Language is acquired in part through statistical learning abilities that encode environmental regularities. Language development is also heavily influenced by social environmental factors such as socioeconomic status. However, it is unknown to what extent statistical learning interacts with SES to affect language outcomes. We measured event-related potentials in 26 children aged 8-12 while they performed a visual statistical learning task. Regression analyses indicated that children's learning performance moderated the relationship between socioeconomic status and both syntactic and vocabulary language comprehension scores. For children demonstrating high learning, socioeconomic status had a weaker effect on language compared to children showing low learning. These results suggest that high statistical learning ability can provide a buffer against the disadvantages associated with being raised in a lower socioeconomic status household.

Much of our current knowledge regarding the association of FOXP2 with speech and language development comes from singleton and small family studies where a small number of rare variants have been identified. However, neither genome-wide nor gene-specific studies have provided evidence that common polymorphisms in the gene contribute to individual differences in language development in the general population. One explanation for this inconsistency is that previous studies have been limited to relatively small samples of individuals with low language abilities, using low density gene coverage. The current study examined the association between common variants in FOXP2 and a quantitative measure of language ability in a population-based cohort of European decent (n = 812). No significant associations were found for a panel of 13 SNPs that covered the coding region of FOXP2 and extended into the promoter region. Power analyses indicated we should have been able to detect a QTL variance of 0.02 for an associated allele with MAF of 0.2 or greater with 80% power. This suggests that, if a common variant associated with language ability in this gene does exist, it is likely of small effect. Our findings lead us to conclude that while genetic variants in FOXP2 may be significant for rare forms of language impairment, they do not contribute appreciably to individual variation in the normal range as found in the general population.

Resting state studies of spontaneous fluctuations in the functional magnetic resonance imaging (fMRI) blood oxygen level dependent signal have shown great potential in mapping the intrinsic functional connectivity of the human brain underlying cognitive functions. The aim of the present study was to explore the developmental changes in functional networks of the developing human brain exemplified with the language network in typically developing preschool children. To this end, resting-sate fMRI data were obtained from native Chinese children at ages of 3 and 5 years, 15 in each age group. Resting-state functional connectivity (RSFC) was analyzed for four regions of interest; these are the left and right anterior superior temporal gyrus (aSTG), left posterior superior temporal gyrus (pSTG), and left inferior frontal gyrus (IFG). The comparison of these RSFC maps between 3- and 5-year-olds revealed that RSFC decreases in the right aSTG and increases in the left hemisphere between aSTG seed and IFG, between pSTG seed and IFG, as well as between IFG seed and posterior superior temporal sulcus. In a subsequent analysis, functional asymmetry of the language network seeding in aSTG, pSTG and IFG was further investigated. The results showed an increase of left lateralization in both RSFC of pSTG and of IFG from ages 3 to 5 years. The IFG showed a leftward lateralized trend in 3-year-olds, while pSTG demonstrated rightward asymmetry in 5-year-olds. These findings suggest clear developmental trajectories of the language network between 3- and 5-year-olds revealed as a function of age, characterized by increasing long-range connections and dynamic hemispheric lateralization with age. Our study provides new insights into the developmental changes of a well-established functional network in young children and also offers a basis for future cross-culture and cross-age studies of the resting-state language network.

Recent evidence suggests that spatial language in preschool positively affects the development of verbal number skills, as indexed by aggregated performances on counting and number naming tasks. We firstly aimed to specify whether spatial language (the knowledge of locative prepositions) significantly relates to both of these measures. In addition, we assessed whether the predictive value of spatial language extends beyond verbal number skills to numerical subdomains without explicit verbal component, such as number writing, symbolic magnitude classifications, ordinal judgments and numerosity comparisons. To determine the unique contributions of spatial language to these numerical skills, we controlled in our regression analyses for intrinsic and extrinsic spatial abilities, phonological awareness as well as age, socioeconomic status and home language. With respect to verbal number skills, it appeared that spatial language uniquely predicted forward and backward counting but not number naming, which was significantly affected only by phonological awareness. Regarding numerical tasks that do not contain explicit verbal components, spatial language did not relate to number writing or numerosity comparisons. Conversely, it explained unique variance in symbolic magnitude classifications and was the only predictor of ordinal judgments. These findings thus highlight the importance of spatial language for early numerical development beyond verbal number skills and suggest that the knowledge of spatial terms is especially relevant for processing cardinal and ordinal relations between symbolic numbers. Promoting spatial language in preschool might thus be an interesting avenue for fostering the acquisition of these symbolic numerical skills prior to formal schooling.

