Social interactions offset the detrimental effects of digital media use on children's vocabulary.

Young children's rapid vocabulary growth during the first few years is supported by input during social interactions with caregivers and, increasingly, from digital media. However, the amount of exposure to both sources can vary substantially across socioeconomic classes, and little is known about how social interactions and digital media use together predict vocabulary in the first few years of life. The current study takes a first step toward examining whether increased social interactions with other individuals may buffer the potentially detrimental effects of digital media use on language among a socioeconomically diverse sample. 305 caregivers of children between 17 and 30-months completed questionnaires about their family demographics, their child's technology use, and the child's daily routines and social interactions. Findings suggest children who experience fewer human interactions and greater technology exposure have smaller vocabularies than their peers who socialize more and use less technology, and this disparity becomes greater as children get older. Moreover, the number of social interactions moderates the link between SES, digital media, and vocabulary such that the negative impact of digital media on vocabulary for children from low SES households can be offset with increased social interactions. Together, this suggests that increasing the amount of human interactions may serve as a protective factor for vocabulary outcomes in a world where digital media use is prominent.

Limited but specific engagement of the mature language network during linguistic statistical learning.

Statistical learning (SL) is the ability to detect and learn regularities from input and is foundational to language acquisition. Despite the dominant role of SL as a theoretical construct for language development, there is a lack of direct evidence supporting the shared neural substrates underlying language processing and SL. It is also not clear whether the similarities, if any, are related to linguistic processing, or statistical regularities in general. The current study tests whether the brain regions involved in natural language processing are similarly recruited during auditory, linguistic SL. Twenty-two adults performed an auditory linguistic SL task, an auditory nonlinguistic SL task, and a passive story listening task as their neural activation was monitored. Within the language network, the left posterior temporal gyrus showed sensitivity to embedded speech regularities during auditory, linguistic SL, but not auditory, nonlinguistic SL. Using a multivoxel pattern similarity analysis, we uncovered similarities between the neural representation of auditory, linguistic SL, and language processing within the left posterior temporal gyrus. No other brain regions showed similarities between linguistic SL and language comprehension, suggesting that a shared neurocomputational process for auditory SL and natural language processing within the left posterior temporal gyrus is specific to linguistic stimuli.

The Necessity of Taking Culture and Context into Account When Studying the Relationship between Socioeconomic Status and Brain Development.

Decades of research has revealed a relationship between childhood socioeconomic status (SES) and brain development at the structural and functional levels. Of particular note is the distinction between income and maternal education, two highly correlated factors which seem to influence brain development through distinct pathways. Specifically, while a families' income-to-needs ratio is linked with physiological stress and household chaos, caregiver education influences the day-to-day language environment a child is exposed to. Variability in either one of these environmental experiences is related to subsequent brain development. While this work has the potential to inform public policies in a way that benefits children, it can also oversimplify complex factors, unjustly blame low-SES parents, and perpetuate a harmful deficit perspective. To counteract these shortcomings, researchers must consider sociodemographic differences in the broader cultural context that underlie SES-based differences in brain development. This review aims to address these issues by (a) identifying how sociodemographic mechanisms associated with SES influence the day-to-day experiences of children, in turn, impacting brain development, while (b) considering the broader cultural contexts that may differentially impact this relationship.

Executive function skills account for a bilingual advantage in English novel word learning among low-income preschoolers.

The current study compared economically disadvantaged bilingual and monolingual preschoolers' performance on an English novel word learning task and examined whether children's executive function (EF) skills account for differences in novel word learning performance across groups. In total, 39 English monolinguals and 35 Spanish-English bilingual preschoolers from low-income homes completed a battery of EF measures and the Quick Interactive Language Screener to gauge English novel word learning ability. Within a poverty context, bilingual preschoolers performed significantly better on measures of English novel word learning as compared with their monolingual peers. This bilingual advantage in novel word learning ability was mediated by short-term memory, but not inhibition or attention shifting, which indicates that gains in short-term memory may facilitate word learning in English for bilingual preschoolers from economically disadvantaged backgrounds. These findings have important practical implications for interventions designed to promote English vocabulary growth for low-income bilingual children.

Age and vocabulary knowledge differentially influence the N400 and theta responses during semantic retrieval.

Using electroencephalography (EEG) to study the neural oscillations supporting language development is increasingly common; however, a clear understanding of the relationship between neural oscillations and traditional Event Related Potentials (ERPs) is needed to disentangle how maturation of language-related neural networks supports semantic processing throughout grade school. Theta and the N400 are both thought to index semantic retrieval but, in adults, are only weakly correlated with one another indicating they may measure somewhat unique aspects of retrieval. Here, we studied the relationship between the N400 amplitude and theta power during semantic retrieval with key indicators of language abilities including age, vocabulary, reading comprehension and phonological memory in 226 children ages 8-15 years. The N400 and theta responses were positively correlated over posterior areas, but negatively correlated over frontal areas. When controlling for the N400 amplitude, the amplitude of the theta response was predicted by age, but not by language measures. On the other hand, when controlling theta amplitude, the amplitude of the N400 was predicted by both vocabulary knowledge and age. These findings indicate that while there is a clear relationship between the N400 and theta responses, they may each index unique aspects of development related to semantic retrieval.

Developmental differences in EEG oscillations supporting the identification of novel word meaning from context.

