Learning Of Nonadjacent Dependencies Research Articles

Dynamic Motion and Human Agents Facilitate Visual Nonadjacent Dependency Learning.

Many events that humans and other species experience contain regularities in which certain elements within an event predict certain others. While some of these regularities involve tracking the co-occurrences between temporally adjacent stimuli, others involve tracking the co-occurrences between temporally distant stimuli (i.e., nonadjacent dependencies, NADs). Prior research shows robust learning of adjacent dependencies in humans and other species, whereas learning NADs is more difficult, and often requires support from properties of the stimulus to help learners notice the NADs. Here, we report on seven experiments that examined NAD learning from various types of visual stimuli, exploring the effects of dynamic motion on adults' NAD learning from visual sequences involving human and nonhuman agents. We tested adults' NAD learning from visual sequences of human actions, object transformations, static images of human postures, and static images of an object in different postures. We found that dynamic motion aids the acquisition of NADs. We also found that learning NADs in sequences involving human agents is more robust compared to sequences involving nonhuman objects. We propose that dynamic motion and human agents both independently result in richer representations that provide a stronger signal for NADlearning.

Non-adjacent dependency learning from variable input: investigating the effects of bilingualism, phonological memory, and cognitive control.

One proposed advantage of bilingualism concerns the ability to extract regularities based on frequency information (statistical learning). Specifically, it has been proposed that bilinguals have an advantage in statistical learning that particularly holds in situations of variable input. Empirical evidence on this matter is scarce. An additional question is whether a potential bilingual advantage in statistical learning can be attributed to enhancements in phonological memory and cognitive control. Previous findings on effects of bilingualism on phonological memory and cognitive control are not consistent. In the present study, we compared statistical learning from consistent and variable input in monolingual and bilingual children (Study 1) and adults (Study 2). We also explored whether phonological memory and cognitive control might account for any potential group differences found. The findings suggest that there might be some advantage of bilinguals in statistical learning, but that this advantage is not robust: It largely surfaced only in t-tests against chance for the groups separately, did not surface in the same way for children and adults, and was modulated by experiment order. Furthermore, our results provide no evidence that any enhancement in bilinguals' statistical learning was related to improved phonological memory and cognitive control: bilinguals did not outperform monolinguals on these cognitive measures and performance on these measures did not consistently relate to statistical learning outcomes. Taken together, these findings suggest that any potential effects of bilingualism on statistical learning probably do not involve enhanced cognitive abilities associated with bilingualism.

Memory for nonadjacent dependencies in the first year of life and its relation to sleep

Grammar learning requires memory for dependencies between nonadjacent elements in speech. Immediate learning of nonadjacent dependencies has been observed in very young infants, but their memory of such dependencies has remained unexplored. Here we used event-related potentials to investigate whether 6- to 8-month-olds retain nonadjacent dependencies and if sleep after learning affects this memory. Infants were familiarised with two rule-based morphosyntactic dependencies, presented in sentences of an unknown language. Brain responses after a retention period reveal memory of the nonadjacent dependencies, independent of whether infants napped or stayed awake. Napping, however, altered a specific processing stage, suggesting that memory evolves during sleep. Infants with high left frontal spindle activity show an additional brain response indicating memory of individual speech phrases. Results imply that infants as young as 6 months are equipped with memory mechanisms relevant to grammar learning. They also suggest that during sleep, consolidation of highly specific information can co-occur with changes in the nature of generalised memory.

Spike-based statistical learning explains human performance in non-adjacent dependency learning tasks

Grammar acquisition is of significant importance for mastering human language. As the language signal is sequential in its nature, it poses the challenging task to extract its structure during online processing. This modeling study shows how spike-timing dependent plasticity (STDP) successfully enables sequence learning of artificial grammars that include non-adjacent dependencies (NADs) and nested NADs. Spike-based statistical learning leads to synaptic representations that comply with human acquisition performances under various distributional stimulus conditions. STDP, therefore, represents a practicable neural mechanism underlying human statistical grammar learning. These findings highlight that initial stages of the language acquisition process are possibly based on associative learning strategies. Moreover, the applicability of STDP demonstrates that the non-human brain possesses potential precursor abilities that support the acquisition of linguistic structure.