The huge power for social influence of digital media may come with the risk of intensifying common societal biases, such as gender and age stereotypes. Speaker's gender and age also behaviorally manifest in language use, and language may be a powerful tool to shape impact. The present study took the example of TED, a highly successful knowledge dissemination platform, to study online influence. Our goal was to investigate how gender- and age-linked language styles-beyond chronological age and identified gender-link to talk impact and whether this reflects gender and age stereotypes. In a pre-registered study, we collected transcripts of TED Talks along with their impact measures, i.e., views and ratios of positive and negative talk ratings, from the TED website. We scored TED Speakers' (N = 1,095) language with gender- and age-morphed language metrics to obtain measures of female versus male, and younger versus more senior language styles. Contrary to our expectations and to the literature on gender stereotypes, more female language was linked to higher impact in terms of quantity, i.e., more talk views, and this was particularly the case among talks with a lot of views. Regarding quality of impact, language signatures of gender and age predicted different types of positive and negative ratings above and beyond main effects of speaker's gender and age. The differences in ratings seem to reflect common stereotype contents of warmth (e.g., "beautiful" for female, "courageous" for female and senior language) versus competence (e.g., "ingenious", "informative" for male language). The results shed light on how verbal behavior may contribute to stereotypical evaluations. They also illuminate how, within new digital social contexts, female language might be uniquely rewarded and, thereby, an underappreciated but highly effective tool for social influence. WC = 286 (max. 300 words).

We used event-related potentials to investigate morphosyntactic development in 78 adult English-speaking learners of Spanish as a second language (L2) across the proficiency spectrum. We examined how development is modulated by the similarity between the native language (L1) and the L2, by comparing number (a feature present in English) and gender agreement (novel feature). We also investigated how development is impacted by structural distance, manipulating the distance between the agreeing elements by probing both within-phrase (fruta muy jugosa "fruit-FEM-SG very juicy-FEM-SG") and across-phrase agreement (fresa es ácida "strawberry-FEM-SG is tart-FEM-SG"). Regression analyses revealed that the learners' overall proficiency, as measured by a standardized test, predicted their accuracy with the target properties in the grammaticality judgment task (GJT), but did not predict P600 magnitude to the violations. However, a relationship emerged between immersion in Spanish-speaking countries and P600 magnitude for gender. Our results also revealed a correlation between accuracy in the GJT and P600 magnitude, suggesting that behavioral sensitivity to the target property predicts neurophysiological sensitivity. Subsequent group analyses revealed that the highest-proficiency learners showed equally robust P600 effects for number and gender. This group also elicited more positive waveforms for within- than across-phrase agreement overall, similar to the native controls. The lowest-proficiency learners showed a P600 for number overall, but no effects for gender. Unlike the highest-proficiency learners, they also showed no sensitivity to structural distance, suggesting that sensitivity to such linguistic factors develops over time. Overall, these results suggest an important role for proficiency in morphosyntactic development, although differences emerged between behavioral and electrophysiological measures. While L2 proficiency predicted behavioral sensitivity to agreement, development with respect to the neurocognitive mechanisms recruited in processing only emerged when comparing the two extremes of the proficiency spectrum. Importantly, while both L1-L2 similarity and hierarchical structure impact development, they do not constrain it.

The results of studies targeting cognitive and academic advantages in children frequenting early bilingual immersion school programs (CLIL) have been contradictory. While the impact of the amount of CLIL experience has already been studied, the role of the second language learned has been little studied to account for differences among study findings. The link between executive skills (EF) and scholar abilities (e.g., mathematics) in the CLIL context has also been little investigated. The purpose of the present study was to determine if the impact of CLIL on EF and academic performances varies depending on the immersion language and the duration of CLIL experience. The sample included a total of 230 French-speaking children attending second (141) and fifth (89) grade classes. Within each grade, there were three matched language groups composed of children respectively immersed in English, immersed in Dutch, and non-immersed controls. The children were administered tasks assessing executive functions [alerting, cognitive flexibility, and working memory], as well as arithmetic abilities. In second grade, we detected no difference in EF between the language groups. On the other hand, in fifth grade, the two immersed groups outperformed the non-immersed group on the cognitive flexibility task but did not differ between them. Moreover, only the Dutch immersed group outperformed the control group on the working memory task. Arithmetic performances also differed depending on the language learned; in second grade, Dutch learners performed better than the monolingual group. In fifth grade, Dutch learners outperformed the two other groups. These results suggest that the impact of CLIL on executive skills and arithmetic performances might be modulated by the amount of CLIL experience and the second language learned in immersion.

