. This study provides first evidence for fast-mapping in sign language, and contributes to theoretical accounts of how word learning develops when all input occurs in the visual modality.

Toddlers' Ability to Leverage Statistical Information to Support Word Learning.

PURPOSE: This study investigated whether the ability to utilize statistical regularities from fluent speech and map potential words to meaning at 18-months predicts vocabulary at 18- and again at 24-months. METHOD: Eighteen-month-olds (N = 47) were exposed to an artificial language with statistical regularities within the speech stream, then participated in an object-label learning task. Learning was measured using a modified looking-while-listening eye-tracking design. Parents completed vocabulary questionnaires when their child was 18-and 24-months old. RESULTS: Ability to learn the object-label pairing for words after exposure to the artificial language predicted productive vocabulary at 24-months and amount of vocabulary change from 18- to 24 months, independent of non-verbal cognitive ability, socio-economic status (SES) and/or object-label association performance. CONCLUSION: Eighteen-month-olds' ability to use statistical information derived from fluent speech to identify words within the stream of speech and then to map the "words" to meaning directly predicts vocabulary size at 24-months and vocabulary change from 18 to 24 months. The findings support the hypothesis that statistical word segmentation is one of the important aspects of word learning and vocabulary acquisition in toddlers.

Moving towards accurate and early prediction of language delay with network science and machine learning approaches.

Due to wide variability of typical language development, it has been historically difficult to distinguish typical and delayed trajectories of early language growth. Improving our understanding of factors that signal language disorder and delay has the potential to improve the lives of the millions with developmental language disorder (DLD). We develop predictive models of low language (LL) outcomes by analyzing parental report measures of early language skill using machine learning and network science approaches. We harmonized two longitudinal datasets including demographic and standardized measures of early language skills (the MacArthur-Bates Communicative Developmental Inventories; MBCDI) as well as a later measure of LL. MBCDI data was used to calculate several graph-theoretic measures of lexico-semantic structure in toddlers' expressive vocabularies. We use machine-learning techniques to construct predictive models with these datasets to identify toddlers who will have later LL outcomes at preschool and school-age. This approach yielded robust and reliable predictions of later LL outcome with classification accuracies in single datasets exceeding 90%. Generalization performance between different datasets was modest due to differences in outcome ages and diagnostic measures. Grammatical and lexico-semantic measures ranked highly in predictive classification, highlighting promising avenues for early screening and delineating the roots of language disorders.

Perceptual Connectivity Influences Toddlers' Attention to Known Objects and Subsequent Label Processing.

While recent research suggests that toddlers tend to learn word meanings with many "perceptual" features that are accessible to the toddler's sensory perception, it is not clear whether and how building a lexicon with perceptual connectivity supports attention to and recognition of word meanings. We explore this question in 24-30-month-olds (N = 60) in relation to other individual differences, including age, vocabulary size, and tendencies to maintain focused attention. Participants' looking to item pairs with high vs. low perceptual connectivity-defined as the number of words in a child's lexicon sharing perceptual features with the item-was measured before and after target item labeling. Results revealed pre-labeling attention to known items is biased to both high- and low-connectivity items: first to high, and second, but more robustly, to low-connectivity items. Subsequent object-label processing was also facilitated for high-connectivity items, particularly for children with temperamental tendencies to maintain focused attention. This work provides the first empirical evidence that patterns of shared perceptual features within children's known vocabularies influence both visual and lexical processing, highlighting the potential for a newfound set of developmental dependencies based on the perceptual/sensory structure of early vocabularies.

When slowing down processing helps learning: Lexico-semantic structure supports retention, but interferes with disambiguation of novel object-label mappings.

This project explores how children disambiguate and retain novel object-label mappings in the face of semantic similarity. Burgeoning evidence suggests that semantic structure in the developing lexicon promotes word learning in ostensive contexts, whereas other findings indicate that semantic similarity interferes with and temporarily slows familiar word recognition. This project explores how these distinct processes interact when mapping and retaining labels for novel objects (i.e., low-frequency objects that are unfamiliar to toddlers) via disambiguation from a semantically similar familiar referent in 24-month-olds (N = 65). Toddlers' log-adjusted looking to labeled target objects (relative to distractor objects) was measured in three conditions: Familiar trials (familiar label spoken while viewing semantically related familiar and novel objects), Disambiguation trials (unfamiliar label spoken while viewing semantically similar familiar and unfamiliar object), and Retention trials (unfamiliar label spoken while viewing novel object pairs). Toddlers' individual vocabulary structure was then compared to performance on each condition. Vocabulary structure was measured at two levels: category-level structure (semantic density) for experimental items, and lexicon-level structure (global clustering coefficient). The findings suggest, consistent with prior results, that semantic density interfered with known word recognition, and facilitated unfamiliar word retention. Children did not show a significant novel word preference during disambiguation, and disambiguation behavior was not impacted by semantic structure. These findings connect seemingly disparate mechanisms of semantic interference in processing and semantic leveraging in word learning. Semantic interference momentarily slows word recognition and resolution of referential uncertainty for novel label-object mappings. Nevertheless, this slowing might support retention by enabling comparison between related objects.