No need to forget, just keep the balance: Hebbian neural networks for statistical learning

Language processing in humans has long been proposed to rely on sophisticated learning abilities including statistical learning. Endress and Johnson (E&J, 2021) recently presented a neural network model for statistical learning based on Hebbian learning principles. This model accounts for word segmentation tasks, one primary paradigm in statistical learning. In this discussion paper we review this model and compare it with the Hebbian model previously presented by Tovar and Westermann (T&W, 2017a; 2017b; 2018) that has accounted for serial reaction time tasks, cross-situational learning, and categorization paradigms, all relevant in the study of statistical learning. We discuss the similarities and differences between both models, and their key findings. From our analysis, we question the concept of “forgetting” in the model of E&J and their suggestion of considering forgetting as the critical ingredient for successful statistical learning. We instead suggest that a set of simple but well-balanced mechanisms including spreading activation, activation persistence, and synaptic weight decay, all based on biologically grounded principles, allow modeling statistical learning in Hebbian neural networks, as demonstrated in the T&W model which successfully covers learning of nonadjacent dependencies and accounts for differences between typical and atypical populations, both aspects that have not been fully demonstrated in the E&J model. We outline the main computational and theoretical differences between the E&J and T&W approaches, present new simulation results, and discuss implications for the development of a computational cognitive theory of statistical learning.

A Special Role of Syllables, But Not Vowels or Consonants, for Nonadjacent Dependency Learning.

Successful language processing entails tracking (morpho)syntactic relationships between distant units of speech, so-called nonadjacent dependencies (NADs). Many cues to such dependency relations have been identified, yet the linguistic elements encoding them have received little attention. In the present investigation, we tested whether and how these elements, here syllables, consonants, and vowels, affect behavioral learning success as well as learning-related changes in neural activity in relation to item-specific NAD learning. In a set of two EEG studies with adults, we compared learning under conditions where either all segment types (Experiment 1) or only one segment type (Experiment 2) was informative. The collected behavioral and ERP data indicate that, when all three segment types are available, participants mainly rely on the syllable for NAD learning. With only one segment type available for learning, adults also perform most successfully with syllable-based dependencies. Although we find no evidence for successful learning across vowels in Experiment 2, dependencies between consonants seem to be identified at least passively at the phonetic-feature level. Together, these results suggest that successful item-specific NAD learning may depend on the availability of syllabic information. Furthermore, they highlight consonants' distinctive power to support lexical processes. Although syllables show a clear facilitatory function for NAD learning, the underlying mechanisms of this advantage require further research.

Statistical learning in children with a family risk of dyslexia.

The assumption that statistical learning is affected in dyslexia has generally been evaluated in children and adults with diagnosed dyslexia, not in pre‐literate children with a family risk (FR) of dyslexia. In this study, four‐to‐five‐year‐old FR children (n = 25) and No‐FR children (n = 33) completed tasks of emerging literacy (phoneme awareness and RAN). They also performed an online non‐adjacent dependency learning (NADL) task, based on the Serial Reaction Time (SRT) task paradigm. Children's accuracy (hits), signal sensitivity (d′) and reaction times were measured. The FR group performed marginally more poorly on phoneme awareness and significantly more poorly on RAN than the No‐FR group. Regarding NADL outcomes, the results were less straightforward: the data suggested successful statistical learning for both groups, as indicated by the hit and reaction time curves found. However, the FR group was less accurate and slower on the task than the No‐FR group. Furthermore, unlike the No‐FR group, performance in the FR group varied as a function of the specific stimulus presented. Taken together, these findings fail to show a robust difference in statistical learning between children with and without an FR of dyslexia at preschool age, in line with earlier work on older children and adults with dyslexia.

Children's Learning of Non-adjacent Dependencies Using a Web-Based Computer Game Setting.

Infants show impressive speech decoding abilities and detect acoustic regularities that highlight the syntactic relations of a language, often coded via non-adjacent dependencies (NADs, e.g., is singing). It has been claimed that infants learn NADs implicitly and associatively through passive listening and that there is a shift from effortless associative learning to a more controlled learning of NADs after the age of 2 years, potentially driven by the maturation of the prefrontal cortex. To investigate if older children are able to learn NADs, Lammertink et al. (2019) recently developed a word-monitoring serial reaction time (SRT) task and could show that 6–11-year-old children learned the NADs, as their reaction times (RTs) increased then they were presented with violated NADs. In the current study we adapted their experimental paradigm and tested NAD learning in a younger group of 52 children between the age of 4–8 years in a remote, web-based, game-like setting (whack-a-mole). Children were exposed to Italian phrases containing NADs and had to monitor the occurrence of a target syllable, which was the second element of the NAD. After exposure, children did a “Stem Completion” task in which they were presented with the first element of the NAD and had to choose the second element of the NAD to complete the stimuli. Our findings show that, despite large variability in the data, children aged 4–8 years are sensitive to NADs; they show the expected differences in r RTs in the SRT task and could transfer the NAD-rule in the Stem Completion task. We discuss these results with respect to the development of NAD dependency learning in childhood and the practical impact and limitations of collecting these data in a web-based setting.

