Second Language Experience Facilitates Statistical Learning of Novel Linguistic Materials

Dissociation Between Linguistic and Nonlinguistic Statistical Learning in Children with Autism

Statistical learning (SL), the ability to detect and extract regularities from inputs, is considered a domain-general building block for typical language development. We compared 55 verbal children with autism (ASD, 6-12 years) and 50 typically-developing children in four SL tasks. The ASD group exhibited reduced learning in the linguistic SL tasks (syllable and letter), but showed intact learning for the nonlinguistic SL tasks (tone and image). In the ASD group, better linguistic SL was associated with higher language skills measured by parental report and sentence recall. Therefore, the atypicality of SL in autism is not domain-general but tied to specific processing constraints related to verbal stimuli. Our findings provide a novel perspective for understanding language heterogeneity in autism.

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.

Sensitivity to word endings as probabilistic orthographic cues to lexical stress among English as second language learners

Assigning stress to polysyllabic words is a crucial aspect of reading aloud in English. Previous research demonstrated that native English speakers are sensitive to word endings as probabilistic orthographic cues to stress assignment. However, little is known about if second language (L2) learners of English are sensitive to word endings as cues to lexical stress. The current study investigated whether native Chinese-speakers learning English as a second language (ESL) are sensitive to word endings as probabilistic orthographic cues to lexical stress. Our ESL learners demonstrated sensitivity to word endings as cues in a stress-assignment task and a naming task. With the increase in language proficiency, ESL learners responded more accurately in the stress-assignment task. Moreover, stress position and language proficiency moderated the strength of the sensitivity, with a trochaic bias and better proficiency leading to better sensitivity in the stress-assignment task. However, as language proficiency increased, participants' naming speed became faster in iambic but slower in trochaic patterns, reflecting the learners' fledgling knowledge about the specific stress patterns associated with varying orthographic cues, especially in a demanding naming task. Taken together, the evidence from our ESL learners fits in the proposed statistical learning mechanism, that is, L2 learners are able to implicitly extract statistical regularities from linguistic materials, the orthographic cues to lexical stress in our study. Stress position and language proficiency both play a role in developing this sensitivity.

The Influence of Memory on Visual Perception in Infants, Children, and Adults

Perception is not an independent, in-the-moment event. Instead, perceiving involves integrating prior expectations with current observations. How does this ability develop from infancy through adulthood? We examined how prior visual experience shapes visual perception in infants, children, and adults. Using an identical task across age groups, we exposed participants to pairs of colorful stimuli and implicitly measured their ability to discriminate relative saturation levels. Results showed that adult participants were biased by previously experienced exemplars, and exhibited weakened in-the-moment discrimination between different levels of saturation. In contrast, infants and children showed less influence of memory in their perception, and they actually outperformed adults in discriminating between current levels of saturation. Our findings suggest that as humans develop, their perception relies more on prior experience and less on current observation.

Knowledge of Statistics or Statistical Learning? Readers Prioritize the Statistics of their Native Language Over the Learning of Local Regularities

A large body of evidence suggests that people spontaneously and implicitly learn about regularities present in the visual input. Although theorized as critical for reading, this ability has been demonstrated mostly with pseudo-fonts or highly atypical artificial words. We tested whether local statistical regularities are extracted from materials that more closely resemble one’s native language. In two experiments, Italian speakers saw a set of letter strings modelled on the Italian lexicon and guessed which of these strings were words in a fictitious language and which were foils. Unknown to participants, words could be distinguished from foils based on their average bigram frequency. Surprisingly, in both experiments, we found no evidence that participants relied on this regularity. Instead, lexical decisions were guided by minimal bigram frequency, a cue rooted in participants’ native language. We discuss the implications of these findings for accounts of statistical learning and visual word processing.

