Similar Neural Correlates for Language and Sequential Learning: Evidence from Event-Related Brain Potentials

Are the P600 and P3 ERP components linked to the task-evoked pupillary response as a correlate of norepinephrine activity?

During language comprehension, anomalies and ambiguities in the input typically elicit the P600 event-related potential component. Although traditionally interpreted as a specific signal of combinatorial operations in sentence processing, the component has alternatively been proposed to be a variant of the oddball-sensitive, domain-general P3 component. In particular, both components might reflect phasic norepinephrine release from the locus coeruleus (LC/NE) to motivationally significant stimuli. In this preregistered study, we tested this hypothesis by relating both components to the task-evoked pupillary response, a putative biomarker of LC/NE activity. 36 participants completed a sentence comprehension task (containing 25% morphosyntactic violations) and a non-linguistic oddball task (containing 20% oddballs), while the EEG and pupil size were co-registered. Our results showed that the task-evoked pupillary response and the ERP amplitudes of both components were similarly affected by both experimental tasks. In the oddball task, there was also a temporally specific relationship between the P3 and the pupillary response beyond the shared oddball effect, thereby further linking the P3 to NE. Because this link was less reliable in the linguistic context, we did not find conclusive evidence for or against a relationship between the P600 and the pupillary response. Still, our findings further stimulate the debate on whether language-related ERPs are indeed specific to linguistic processes or shared across cognitive domains. However, further research is required to verify a potential link between the two ERP positivities and the LC/NE system as the common neural generator.

General cognitive processing for orthographic discrepancy engages foveal attention during sentence comprehension

Words are processed in the parafovea and fovea in succession during natural reading, but the classic rapid serial visual presentation (RSVP) paradigm presents words only in the fovea. Unlike the RSVP paradigm, the RSVP with flanker (RSVP-flanker) paradigm is similar to natural text reading. Previous studies using the RSVP-flanker paradigm have suggested that high-level semantic/syntactic integration engages foveal fixation after parafoveal semantic access. However, it is less clear how general cognitive processing, such as discrepancy monitoring and error correction, unfolds across the parafoveal and foveal visual fields. In the current study, Chinese sentences were presented with the RSVP-flanker paradigm. Critical words were manipulated so that they were expected (EXP), semantically violated (VIO), or orthographically similar (ORT). Because of the nuanced differences between the EXP and ORT conditions, the processing of ORT critical words required more general cognitive processing, such as discrepancy monitoring and error correction. In contrast, the processing of VIO words may require more semantic integration. The ERP results showed more positive foveal late positive component (LPC) in ORT versus VIO. Moreover, there was no parafoveal LPC effect, but a robust foveal LPC effect, in the contrasts of VIO/ORT versus EXP, replicating previous results. Together, the results provide substantial evidence that general cognitive processing for orthographic discrepancy occurs at the foveal perception.

Intact predictive processing in autistic adults: evidence from statistical learning

Impairment in predictive processes gained a lot of attention in recent years as an explanation for autistic symptoms. However, empirical evidence does not always underpin this framework. Thus, it is unclear what aspects of predictive processing are affected in autism spectrum disorder. In this study, we tested autistic adults on a task in which participants acquire probability-based regularities (that is, a statistical learning task). Twenty neurotypical and 22 autistic adults learned a probabilistic, temporally distributed regularity for about 40 min. Using frequentist and Bayesian methods, we found that autistic adults performed comparably to neurotypical adults, and the dynamics of learning did not differ between groups either. Thus, our study provides evidence for intact statistical learning in autistic adults. Furthermore, we discuss potential ways this result can extend the scope of the predictive processing framework, noting that atypical processing might not always mean a deficit in performance.