Nonhuman primates learn adjacent dependencies but fail to learn nonadjacent dependencies in a statistical learning task with a salient cue.

There is ample evidence that humans and nonhuman animals can learn complex statistical regularities presented within various types of input. However, humans outperform their nonhuman primate counterparts when it comes to recognizing relationships that exist across one or several intervening stimuli (nonadjacent dependencies). This is especially true when the two elements in the dependency do not share any perceptual similarity (arbitrary associations). In the present study, we investigated whether manipulating the saliency of the predictive stimulus would enhance nonadjacent dependency learning in nonhuman primates. Rhesus macaques and tufted capuchins engaged in a computerized signal detection task that included sequences that were random in nature, included an adjacent dependency, or included a nonadjacent dependency. We manipulated the saliency of the predictive stimulus, such that the predictor jittered in place on the screen in some grammar blocks, as well as the transitional probability (the likelihood of the stimulus preceding the target to accurately predict the target's appearance) from block to block. Some monkeys evidenced learning of adjacent dependencies by faster response times to targets that followed a predictive stimulus compared to targets that were not preceded by a predictor. However, consistent with the body of evidence that indicates that nonhuman animals' statistical learning mechanisms are not at the same level of sophistication as humans', there was no evidence that monkeys learned nonadjacent dependencies of arbitrary associations, even when the salient cue was present.

Gradual development of non-adjacent dependency learning during early childhood

In order to become proficient native speakers, children have to learn the morpho-syntactic relations between distant elements in a sentence, so-called non-adjacent dependencies (NADs). Previous research suggests that NAD learning in children comprises different developmental stages, where until 2 years of age children are able to learn NADs associatively under passive listening conditions, while starting around the age of 3–4 years children fail to learn NADs during passive listening. To test whether the transition between these developmental stages occurs gradually, we tested children’s NAD learning in a foreign language using event-related potentials (ERPs). We found ERP evidence of NAD learning across the ages of 1, 2 and 3 years. The amplitude of the ERP effect indexing NAD learning, however, decreased with age. These findings might indicate a gradual transition in children’s ability to learn NADs associatively. Cognitively, this transition might be driven by children’s increasing knowledge of their native language, hindering NAD learning in novel contexts. Neuroanatomically, maturation of the prefrontal cortex might play a crucial role, promoting top-down learning, affecting bottom-up, associative learning. In sum, our study suggests that NAD learning under passive listening conditions undergoes a gradual transition between different developmental stages during early childhood.

Learning non-adjacent rules and non-adjacent dependencies from human actions in 9-month-old infants.

Seven month old infants can learn simple repetition patterns, such as we-fo-we, and generalize the rules to sequences of new syllables, such as ga-ti-ga. However, repetition rule learning in visual sequences seems more challenging, leading some researchers to claim that this type of rule learning applies preferentially to communicative stimuli. Here we demonstrate that 9-month-old infants can learn repetition rules in sequences of non-communicative dynamic human actions. We also show that when primed with these non-adjacent repetition patterns, infants can learn non-adjacent dependencies that involve memorizing the dependencies between specific human actions—patterns that prior research has shown to be difficult for infants in the visual domain and in speech. We discuss several possible mechanisms that account for the apparent advantage stimuli involving human action sequences has over other kinds of stimuli in supporting non-adjacent dependency learning. We also discuss possible implications for theories of language acquisition.

Concurrent visual learning of adjacent and nonadjacent dependencies in adults and children.