Implicit learning about new words by picking up on associative information in the contexts they appear in is an important aspect of vocabulary growth. The current study investigated the neural correlates that underlie how school-aged children and adolescents identify the meaning of novel words embedded within sentence contexts. Importantly, we examine how differences in the brain response to novel words and their context differ as a function of 1) explicit learning success, i.e., whether novel word meanings can be correctly estimated in isolation after a learning opportunity, and 2) individual differences in offline language aptitude as well as age across our cohort (N = 82; 8-16 years). Using a regression-based analysis, we identified the unique influence of these individuals difference metrics by using both measures within the same series of models. The most notable finding from our analysis was a frequency-specific dissociation between the way age and language abilities held relationships with task-relevant oscillatory activity during the novel word meaning task: language abilities associated with task-relevant changes in beta band activity during sentence processing, while age associated with task-relevant changes in theta band activity during pseudoword processing. These effects reflect the how the neural correlates of mapping semantic meaning from sentence contexts-an important skill for word learning-is uniquely influenced by the maturity of language abilities as well as age.

Mechanical Properties of the Developing Brain are Associated with Language Input and Vocabulary Outcome.

The quality of language that children hear in their environment is associated with the development of language-related brain regions, in turn promoting vocabulary knowledge. Although informative, it remains unknown how these environmental influences alter the structure of neural tissue and subsequent vocabulary outcomes. The current study uses magnetic resonance elastography (MRE) to examine how children's language environments underlie brain tissue mechanical properties, characterized as brain tissue stiffness and damping ratio, and promote vocabulary knowledge. Twenty-five children, ages 5-7, had their audio and video recorded while engaging in a play session with their parents. Children also completed the Picture Vocabulary Task (from NIH Toolbox) and participated in an MRI, where MRE and anatomical images were acquired. Higher quality input was associated with greater stiffness in the bilateral inferior frontal gyrus and right superior temporal gyrus, whereas greater vocabulary knowledge was associated with lower damping ratio in the right inferior frontal gyrus. These findings suggest changes in neural tissue composition are sensitive to malleable aspects of the environment, whereas tissue organization is more strongly associated with vocabulary outcome. Notably, these associations were independent of maternal education, suggesting more proximal measures of a child's environment may be the source of differences in neural tissue structure underlying variability in vocabulary outcomes.

Mapping brain mechanical property maturation from childhood to adulthood.

Magnetic resonance elastography (MRE) is a phase contrast MRI technique which uses external palpation to create maps of brain mechanical properties noninvasively and in vivo. These mechanical properties are sensitive to tissue microstructure and reflect tissue integrity. MRE has been used extensively to study aging and neurodegeneration, and to assess individual cognitive differences in adults, but little is known about mechanical properties of the pediatric brain. Here we use high-resolution MRE imaging in participants of ages ranging from childhood to adulthood to understand brain mechanical properties across brain maturation. We find that brain mechanical properties differ considerably between childhood and adulthood, and that neuroanatomical subregions have differing maturational trajectories. Overall, we observe lower brain stiffness and greater brain damping ratio with increasing age from 5 to 35 years. Gray and white matter change differently during maturation, with larger changes occurring in gray matter for both stiffness and damping ratio. We also found that subregions of cortical and subcortical gray matter change differently, with the caudate and thalamus changing the most with age in both stiffness and damping ratio, while cortical subregions have different relationships with age, even between neighboring regions. Understanding how brain mechanical properties mature using high-resolution MRE will allow for a deeper understanding of the neural substrates supporting brain function at this age and can inform future studies of atypical maturation.

Linking the neural basis of distributional statistical learning with transitional statistical learning: The paradox of attention.

Statistical learning, the process of tracking distributional information and discovering embedded patterns, is traditionally regarded as a form of implicit learning. However, recent studies proposed that both implicit (attention-independent) and explicit (attention-dependent) learning systems are involved in statistical learning. To understand the role of attention in statistical learning, the current study investigates the cortical processing of distributional patterns in speech across local and global contexts. We then ask how these cortical responses relate to statistical learning behavior in a word segmentation task. We found Event-Related Potential (ERP) evidence of pre-attentive processing of both the local (mismatching negativity) and global distributional information (late discriminative negativity). However, as speech elements became less frequent and more surprising, some participants showed an involuntary attentional shift, reflected in a P3a response. Individuals who displayed attentive neural tracking of distributional information showed faster learning in a speech statistical learning task. These results suggest that an involuntary attentional shift might play a facilitatory, but not essential, role in statistical learning.

Temporal and topographical changes in theta power between middle childhood and adolescence during sentence comprehension.

Time frequency analysis of the EEG is increasingly used to study the neural oscillations supporting language comprehension. Although this method holds promise for developmental research, most existing work focuses on adults. Theta power (4-8 Hz) in particular often corresponds to semantic processing of words in isolation and in ongoing text. Here we investigated how the timing and topography of theta engagement to individual words during written sentence processing changes between childhood and adolescence (8-15 years). Results show that topographically, the theta response is broadly distributed in children, occurring over left and right central-posterior and midline frontal areas, and localizes to left central-posterior areas by adolescence. There were two notable developmental shifts. First, in response to each word, early (150-300 msec) theta engagement over frontal areas significantly decreases between 8 and 9 years and 10-11 years. Second, throughout the sentence, theta engagement over the right parietal areas significantly decreases between 10 and 11 years and 12-13 years with younger children's theta response remaining significantly elevated between words compared to adolescents'. We found no significant differences between 12 and 13 years and 14-15 years. These findings indicate that children's engagement of the language network during sentence processing continues to change through middle childhood but stabilizes into adolescence.