Reading fluency and statistical learning across modalities and domains: Online and offline measures

The vulnerability of statistical learning has been demonstrated in reading difficulties in both the visual and acoustic modalities. We examined segmentation abilities of Hungarian speaking adolescents with different levels of reading fluency in the acoustic verbal and visual nonverbal domains. We applied online target detection tasks, where the extent of learning is reflected in differences between reaction times to predictable versus unpredictable targets. Explicit judgments of well-formedness were also elicited in an offline two-alternative forced choice (2AFC) task. Learning was evident in both the acoustic verbal and visual nonverbal tasks, both in online and offline measures, but learning effects were larger both in online and offline tasks in the verbal acoustic condition. We haven’t found evidence for a significant relationship between statistical learning and reading fluency in adolescents in either modality. Together with earlier findings, these results suggest that the relationship between reading and statistical learning is dependent on the domain, modality and nature of the statistical learning task, on the reading task, on the age of participants, and on the specific language. The online target detection task is a promising tool which can be adapted to a wider set of tasks to further explore the contribution of statistical learning to reading acquisition in participants from different populations.

Modality, presentation, domain and training effects in statistical learning

While several studies suggest that the nature and properties of the input have significant effects on statistical learning, they have rarely been investigated systematically. In order to understand how input characteristics and their interactions impact statistical learning, we explored the effects of modality (auditory vs. visual), presentation type (serial vs. simultaneous), domain (linguistic vs. non-linguistic), and training type (random, starting small, starting big) on artificial grammar learning in young adults (N = 360). With serial presentation of stimuli, learning was more effective in the auditory than in the visual modality. However, with simultaneous presentation of visual and serial presentation of auditory stimuli, the modality effect was not present. We found a significant domain effect as well: a linguistic advantage over nonlinguistic material, which was driven by the domain effect in the auditory modality. Overall, the auditory linguistic condition had an advantage over other modality-domain types. Training types did not have any overall effect on learning; starting big enhanced performance only in the case of serial visual presentation. These results show that input characteristics such as modality, presentation type, domain and training type influence statistical learning, and suggest that their effects are also dependent on the specific stimuli and structure to be learned.

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.

Unraveling the Interconnections Between Statistical Learning and Dyslexia: A Review of Recent Empirical Studies

One important aspect of human cognition involves the learning of structured information encountered in our environment, a phenomenon known as statistical learning. A growing body of research suggests that learning to read print is partially guided by learning the statistical contingencies existing between the letters within a word, and also between the letters and sounds to which the letters refer. Research also suggests that impairments to statistical learning ability may at least partially explain the difficulties experienced by individuals diagnosed with dyslexia. However, the findings regarding impaired learning are not consistent, perhaps partly due to the varied use of methodologies across studies - such as differences in the learning paradigms, stimuli used, and the way that learning is assessed - as well as differences in participant samples such as age and extent of the learning disorder. In this review, we attempt to examine the purported link between statistical learning and dyslexia by assessing a set of the most recent and relevant studies in both adults and children. Based on this review, we conclude that although there is some evidence for a statistical learning impairment in adults with dyslexia, the evidence for an impairment in children is much weaker. We discuss several suggestive trends that emerge from our examination of the research, such as issues related to task heterogeneity, possible age effects, the role of publication bias, and other suggestions for future research such as the use of neural measures and a need to better understand how statistical learning changes across typical development. We conclude that no current theoretical framework of dyslexia fully captures the extant research findings on statistical learning.

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.

Disentangling sequential from hierarchical learning in Artificial Grammar Learning: Evidence from a modified Simon Task

In this paper we probe the interaction between sequential and hierarchical learning by investigating implicit learning in a group of school-aged children. We administered a serial reaction time task, in the form of a modified Simon Task in which the stimuli were organised following the rules of two distinct artificial grammars, specifically Lindenmayer systems: the Fibonacci grammar (Fib) and the Skip grammar (a modification of the former). The choice of grammars is determined by the goal of this study, which is to investigate how sensitivity to structure emerges in the course of exposure to an input whose surface transitional properties (by hypothesis) bootstrap structure. The studies conducted to date have been mainly designed to investigate low-level superficial regularities, learnable in purely statistical terms, whereas hierarchical learning has not been effectively investigated yet. The possibility to directly pinpoint the interplay between sequential and hierarchical learning is instead at the core of our study: we presented children with two grammars, Fib and Skip, which share the same transitional regularities, thus providing identical opportunities for sequential learning, while crucially differing in their hierarchical structure. More particularly, there are specific points in the sequence (k-points), which, despite giving rise to the same transitional regularities in the two grammars, support hierarchical reconstruction in Fib but not in Skip. In our protocol, children were simply asked to perform a traditional Simon Task, and they were completely unaware of the real purposes of the task. Results indicate that sequential learning occurred in both grammars, as shown by the decrease in reaction times throughout the task, while differences were found in the sensitivity to k-points: these, we contend, play a role in hierarchical reconstruction in Fib, whereas they are devoid of structural significance in Skip. More particularly, we found that children were faster in correspondence to k-points in sequences produced by Fib, thus providing an entirely new kind of evidence for the hypothesis that implicit learning involves an early activation of strategies of hierarchical reconstruction, based on a straightforward interplay with the statistically-based computation of transitional regularities on the sequences of symbols.