The developmental significance of the frequently encountered white matter signal abnormality (WMSA) findings on MRI around term-equivalent age (TEA) in very preterm infants, remains in question. The use of conventional qualitative analysis methods is subjective, lacks sufficient reliability for producing accurate and reproducible WMSA diagnosis, and possibly contributes to suboptimal neurodevelopmental outcome prediction. The advantages of quantitative over qualitative diagnostic approaches have been widely acknowledged and demonstrated. The purpose of this study is to objectively and accurately quantify WMSA on TEA T2-weighted MRI in very preterm infants and to assess whether such quantifications predict 2-year language and cognitive developmental outcomes. To this end, we constructed a probabilistic brain atlas, exclusively for very preterm infants to embed tissue distributions (i.e. to encode shapes, locations and geometrical proportion of anatomical structures). Guided with this atlas, we then developed a fully automated method for WMSA detection and quantification using T2-weighted images. Computer simulations and experiments using in vivo very preterm data showed very high detection accuracy. WMSA volume, particularly in the centrum semiovale, on TEA MRI was a significant predictor of standardized language and cognitive scores at 2 years of age. Independent validation of our automated WMSA detection algorithm and school age follow-up are important next steps.

This study investigated the etiology of individual differences in Chinese language and reading skills in 312 typically developing Chinese twin pairs aged from 3 to 11 years (228 pairs of monozygotic twins and 84 pairs of dizygotic twins; 166 male pairs and 146 female pairs). Children were individually given tasks of Chinese word reading, receptive vocabulary, phonological memory, tone awareness, syllable and rhyme awareness, rapid automatized naming, morphological awareness and orthographic skills, and Raven's Coloured Progressive Matrices. All analyses controlled for the effects of age. There were moderate to substantial genetic influences on word reading, tone awareness, phonological memory, morphological awareness and rapid automatized naming (estimates ranged from .42 to .73), while shared environment exerted moderate to strong effects on receptive vocabulary, syllable and rhyme awareness and orthographic skills (estimates ranged from .35 to .63). Results were largely unchanged when scores were adjusted for nonverbal reasoning as well as age. Findings of this study are mostly similar to those found for English, a language with very different characteristics, and suggest the universality of genetic and environmental influences across languages.

Language tests developed and validated in one country may lose their desired properties when translated for use in another, possibly resulting in misleading estimates of ability. Using Item Response Theory (IRT) methodology, we assess the performance of a test of receptive vocabulary, the U.S.-validated Peabody Picture Vocabulary Test-Third Edition (PPVT-III), when translated, adapted, and administered to children 3 to 10 years of age in Madagascar (N = 1372), in the local language (Malagasy). Though Malagasy is considered a single language, there are numerous dialects spoken in Madagascar. Our findings were that test scores were positively correlated with age and indicators of socio-economic status. However, over half (57/96) of items evidenced unexpected response variation and/or bias by local dialect spoken. We also encountered measurement error and reduced differentiation among person abilities when we used the publishers' recommended stopping rules, largely because we lost the original item ordering by difficulty when we translated test items into Malagasy. Our results suggest that bias and testing inefficiency introduced from the translation of the PPVT can be significantly reduced with the use of methods based on IRT at both the pre-testing and analysis stages. We explore and discuss implications for cross-cultural comparisons of internationally recognized tests, such as the PPVT.

Automatically inferring user demographics from social media posts is useful for both social science research and a range of downstream applications in marketing and politics. We present the first extensive study where user behaviour on Twitter is used to build a predictive model of income. We apply non-linear methods for regression, i.e. Gaussian Processes, achieving strong correlation between predicted and actual user income. This allows us to shed light on the factors that characterise income on Twitter and analyse their interplay with user emotions and sentiment, perceived psycho-demographics and language use expressed through the topics of their posts. Our analysis uncovers correlations between different feature categories and income, some of which reflect common belief e.g. higher perceived education and intelligence indicates higher earnings, known differences e.g. gender and age differences, however, others show novel findings e.g. higher income users express more fear and anger, whereas lower income users express more of the time emotion and opinions.