Concurrent learning of adjacent and nonadjacent dependencies has been shown in adults only. This study extended this line of research by examining dependency-specific learning for both adjacent and nonadjacent dependencies concurrently in both adults and children. Seventy adults aged 18 to 64 (40 women, 30 men; Experiment 1) and 64 children aged 10 to 11 years (40 girls, 24 boys; Experiment 2) were tested with a new serial reaction time (SRT) task in which they were trained for 5-8 min on materials comprising equally probable adjacent and nonadjacent dependencies. They were then asked to discriminate between trained and untrained dependencies in a familiarity task. Both adults and children showed implicit concurrent learning of both adjacent and nonadjacent dependencies. The two dependency types were learned to the same extent. However, adults showed a rapid, sustainable, and dependency-specific sensitivity throughout the SRT task while children only showed a dependency-specific sensitivity to violations of expectations after exposure. When the two groups were statistically compared, only adults showed a dependency-specific learning effect after exposure. These findings are in line with the age-related improvement model of dependency learning. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Grammatical performance in children with dyslexia: the contributions of individual differences in phonological memory and statistical learning

AbstractSeveral studies have signaled grammatical difficulties in individuals with developmental dyslexia. These difficulties may stem from a phonological deficit, but may alternatively be explained through a domain-general deficit in statistical learning. This study investigates grammar in children with and without dyslexia, and whether phonological memory and/or statistical learning ability contribute to individual differences in grammatical performance. We administered the CELF “word structure” and “recalling sentences” subtests and measures of phonological memory (digit span, nonword repetition) and statistical learning (serial reaction time, nonadjacent dependency learning) among 8- to 11-year-old children with and without dyslexia (N = 50 per group). Consistent with previous findings, our results show subtle difficulties in grammar, as children with dyslexia achieved lower scores on the CELF (word structure: p = .0027, recalling sentences: p = .053). While the two phonological memory measures were found to contribute to individual differences in grammatical performance, no evidence for a relationship with statistical learning was found. An error analysis revealed errors in irregular morphology (e.g., plural and past tense), suggesting problems with lexical retrieval. These findings are discussed in light of theoretical accounts of the underlying deficit in dyslexia.

Linguistic and non-linguistic non-adjacent dependency learning in early development

Non-adjacent dependencies (NADs) are important building blocks for language and extracting them from the input is a fundamental part of language acquisition. Prior event-related potential (ERP) studies revealed changes in the neural signature of NAD learning between infancy and adulthood, suggesting a developmental shift in the learning route for NADs. The present study aimed to specify which brain regions are involved in this developmental shift and whether this shift extends to NAD learning in the non-linguistic domain. In two experiments, 2- and 3-year-old German-learning children were familiarized with either Italian sentences or tone sequences containing NADs and subsequently tested with NAD violations, while functional near-infrared spectroscopy (fNIRS) data were recorded. Results showed increased hemodynamic responses related to the detection of linguistic NAD violations in the left temporal, inferior frontal, and parietal regions in 2-year-old children, but not in 3-year-old children. A different developmental trajectory was found for non-linguistic NADs, where 3-year-old, but not 2-year-old children showed evidence for the detection of non-linguistic NAD violations. These results confirm a developmental shift in the NAD learning route and point to distinct mechanisms underlying NAD learning in the linguistic and the non-linguistic domain.

When less is more: Enhanced statistical learning of non-adjacent dependencies after disruption of bilateral DLPFC

Abstract Brain networks related to human learning can interact in cooperative but also competitive ways to optimize performance. The investigation of learning and memory processes in a competitive framework is still rare. Previous studies have shown that manipulations reducing the engagement of prefrontal cortical areas could lead to improved statistical learning performance. However, no study has investigated how disruption of the dorsolateral prefrontal cortex (DLPFC) affects the acquisition and consolidation of non-adjacent second-order dependencies. The present study aimed to test the role of the DLPFC, more specifically, the Brodmann 9 area in implicit temporal statistical learning of non-adjacent dependencies. We applied 1 Hz inhibitory transcranial magnetic stimulation or sham stimulation over both the left and right DLPFC intermittently during the learning. The DLPFC-stimulated group showed better performance compared to the sham group after a 24-hour consolidation period. This finding suggests that the disruption of DLPFC during learning induces qualitative changes in the consolidation of non-adjacent statistical regularities. A possible mechanism behind this result is that the stimulation of the DLPFC promotes a shift to model-free learning by weakening the access to model-based processes.