The Role of Stimulus-Specific Perceptual Fluency in Statistical Learning

Humans have the ability to learn surprisingly complicated statistical information in a variety of modalities and situations, often based on relatively little input. These statistical learning (SL) skills appear to underlie many kinds of learning, but despite their ubiquity, we still do not fully understand precisely what SL is and what individual differences on SL tasks reflect. Here, we present experimental work suggesting that at least some individual differences arise from stimulus‐specific variation in perceptual fluency: the ability to rapidly or efficiently code and remember the stimuli that SL occurs over. Experiment 1 demonstrates that participants show improved SL when the stimuli are simple and familiar; Experiment 2 shows that this improvement is not evident for simple but unfamiliar stimuli; and Experiment 3 shows that for the same stimuli (Chinese characters), SL is higher for people who are familiar with them (Chinese speakers) than those who are not (English speakers matched on age and education level). Overall, our findings indicate that performance on a standard SL task varies substantially within the same (visual) modality as a function of whether the stimuli involved are familiar or not, independent of stimulus complexity. Moreover, test–retest correlations of performance in an SL task using stimuli of the same level of familiarity (but distinct items) are stronger than correlations across the same task with stimuli of different levels of familiarity. Finally, we demonstrate that SL performance is predicted by an independent measure of stimulus‐specific perceptual fluency that contains no SL component at all. Our results suggest that a key component of SL performance may be related to stimulus‐specific processing and familiarity.

Phonetic Effects in Child and Adult Word Segmentation

Purpose The aim of the study was to investigate the effects of specific acoustic patterns on word learning and segmentation in 8- to 11-year-old children and in college students. Method Twenty-two children (ages 8;2-11;4 [years;months]) and 36 college students listened to synthesized "utterances" in artificial languages consisting of six iterated "words," which followed either a phonetically natural lenition-fortition pattern or an unnatural (cross-linguistically unattested) antilenition pattern. A two-alternative forced-choice task tested whether they could discriminate between occurring and nonoccurring sequences. Participants were exposed to both languages, counterbalanced for order across subjects, in sessions spaced at least 1 month apart. Results Children showed little evidence for learning in either the phonetically natural or unnatural condition nor evidence of differences in learning across the two conditions. Adults showed the predicted (and previously attested) interaction between learning and phonetic condition: The phonetically natural language was learned better. The adults also showed a strong effect of session: Subjects performed much worse during the second session than the first. Conclusions School-age children not only failed to demonstrate the phonetic asymmetry demonstrated by adults in previous studies but also failed to show strong evidence for any learning at all. The fact that the phonetic asymmetry (and general learning effect) was replicated with adults suggests that the child result is not due to inadequate stimuli or procedures. The strong carryover effect for adults also suggests that they retain knowledge about the sound patterns of an artificial language for over a month, longer than has been reported in laboratory studies of purely phonetic/phonological learning. Supplemental Material https://doi.org/10.23641/asha.13641284.

Tuning in to non-adjacencies: Exposure to learnable patterns supports discovering otherwise difficult structures

Non-adjacent dependencies are ubiquitous in language, but difficult to learn in artificial language experiments in the lab. Previous research suggests that non-adjacent dependencies are more learnable given structural support in the input - for instance, in the presence of high variability between dependent items. However, not all non-adjacent dependencies occur in supportive contexts. How are such regularities learned? One possibility is that learning one set of non-adjacent dependencies can highlight similar structures in subsequent input, facilitating the acquisition of new non-adjacent dependencies that are otherwise difficult to learn. In three experiments, we show that prior exposure to learnable non-adjacent dependencies - i.e., dependencies presented in a learning context that has been shown to facilitate discovery - improves learning of novel non-adjacent regularities that are typically not detected. These findings demonstrate how the discovery of complex linguistic structures can build on past learning in supportive contexts.