Deficits in social communication, particularly pragmatic language, are characteristic of individuals with autism spectrum disorder (ASD). Speech disfluencies may serve pragmatic functions such as cueing speaking problems. Previous studies have found that speakers with ASD differ from typically developing (TD) speakers in the types and patterns of disfluencies they produce, but fail to provide sufficiently detailed characterizations of the methods used to categorize and quantify disfluency, making cross-study comparison difficult. In this study we propose a simple schema for classifying major disfluency types, and use this schema in an exploratory analysis of differences in disfluency rates and patterns among children with ASD compared to TD and language impaired (SLI) groups. 115 children ages 4-8 participated in the study (ASD = 51; SLI = 20; TD = 44), completing a battery of experimental tasks and assessments. Measures of morphological and syntactic complexity, as well as word and disfluency counts, were derived from transcripts of the Autism Diagnostic Observation Schedule (ADOS). High inter-annotator agreement was obtained with the use of the proposed schema. Analyses showed ASD children produced a higher ratio of content to filler disfluencies than TD children. Relative frequencies of repetitions, revisions, and false starts did not differ significantly between groups. TD children also produced more cued disfluencies than ASD children.

Successful open source software (OSS) projects comprise freely observable, task-oriented social networks with hundreds or thousands of participants and large amounts of (textual and technical) discussion. The sheer volume of interactions and participants makes it challenging for participants to find relevant tasks, discussions and people. Tagging (e.g., @AmySmith) is a socio-technical practice that enables more focused discussion. By tagging important and relevant people, discussions can be advanced more effectively. However, for all but a few insiders, it can be difficult to identify important and/or relevant people. In this paper we study tagging in OSS projects from a socio-linguistics perspective. First we argue that textual content per se reveals a great deal about the status and identity of who is speaking and who is being addressed. Next, we suggest that this phenomenon can be usefully modeled using modern deep-learning methods. Finally, we illustrate the value of these approaches with tools that could assist people to find the important and relevant people for a discussion.

Accurate aphasia diagnosis is important in stroke care. A wide range of language tests are available and include informal assessments, tests developed by healthcare institutions and commercially published tests available for purchase in pre-packaged kits. The psychometrics of these tests are often reported online or within the purchased test manuals, not the peer-reviewed literature, therefore the diagnostic capabilities of these measures have not been systematically evaluated. This review aimed to identify both commercial and non-commercial language tests and tests used in stroke care and to examine the diagnostic capabilities of all identified measures in diagnosing aphasia in stroke populations.

Software engineering artifact extraction from natural language requirements without human intervention is a challenging task. Out of these artifacts, the use case plays a prominent role in software design and development. In the literature, most of the approaches are either semi-automated or necessitate formalism or make use of restricted natural language for the extraction of use cases from textual requirements. In this paper, we resolve the challenge of automated artifact extraction from natural language requirements. We propose an automated approach to generate use cases, actors, and their relationships from natural language requirements. Our proposed approach involves no human intervention or formalism. To automate the proposed approach, we have used Natural Language Processing and Network Science. Our proposed approach provides promising results for the extraction of use case elements from natural language requirements. We validate the proposed approach using several literature-based case studies. The proposed approach significantly improves the results in comparison to an existing approach. On average, the proposed approach achieves around 71.5% accuracy (F-Measure), whereas the baseline method achieves around 16% accuracy (F-Measure) on average. The evaluation of the proposed approach on the literature-based case studies shows its significance for the extraction of use case elements from natural language requirements. The approach reduces human effort in software design and development.

Delayed or impaired language development is a common developmental concern, yet there is little agreement about the criteria used to identify and classify language impairments in children. Children's language difficulties are at the interface between education, medicine and the allied professions, who may all adopt different approaches to conceptualising them. Our goal in this study was to use an online Delphi technique to see whether it was possible to achieve consensus among professionals on appropriate criteria for identifying children who might benefit from specialist services. We recruited a panel of 59 experts representing ten disciplines (including education, psychology, speech-language therapy/pathology, paediatrics and child psychiatry) from English-speaking countries (Australia, Canada, Ireland, New Zealand, United Kingdom and USA). The starting point for round 1 was a set of 46 statements based on articles and commentaries in a special issue of a journal focusing on this topic. Panel members rated each statement for both relevance and validity on a seven-point scale, and added free text comments. These responses were synthesised by the first two authors, who then removed, combined or modified items with a view to improving consensus. The resulting set of statements was returned to the panel for a second evaluation (round 2). Consensus (percentage reporting 'agree' or 'strongly agree') was at least 80 percent for 24 of 27 round 2 statements, though many respondents qualified their response with written comments. These were again synthesised by the first two authors. The resulting consensus statement is reported here, with additional summary of relevant evidence, and a concluding commentary on residual disagreements and gaps in the evidence base.