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.

Editors’ Introduction and Review: Visual Narrative Research: An Emerging Field in Cognitive Science

Drawn sequences of images are among our oldest records of human intelligence, appearing on cave paintings, wall carvings, and ancient pottery, and they pervade across cultures from instruction manuals to comics. They also appear prevalently as stimuli across Cognitive Science, for studies of temporal cognition, event structure, social cognition, discourse, and basic intelligence. Yet, despite this fundamental place in human expression and research on cognition, the study of visual narratives themselves has only recently gained traction in Cognitive Science. This work has suggested that visual narrative comprehension requires cultural exposure across a developmental trajectory and engages with domain‐general processing mechanisms shared by visual perception, attention, event cognition, and language, among others. Here, we review the relevance of such research for the broader Cognitive Science community, and make the case for why researchers should join the scholarship of this ubiquitous but understudied aspect of human expression.

Drawn sequences of images, like those in comics and picture stories, are a pervasive and fundamental way that humans have communicated for millennia. Yet, the study of visual narratives has only recently gained traction in Cognitive Science. Here we explore what has held back the study of the cognition of visual narratives, and why researchers should join in scholarship of this ubiquitous aspect of expression.

Input Complexity Affects Long-Term Retention of Statistically Learned Regularities in an Artificial Language Learning Task

Statistical learning (SL) involving sensitivity to distributional regularities in the environment has been suggested to be an important factor in many aspects of cognition, including language. However, the degree to which statistically-learned information is retained over time is not well understood. To establish whether or not learners are able to preserve such regularities over time, we examined performance on an artificial second language learning task both immediately after training and also at a follow-up session 2 weeks later. Participants were exposed to an artificial language (Brocanto2), half of them receiving simplified training items in which only 20% of sequences contained complex structures, whereas the other half were exposed to a training set in which 80% of the items were composed of complex sequences. Overall, participants showed signs of learning at the first session and retention at the second, but the degree of learning was affected by the nature of the training they received. Participants exposed to the simplified input outperformed those in the more complex training condition. A GLMM was used to model the relationship between stimulus properties and participants' endorsement strategies across both sessions. The results indicate that participants in the complex training condition relied more on an item's chunk strength than those in the simple training condition. Taken together, this set of findings shows that statistically learned regularities are retained over the course of 2 weeks. The results also demonstrate that training on input featuring simple items leads to improved learning and retention of grammatical regularities.

Implicit Learning, Bilingualism, and Dyslexia: Insights From a Study Assessing AGL With a Modified Simon Task

This paper presents an experimental study investigating artificial grammar learning in monolingual and bilingual children, with and without dyslexia, using an original methodology. We administered a serial reaction time task, in the form of a modified Simon task, in which the sequence of the stimuli was manipulated according to the rules of a simple Lindenmayer grammar (more specifically, a Fibonacci grammar). By ensuring that the subjects focused on the correct response execution at the motor stage in presence of congruent or incongruent visual stimuli, we could meet the two fundamental criteria for implicit learning: the absence of an intention to learn and the lack of awareness at the level of resulting knowledge. The participants of our studies were four groups of 10-year-old children: 30 Italian monolingual typically developing children, 30 bilingual typically developing children with Italian L2, 24 Italian monolingual dyslexic children, and 24 bilingual dyslexic children with Italian L2. Participants were administered the modified Simon task developed according to the rules of the Fibonacci grammar and tested with respect to the implicit learning of three regularities: (i) a red is followed by a blue, (ii) a sequence of two blues is followed by a red, and (iii) a blue can be followed either by a red or by a blue. Results clearly support the hypothesis that learning took place, since participants of all groups became increasingly sensitive to the structure of the input, implicitly learning the sequence of the trials and thus appropriately predicting the occurrence of the relevant items, as manifested by faster reaction times in predictable trials. Moreover, group differences were found, with bilinguals being overall faster than monolinguals and dyslexics less accurate than controls. Finally, an advantage of bilingualism in dyslexia was found, with bilingual dyslexics performing consistently better than monolingual dyslexics and, in some conditions, at the level of the two control groups. These results are taken to suggest that bilingualism should be supported also among linguistically impaired individuals.

