Learning non-adjacent regularities at age 0 ; 7

Functional reorganization of brain regions supporting artificial grammar learning across the first half year of life

Pre-babbling infants can track nonadjacent dependencies (NADs) in the auditory domain. While this forms a crucial prerequisite for language acquisition, the neurodevelopmental origins of this ability remain unknown. We applied functional near-infrared spectroscopy in neonates and 6- to 7-month-old infants to investigate the neural substrate supporting NAD learning and detection using tone sequences in an artificial grammar learning paradigm. Detection of NADs was indicated by left prefrontal activation in neonates while by left supramarginal gyrus (SMG), superior temporal gyrus (STG), and inferior frontal gyrus activation in 6- to 7-month-olds. Functional connectivity analyses further indicated that the neonate activation pattern during the test phase benefited from a brain network consisting of prefrontal regions, left SMG and STG during the rest and learning phases. These findings suggest a left-hemispheric learning-related functional brain network may emerge at birth and serve as the foundation for the later engagement of these regions for NAD detection, thus, providing a neural basis for language acquisition.

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.

Infants differentially extract rules from language

Infants readily extract linguistic rules from speech. Here, we ask whether this advantage extends to linguistic stimuli that do not rely on the spoken modality. To address this question, we first examine whether infants can differentially learn rules from linguistic signs. We show that, despite having no previous experience with a sign language, six-month-old infants can extract the reduplicative rule (AA) from dynamic linguistic signs, and the neural response to reduplicative linguistic signs differs from reduplicative visual controls, matched for the dynamic spatiotemporal properties of signs. We next demonstrate that the brain response for reduplicative signs is similar to the response to reduplicative speech stimuli. Rule learning, then, apparently depends on the linguistic status of the stimulus, not its sensory modality. These results suggest that infants are language-ready. They possess a powerful rule system that is differentially engaged by all linguistic stimuli, speech or sign.

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.

Non-adjacent Dependency Learning in Humans and Other Animals

Learning and processing natural language requires the ability to track syntactic relationships between words and phrases in a sentence, which are often separated by intervening material. These nonadjacent dependencies can be studied using artificial grammar learning paradigms and structured sequence processing tasks. These approaches have been used to demonstrate that human adults, infants and some nonhuman animals are able to detect and learn dependencies between nonadjacent elements within a sequence. However, learning nonadjacent dependencies appears to be more cognitively demanding than detecting dependencies between adjacent elements, and only occurs in certain circumstances. In this review, we discuss different types of nonadjacent dependencies in language and in artificial grammar learning experiments, and how these differences might impact learning. We summarize different types of perceptual cues that facilitate learning, by highlighting the relationship between dependent elements bringing them closer together either physically, attentionally, or perceptually. Finally, we review artificial grammar learning experiments in human adults, infants, and nonhuman animals, and discuss how similarities and differences observed across these groups can provide insights into how language is learned across development and how these language-related abilities might have evolved.

The profile of abstract rule learning in infancy: Meta-analytic and experimental evidence

Everyone agrees that infants possess general mechanisms for learning about the world, but the existence and operation of more specialized mechanisms is controversial. One mechanism-rule learning-has been proposed as potentially specific to speech, based on findings that 7-month-olds can learn abstract repetition rules from spoken syllables (e.g. ABB patterns: wo-fe-fe, ga-tu-tu…) but not from closely matched stimuli, such as tones. Subsequent work has shown that learning of abstract patterns is not simply specific to speech. However, we still lack a parsimonious explanation to tie together the diverse, messy, and occasionally contradictory findings in that literature. We took two routes to creating a new profile of rule learning: meta-analysis of 20 prior reports on infants' learning of abstract repetition rules (including 1,318 infants in 63 experiments total), and an experiment on learning of such rules from a natural, non-speech communicative signal. These complementary approaches revealed that infants were most likely to learn abstract patterns from meaningful stimuli. We argue that the ability to detect and generalize simple patterns supports learning across domains in infancy but chiefly when the signal is meaningfully relevant to infants' experience with sounds, objects, language, and people.