Preterm children often have language problems. This atypical language development is probably due to atypical brain development. We conducted a systematic review to provide an overview of the extensive and diverse scientific literature on the relations between language outcome and underlying brain structures in school-aged preterm-born children. Embase, Medline Ovid, Web of Science, Cochrane central and Google scholar were searched for relevant studies. Inclusion criteria were: cases are school-aged preterm children; structural MRI (T1- and T2-weighted sequences) or DTI used in combination with a neurocognitive language test; publication in an English-language peer-reviewed journal. Correlational measures between language scores and brain volume or fractional anisotropy of a brain structure were extracted. 23 studies were included. The relations between oral language, verbal fluency and/or written language and MRI/DTI measurements of white matter, gray matter, cerebellum, corpus callosum and/or the fasciculi are presented. Oral language skills and verbal fluency appear to be related to the corpus callosum. Oral language skills are also related to the uncinate fasciculus. There seems to be no clear relation between cerebellar development and verbal fluency skills. Not one single brain area is responsible for atypical language development, but several brain areas and their connections are essential. For future research it is recommended to relate brain areas to oral language skills on a microstructural level in preterm children. We also recommend to use language tests in which it is possible to distinguish between several language domains, such as perceptive and expressive language.

In a cross-sectional study of youth ages 8-15, we examined implicit and explicit gender stereotypes regarding math and language abilities. We investigated how implicit and explicit stereotypes differ across age and gender groups and whether they are consistent with cultural stereotypes. Participants (N = 270) completed the Affect Misattribution Procedure (AMP) and a survey of explicit beliefs. Across all ages, boys showed neither math nor language implicit gender biases, whereas girls implicitly favored girls in both domains. These findings are counter to cultural stereotypes, which favor boys in math. On the explicit measure, both boys' and girls' primary tendency was to favor girls in math and language ability, with the exception of elementary school boys, who rated genders equally. We conclude that objective gender differences in academic success guide differences in children's explicit reports and implicit biases.

The FoxP2 transcription factor and its target genes have been implicated in developmental brain diseases with a prominent language component, such as developmental verbal dyspraxia and specific language impairment. How FoxP2 affects neural circuitry development remains poorly understood. The sushi domain protein SRPX2 is a target of FoxP2, and mutations in SRPX2 are associated with language defects in humans. We have previously shown that SRPX2 is a synaptogenic protein that increases excitatory synapse density. Here we provide the first characterization of mice lacking the SRPX2 gene, and show that these mice exhibit defects in both neural circuitry and communication and social behaviors. Specifically, we show that mice lacking SRPX2 show a specific reduction in excitatory VGlut2 synapses in the cerebral cortex, while VGlut1 and inhibitory synapses were largely unaffected. SRPX2 KO mice also exhibit an abnormal ultrasonic vocalization ontogenetic profile in neonatal pups, and reduced preference for social novelty. These data demonstrate a functional role for SRPX2 during brain development, and further implicate FoxP2 and its targets in regulating the development of vocalization and social circuits.

Language is used to identify objects in many different ways. An apple can be identified using its name, color, and other attributes. Skilled language comprehension requires listeners to flexibly shift between different dimensions. We asked whether this shifting would be difficult for 3-year-olds, who have relatively immature executive function skills and struggle to switch between dimensions in card sorting tasks. In the current experiment, children first heard a series of sentences identifying objects using a single dimension (either names or colors). In the second half of the experiment, the labeling dimension was switched. Children were significantly less accurate in fixating the correct object following the dimensional switch. This disruption, however, was temporary; recognition accuracy recovered with increased exposure to the new labeling dimension. These findings provide the first evidence that children's difficulty in shifting between dimensions impacts their ability to comprehend speech. This limitation may affect children's ability to form rich, multi-dimensional representations when learning new words.