Lexical Recognition in Deaf Children Learning American Sign Language: Activation of Semantic and Phonological Features of Signs.

Children learning language efficiently process single words, and activate semantic, phonological, and other features of words during recognition. We investigated lexical recognition in deaf children acquiring American Sign Language (ASL) to determine how perceiving language in the visual-spatial modality affects lexical recognition. Twenty native- or early-exposed signing deaf children (ages 4 to 8 years) participated in a visual world eye-tracking study. Children were presented with a single ASL sign, target picture, and three competitor pictures that varied in their phonological and semantic relationship to the target. Children shifted gaze to the target picture shortly after sign offset. Children showed robust evidence for activation of semantic but not phonological features of signs, however in their behavioral responses children were most susceptible to phonological competitors. Results demonstrate that single word recognition in ASL is largely parallel to spoken language recognition among children who are developing a mature lexicon.

Examining the impact of text style and epistemic beliefs on conceptual change.

Learning can be difficult for students due to incorrect prior knowledge, or misconceptions, interfering with the acquisition of new knowledge. Conceptual change refers to the process of replacing such misconceptions with new and accurate knowledge. The factors associated with conceptual change are currently under debate. The present study attempts to replicate previous investigations of how text style and epistemic beliefs impact conceptual change, and extends this work by investigating how those factors differentially facilitate conceptual change within participants. 157 college students completed a two-part, within participants study in which they completed pretests, read passages addressing a misconception, completed posttests, and were assessed on their epistemic beliefs. Text style (expository vs. refutation) and two dimensions of epistemic beliefs (texture and variability) did not directly impact pre-to-posttest changes in performance. However, interactions between text type, texture, and variability were related to changes in performance.

Vocabulary size and structure affects real-time lexical recognition in 18-month-olds.

The mature lexicon encodes semantic relations between words, and these connections can alternately facilitate and interfere with language processing. We explore the emergence of these processing dynamics in 18-month-olds (N = 79) using a novel approach that calculates individualized semantic structure at multiple granularities in participants' productive vocabularies. Participants completed two interleaved eye-tracked word recognition tasks involving semantically unrelated and related picture contexts, which sought to measure the impact of lexical facilitation and interference on processing, respectively. Semantic structure and vocabulary size differentially impacted processing in each task. Category level structure facilitated word recognition in 18-month-olds with smaller productive vocabularies, while overall lexical connectivity interfered with word recognition for toddlers with relatively larger vocabularies. The results suggest that, while semantic structure at multiple granularities is measurable even in small lexicons, mechanisms of semantic interference and facilitation are driven by the development of structure at different granularities. We consider these findings in light of accounts of adult word recognition that posits that different levels of structure index strong and weak activation from nearby and distant semantic neighbors. We also consider further directions for developmental change in these patterns.

Predict and redirect: Prediction errors support children's word learning.

According to prediction-based learning theories, erroneous predictions support learning. However, empirical evidence for a relation between prediction error and children's language learning is currently lacking. Here we investigated whether and how prediction errors influence children's learning of novel words. We hypothesized that word learning would vary as a function of 2 factors: the extent to which children generate predictions, and the extent to which children redirect attention in response to errors. Children were tested in a novel word learning task, which used eye tracking to measure (a) real-time semantic predictions to familiar referents, (b) attention redirection following prediction errors, and (c) learning of novel referents. Results indicated that predictions and prediction errors interdependently supported novel word learning, via children's efficient redirection of attention. This study provides a developmental evaluation of prediction-based theories and suggests that erroneous predictions play a mechanistic role in children's language learning. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Modeling early lexico-semantic network development: Perceptual features matter most.

What aspects of word meaning are important in early word learning and lexico-semantic network development? Adult lexico-semantic systems flexibly encode multiple types of semantic features, including functional, perceptual, taxonomic, and encyclopedic. However, various theoretical accounts of lexical development differ on whether and how these semantic properties of word meanings are initially encoded into young children's emerging lexico-semantic networks. Whereas some accounts highlight the importance of early perceptual versus conceptual properties, others posit that thematic or functional aspects of word meaning are primary relative to taxonomic knowledge. We seek to shed light on these debates with 2 modeling studies that explore patterns in early word learning using a large database of early vocabulary in 5,450 children, and a newly developed set of semantic features of early acquired nouns. In Study 1, we ask whether semantic properties of early acquired words relate to order in which these words are typically learned; Study 2 models normative lexico-semantic noun-feature network development compared to random network growth. Both studies provide converging evidence that perceptual properties of word meanings play a key role in early word learning and lexico-semantic network development. The findings lend support to theoretical accounts of language learning that highlight the importance of the child's perceptual experience. (PsycINFO Database Record (c) 2019 APA, all rights reserved).