Statistical Learning of Melodic Patterns Influences the Brain's Response to Wrong Notes

The theory of statistical learning has been influential in providing a framework for how humans learn to segment patterns of regularities from continuous sensory inputs, such as speech and music. This form of learning is based on statistical cues and is thought to underlie the ability to learn to segment patterns of regularities from continuous sensory inputs, such as the transition probabilities in speech and music. However, the connection between statistical learning and brain measurements is not well understood. Here we focus on ERPs in the context of tone sequences that contain statistically cohesive melodic patterns. We hypothesized that implicit learning of statistical regularities would influence what was held in auditory working memory. We predicted that a wrong note occurring within a cohesive pattern (within-pattern deviant) would lead to a significantly larger brain signal than a wrong note occurring between cohesive patterns (between-pattern deviant), even though both deviant types were equally likely to occur with respect to the global tone sequence. We discuss this prediction within a simple Markov model framework that learns the transition probability regularities within the tone sequence. Results show that signal strength was stronger when cohesive patterns were violated and demonstrate that the transitional probability of the sequence influences the memory basis for melodic patterns. Our results thus characterize how informational units are stored in auditory memory trace for deviance detection and provide new evidence about how the brain organizes sequential sound input that is useful for perception.

Distributional learning of subcategories in an artificial grammar: Category generalization and subcategory restrictions

There has been significant recent interest in clarifying how learners use distributional information during language acquisition. Many researchers have suggested that distributional learning mechanisms play a major role during grammatical category acquisition, since linguistic form-classes (like noun and verb) and subclasses (like masculine and feminine grammatical gender) are primarily defined by the ways lexical items are distributed in syntactic contexts. Though recent experimental work has affirmed the importance of distributional information for category acquisition, there has been little evidence that learners can acquire linguistic subclasses based only on distributional cues. Across two artificial grammar-learning experiments, we demonstrate that subclasses can be acquired from distributional cues alone. These results add to a body of work demonstrating rational use of distributional information to acquire complex linguistic structures.

Finding words and word structure in artificial speech: the development of infants' sensitivity to morphosyntactic regularities

To achieve language proficiency, infants must find the building blocks of speech and master the rules governing their legal combinations. However, these problems are linked: words are also built according to rules. Here, we explored early morphosyntactic sensitivity by testing when and how infants could find either words or within-word structure in artificial speech snippets embodying properties of morphological constructions. We show that 12-month-olds use statistical relationships between syllables to extract words from continuous streams, but find word-internal regularities only if the streams are segmented. Seven-month-olds fail both tasks. Thus, 12-month-olds infants possess the resources to analyze the internal composition of words if the speech contains segmentation information. However, 7-month-old infants may not possess them, although they can track several statistical relations. This developmental difference suggests that morphosyntactic sensitivity may require computational resources extending beyond the detection of simple statistics.

Word categorization from distributional information: frames confer more than the sum of their (Bigram) parts

Grammatical categories, such as noun and verb, are the building blocks of syntactic structure and the components that govern the grammatical patterns of language. However, in many languages words are not explicitly marked with their category information, hence a critical part of acquiring a language is categorizing the words. Computational analyses of child-directed speech have shown that distributional information-information about how words pattern with one another in sentences-could be a useful source of initial category information. Yet questions remain as to whether learners use this kind of information, and if so, what kinds of distributional patterns facilitate categorization. In this paper we investigated how adults exposed to an artificial language use distributional information to categorize words. We compared training situations in which target words occurred in frames (i.e., surrounded by two words that frequently co-occur) against situations in which target words occurred in simpler bigram contexts (where an immediately adjacent word provides the context for categorization). We found that learners categorized words together when they occurred in similar frame contexts, but not when they occurred in similar bigram contexts. These findings are particularly relevant because they accord with computational investigations showing that frame contexts provide accurate category information cross-linguistically. We discuss these findings in the context of prior research on distribution-based categorization and the broader implications for the role of distributional categorization in language acquisition.

Separating acoustic deviance from novelty during the first year of life: a review of event-related potential evidence

Orienting to salient events in the environment is a first step in the development of attention in young infants. Electrophysiological studies have indicated that in newborns and young infants, sounds with widely distributed spectral energy, such as noise and various environmental sounds, as well as sounds widely deviating from their context elicit an event-related potential (ERP) similar to the adult P3a response. We discuss how the maturation of event-related potentials parallels the process of the development of passive auditory attention during the first year of life. Behavioral studies have indicated that the neonatal orientation to high-energy stimuli gradually changes to attending to genuine novelty and other significant events by approximately 9 months of age. In accordance with these changes, in newborns, the ERP response to large acoustic deviance is dramatically larger than that to small and moderate deviations. This ERP difference, however, rapidly decreases within first months of life and the differentiation of the ERP response to genuine novelty from that to spectrally rich but repeatedly presented sounds commences during the same period. The relative decrease of the response amplitudes elicited by high-energy stimuli may reflect development of an inhibitory brain network suppressing the processing of uninformative stimuli. Based on data obtained from healthy full-term and pre-term infants as well as from infants at risk for various developmental problems, we suggest that the electrophysiological indices of the processing of acoustic and contextual deviance may be indicative of the functioning of auditory attention, a crucial prerequisite of learning and language development.