How statistical learning interacts with the socioeconomic environment to shape children's language development.

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.

Distinct neural networks for detecting violations of adjacent versus nonadjacent sequential dependencies: An fMRI study.

The ability to learn and process sequential dependencies is essential for language acquisition and other cognitive domains. Recent studies suggest that the learning of adjacent (e.g., "A-B") versus nonadjacent (e.g., "A-X-B") dependencies have different cognitive demands, but the neural correlates accompanying such processing are currently underspecified. We developed a sequential learning task in which sequences of printed nonsense syllables containing both adjacent and nonadjacent dependencies were presented. After incidentally learning these grammatical sequences, twenty-one healthy adults (age M = 22.1, 12 females) made familiarity judgments about novel grammatical sequences and ungrammatical sequences containing violations of the adjacent or nonadjacent structure while in a 3T MRI scanner. Violations of adjacent dependencies were associated with increased BOLD activation in both posterior (lateral occipital and angular gyrus) as well as frontal regions (e.g., medial frontal gyrus, inferior frontal gyrus). Initial results indicated no regions showing significant BOLD activations for the violations of nonadjacent dependencies. However, when using a less stringent cluster threshold, exploratory analyses revealed that violations of nonadjacent dependencies were associated with increased activation in subcallosal cortex, paracingulate cortex, and anterior cingulate cortex (ACC). Finally, when directly comparing the adjacent condition to the nonadjacent condition, we found significantly greater levels of activation for the right superior lateral occipital cortex (BA 19) for the adjacent relative to nonadjacent condition. In sum, the detection of violations of adjacent and nonadjacent dependencies appear to involve distinct neural networks, with perceptual brain regions mediating the processing of adjacent but not nonadjacent dependencies. These results are consistent with recent proposals that statistical-sequential learning is not a unified construct but depends on the interaction of multiple neurocognitive mechanisms acting together.

Concurrent Learning of Adjacent and Nonadjacent Dependencies in Visuo-Spatial and Visuo-Verbal Sequences.

Both adjacent and non-adjacent dependencies (AD and NAD) are present in natural language and other domains, yet the learning of non-adjacent sequential dependencies generally only occurs under favorable circumstances. It is currently unknown to what extent adults can learn AD and NAD, presented concurrently in spatial and verbal sequences during a single session, and whether a second session improves performance. In addition, the relationship between AD and NAD learning and other theoretically related cognitive and language processes has not yet been fully established. In this study, participants reproduced two types of sequences generated from an artificial grammar: visuo-spatial sequences with stimuli presented in four spatial locations, and visuo-verbal sequences with printed syllables. Participants were tested for incidental learning by reproducing novel sequences, half consistent with the grammar and half containing violations of either AD or NAD. The procedure was repeated on a second day. Results showed that both AD and NAD were learned in both visuo-spatial and visuo-verbal tasks, although AD learning was better than NAD and learning of NAD decreased over time. Furthermore, NAD learning for both spatial and verbal tasks was positively correlated with a language measure, whereas AD learning for both spatial and verbal tasks was negatively associated with working memory measures in the opposite domain. These results demonstrate that adults can learn both AD and NAD within a single session, but NAD learning is more easily disrupted than AD and both types of learning are sub-served by partially distinct cognitive processes. These findings increase our understanding of the processes governing the learning of AD and NAD in verbal and spatial domains.

Visual sequential processing and language ability in children who are deaf or hard of hearing.

This study investigated the role of sequential processing in spoken language outcomes for children who are deaf or hard of hearing (DHH), ages 5;3-11;4, by comparing them to children with typical hearing (TH), ages 6;3-9;7, on sequential learning and memory tasks involving easily nameable and difficult-to-name visual stimuli. Children who are DHH performed more poorly on easily nameable sequencing tasks, which positively predicted receptive vocabulary scores. Results suggest sequential learning and memory may underlie delayed language skills of many children who are DHH. Implications for language development in children who are DHH are discussed.

The Role of Statistical Learning in Understanding and Treating Spoken Language Outcomes in Deaf Children With Cochlear Implants.