통계적 학습 능력이 한국어 학습자의 인접ㆍ비인접 통사구조 처리ㆍ학습에 미치는 영향

본 연구에서는 이해 기반 구조적 점화 패러다임을 사용하여 성인 한국어 학습자가 인접 통사구조인 수여구문과 비인접 통사구조인 관형절 문장에 노출된 뒤 후속문장에 대한 처리에 어떤 양상을 나타내는지 살펴보고, 이들의 통계적 학습 능력이 L2 통사구조의 암시적 학습과 처리 효율성에 어떤 영향을 미치는지를 규명했다. 아울러 인접구조와 비인접구조에 대한 한국어 학습자의 통계적 학습 능력이 인접 L2 통사구조와 비인접 L2 통사구조의 처리․학습에 차별적으로 영향을 미치는지 여부 또한 고찰했다. 한국어 학습자 39명을 대상으로 이해 기반 구조적 점화 실험을 실시한 결과, 어휘 의존적 점화와 어휘 독립적 점화 모두 관찰되지 않았다. 그러나 인접구조에 대한 통계적 학습 능력은 인접 L2 통사구조 표적문장 이해 정확도를 예측해주었으며, 비인접구조에 대한 통계적 학습 능력은 인접․비인접 L2 통사구조 표적문장에 대한 처리 효율성과 이해 정확도를 예측해주었다. 이는 성인 L2 학습자의 인접․비인접 구조에 대한 통계적 학습 능력이 각각 그에 상응하는 인접․비인접 L2 통사구조의 처리 효율성을 촉진하는 데 기여함을 시사한다.

Non-adjacent dependency learning in infancy, and its link to language development

To acquire language, infants must learn how to identify words and linguistic structure in speech. Statistical learning has been suggested to assist both of these tasks. However, infants’ capacity to use statistics to discover words and structure together remains unclear. Further, it is not yet known how infants’ statistical learning ability relates to their language development. We trained 17-month-old infants on an artificial language comprising non-adjacent dependencies, and examined their looking times on tasks assessing sensitivity to words and structure using an eye-tracked head-turn-preference paradigm. We measured infants’ vocabulary size using a Communicative Development Inventory (CDI) concurrently and at 19, 21, 24, 25, 27, and 30 months to relate performance to language development. Infants could segment the words from speech, demonstrated by a significant difference in looking times to words versus part-words. Infants’ segmentation performance was significantly related to their vocabulary size (receptive and expressive) both currently, and over time (receptive until 24 months, expressive until 30 months), but was not related to the rate of vocabulary growth. The data also suggest infants may have developed sensitivity to generalised structure, indicating similar statistical learning mechanisms may contribute to the discovery of words and structure in speech, but this was not related to vocabulary size.

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.

Statistical learning abilities of children with dyslexia across three experimental paradigms.

Statistical learning (SL) difficulties have been suggested to contribute to the linguistic and non-linguistic problems observed in children with dyslexia. Indeed, studies have demonstrated that children with dyslexia experience problems with SL, but the extent of the problems is unclear. We aimed to examine the performance of children with and without dyslexia across three distinct paradigms using both on- and offline measures, thereby tapping into different aspects of SL. 100 children with and without dyslexia (aged 8–11, 50 per group) completed three SL tasks: serial reaction time (SRT), visual statistical learning (VSL), and auditory nonadjacent dependency learning (A-NADL). Learning was measured through online reaction times during exposure in all tasks, and through offline questions in the VSL and A-NADL tasks. We find significant learning effects in all three tasks, from which we conclude that, collapsing over groups, children are sensitive to the statistical structures presented in the SRT, VSL and A-NADL tasks. No significant interactions of learning effect with group were found in any of the tasks, so we cannot conclude whether or not children with dyslexia perform differently on the SL tasks than their TD peers. These results are discussed in light of the proposed SL deficit in dyslexia.

Successfully learning non-adjacent dependencies in a continuous artificial language stream

Much of the statistical learning literature has focused on adjacent dependency learning, which has shown that learners are capable of extracting adjacent statistics from continuous language streams. In contrast, studies on non-adjacent dependency learning have mixed results, with some showing success and others failure. We review the literature on non-adjacent dependency learning and examine various theories proposed to account for these results, including the proposed necessity of the presence of pauses in the learning stream, or proposals regarding competition between adjacent and non-adjacent dependency learning such that high variability of middle elements is beneficial to learning. Here we challenge those accounts by showing successful learning of non-adjacent dependencies under conditions that are inconsistent with predictions of previous theories. We show that non-adjacent dependencies are learnable without pauses at dependency edges in a variety of artificial language designs. Moreover, we find no evidence of a relationship between non-adjacent dependency learning and the robustness of adjacent statistics. We demonstrate that our two-step statistical learning model can account for all of our non-adjacent dependency learning results, and provides a unified learning account of adjacent and non-adjacent dependency learning. Finally, we discussed the theoretical implications of our findings for natural language acquisition, and argue that the dependency learning process can be a precursor to other language acquisition tasks that are vital to natural language acquisition.