Plasticity in second language learning: The case of Mandarin tones

Adults typically struggle to perceive non-native sound contrasts, especially those that conflict with their first language. Do the same challenges persist when the sound contrasts overlap but do not conflict? To address this question, we explored the acquisition of lexical tones. While tonal variations are present in many languages, they are only used contrastively in tonal languages. We investigated the perception of Mandarin tones by adults with differing experience with Mandarin, including naïve listeners, classroom learners, and native speakers. Naïve listeners discriminated Mandarin tones at above-chance levels, and performance significantly improved after just one month of classroom exposure. Additional evidence for plasticity came from advanced classroom learners, whose tonemic perception was indistinguishable from that of native speakers. The results suggest that unlike many other non-native contrasts, adults studying a language in the classroom can readily acquire the perceptual skills needed to discriminate Mandarin tones.

The prevalence and importance of statistical learning in human cognition and behavior

Statistical learning, the ability to extract regularities from the environment over time, has become a topic of burgeoning interest. Its influence on behavior, spanning infancy to adulthood, has been demonstrated across a range of tasks, both those labeled as tests of statistical learning and those from other learning domains that predated statistical learning research or that are not typically considered in the context of that literature. Given this pervasive role in human cognition, statistical learning has the potential to reconcile seemingly distinct learning phenomena and may be an under-appreciated but important contributor to a wide range of human behaviors that are studied as unrelated processes, such as episodic memory and spatial navigation.

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.

Statistical learning as a window into developmental disabilities

Until recently, most behavioral studies of children with intellectual and developmental disabilities (IDD) have used standardized assessments as a means to probe etiology and to characterize phenotypes. Over the past decade, however, tasks originally developed to investigate learning processes in typical development have been brought to bear on developmental processes in children with IDD.

This brief review will focus on one learning process in particular—statistical learning—and will provide an overview of what has been learned thus far from studies using statistical learning tasks with different groups of children with IDD conditions. While a full picture is not yet available, results to date suggest that studies of learning are both feasible and informative about learning processes that may differ across diagnostic groups, particularly as they relate to language acquisition.

More generally, studies focused on learning processes may be highly informative about different developmental trajectories both across groups and within groups of children.

Infant Statistical Learning

Perception involves making sense of a dynamic, multimodal environment. In the absence of mechanisms capable of exploiting the statistical patterns in the natural world, infants would face an insurmountable computational problem. Infant statistical learning mechanisms facilitate the detection of structure. These abilities allow the infant to compute across elements in their environmental input, extracting patterns for further processing and subsequent learning. In this selective review, we summarize findings that show that statistical learning is both a broad and flexible mechanism (supporting learning from different modalities across many different content areas) and input specific (shifting computations depending on the type of input and goal of learning). We suggest that statistical learning not only provides a framework for studying language development and object knowledge in constrained laboratory settings, but also allows researchers to tackle real-world problems, such as multilingualism, the role of ever-changing learning environments, and differential developmental trajectories.

Statistical learning of speech sounds is most robust during the period of perceptual attunement

Although statistical learning has been shown to be a domain-general mechanism, its constraints, such as its interactions with perceptual development, are less well understood and discussed. This study is among the first to investigate the distributional learning of lexical pitch in non-tone-language-learning infants, exploring its interaction with language-specific perceptual attunement during the first 2years after birth. A total of 88 normally developing Dutch infants of 5, 11, and 14months were tested via a distributional learning paradigm and were familiarized on a unimodal or bimodal distribution of high-level versus high-falling tones in Mandarin Chinese. After familiarization, they were tested on a tonal contrast that shared equal distributional information in either modality. At 5months, infants in both conditions discriminated the contrast, whereas 11-month-olds showed discrimination only in the bimodal condition. By 14months, infants failed to discriminate the contrast in either condition. Results indicate interplay between infants' long-term linguistic experience throughout development and short-term distributional learning during the experiment, and they suggest that the influence of tonal distributional learning varies along the perceptual attunement trajectory, such that opportunities for distributional learning effects appear to be constrained in the beginning and at the end of perceptual attunement. The current study contributes to previous research by demonstrating an effect of age on learning from distributional cues.