Purpose: Statistical learning-the ability to learn patterns in environmental input-is increasingly recognized as a foundational mechanism necessary for the successful acquisition of spoken language. Spoken language is a complex, serially presented signal that contains embedded statistical relations among linguistic units, such as phonemes, morphemes, and words, which represent the phonotactic and syntactic rules of language. In this review article, we first review recent work that demonstrates that, in typical language development, individuals who display better nonlinguistic statistical learning abilities also show better performance on different measures of language. We next review research findings that suggest that children who are deaf and use cochlear implants may have difficulties learning sequential input patterns, possibly due to auditory and/or linguistic deprivation early in development, and that the children who show better sequence learning abilities also display improved spoken language outcomes. Finally, we present recent findings suggesting that it may be possible to improve core statistical learning abilities with specialized training and interventions and that such improvements can potentially impact and facilitate the acquisition and processing of spoken language. Method: We conducted a literature search through various online databases including PsychINFO and PubMed, as well as including relevant review articles gleaned from the reference sections of other review articles used in this review. Search terms included various combinations of the following: sequential learning, sequence learning, statistical learning, sequence processing, procedural learning, procedural memory, implicit learning, language, computerized training, working memory training, statistical learning training, deaf, deafness, hearing impairment, hearing impaired, DHH, hard of hearing, cochlear implant(s), hearing aid(s), and auditory deprivation. To keep this review concise and clear, we limited inclusion to the foundational and most recent (2005-2018) relevant studies that explicitly included research or theoretical perspectives on statistical or sequential learning. We here summarize and synthesize the most recent and relevant literature to understanding and treating language delays in children using cochlear implants through the lens of statistical learning. Conclusions: We suggest that understanding how statistical learning contributes to spoken language development is important for understanding some of the difficulties that children who are deaf and use cochlear implants might face and argue that it may be beneficial to develop novel language interventions that focus specifically on improving core foundational statistical learning skills.

Deaf children with cochlear implants do not appear to use sentence context to help recognize spoken words.

PURPOSE: The authors investigated the ability of deaf children with cochlear implants (CIs) to use sentence context to facilitate the perception of spoken words. METHOD: Deaf children with CIs (n = 24) and an age-matched group of children with normal hearing (n = 31) were presented with lexically controlled sentences and were asked to repeat each sentence in its entirety. Performance was analyzed at each of 3 word positions of each sentence (first, second, and third key word). RESULTS: Whereas the children with normal hearing showed robust effects of contextual facilitation-improved speech perception for the final words in a sentence-the deaf children with CIs on average showed no such facilitation. Regression analyses indicated that for the deaf children with CIs, Forward Digit Span scores significantly predicted accuracy scores for all 3 positions, whereas performance on the Stroop Color and Word Test, Children's Version (Golden, Freshwater, & Golden, 2003) predicted how much contextual facilitation was observed at the final word. CONCLUSIONS: The pattern of results suggests that some deaf children with CIs do not use sentence context to improve spoken word recognition. The inability to use sentence context may be due to possible interactions between language experience and cognitive factors that affect the ability to successfully integrate temporal-sequential information in spoken language.

Cognition assessment using the NIH Toolbox.

Cognition is 1 of 4 domains measured by the NIH Toolbox for the Assessment of Neurological and Behavioral Function (NIH-TB), and complements modules testing motor function, sensation, and emotion. On the basis of expert panels, the cognition subdomains identified as most important for health, success in school and work, and independence in daily functioning were Executive Function, Episodic Memory, Language, Processing Speed, Working Memory, and Attention. Seven measures were designed to tap constructs within these subdomains. The instruments were validated in English, in a sample of 476 participants ranging in age from 3 to 85 years, with representation from both sexes, 3 racial/ethnic categories, and 3 levels of education. This report describes the development of the Cognition Battery and presents results on test-retest reliability, age effects on performance, and convergent and discriminant construct validity. The NIH-TB Cognition Battery is intended to serve as a brief, convenient set of measures to supplement other outcome measures in epidemiologic and longitudinal research and clinical trials. With a computerized format and national standardization, this battery will provide a "common currency" among researchers for comparisons across a wide range of studies and populations.