The Ontogenesis of Action Syntax

Language and action share similar organizational principles. Both are thought to be hierarchical and recursive in nature. Here we address the relationship between language and action from developmental and neurophysiological perspectives. We discuss three major aspects: The extent of the analogy between language and action; the necessity to extend research on the yet largely neglected aspect of action syntax; the positive contribution of a developmental approach to this topic. We elaborate on the claim that adding an ontogenetic approach will help to obtain a comprehensive picture about both the interplay between language and action and its development, and to answer the question whether the underlying mechanisms of detecting syntactic violations of action sequences are similar to or different from the processing of language syntactic violations.

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.

Your Brain on Comics: A Cognitive Model of Visual Narrative Comprehension

The past decade has seen a rapid growth of cognitive and brain research focused on visual narratives like comics and picture stories. This paper will summarize and integrate this emerging literature into the Parallel Interfacing Narrative‐Semantics Model (PINS Model)—a theory of sequential image processing characterized by an interaction between two representational levels: semantics and narrative structure. Ongoing semantic processes build meaning into an evolving mental model of a visual discourse. Updating of spatial, referential, and event information then incurs costs when they are discontinuous with the growing context. In parallel, a narrative structure organizes semantic information into coherent sequences by assigning images to categorical roles, which are then embedded within a hierarchic constituent structure. Narrative constructional schemas allow for specific predictions of structural sequencing, independent of semantics. Together, these interacting levels of representation engage in an iterative process of retrieval of semantic and narrative information, prediction of upcoming information based on those assessments, and subsequent updating based on discontinuity. These core mechanisms are argued to be domain‐general—spanning across expressive systems—as suggested by similar electrophysiological brain responses (N400, P600, anterior negativities) generated in response to manipulation of sequential images, music, and language. Such similarities between visual narratives and other domains thus pose fundamental questions for the linguistic and cognitive sciences.

Visual narratives like comics involve a range of complex cognitive operations in order to be understood. The Parallel Interfacing Narrative‐Semantics (PINS) Model integrates an emerging literature showing that comprehension of wordless image sequences balances two representational levels of semantic and narrative structure. The neurocognitive mechanisms that guide these processes are argued to overlap with other domains, such as language and music.

The P3b and P600(s): Positive contributions to language comprehension

Since its discovery in the 1960s, the P300 has been contributing both directly and indirectly to language research. Perhaps most notably, it has been suggested that the P600, an ERP component that was first characterized in the context of syntactic processing, could be a variant of the P3b subcomponent of the P300. Here, we review studies on both sides of the debate. We also review the "semantic P600," a positivity with a similar time course and distribution to the P600 seen for syntactic manipulations but that is obtained in response to some types of semantic anomalies. Because most current theories of the P600 try to account for both the syntactic and the semantic variant, linking the syntactic P600 to the P3b might also imply a similar link for the semantic P600. However, we describe emerging research in our lab that casts doubt on the idea that the syntactic P600 and the semantic P600 are the same effect. We argue that grouping ERP responses primarily by domain (language vs. nonlanguage) is likely to be misleading and suggest alternative ways of determining whether ERP effects reflect similar or different processing mechanisms.

Language development and disorders: Possible genes and environment interactions

Language development requires both basic cognitive mechanisms for learning language and a rich social context from which learning takes off. Disruptions in learning mechanisms, processing abilities, and/or social interactions increase the risks associated with social exclusion or developmental delays. Given the complexity of language processes, a multilevel approach is proposed where both cognitive mechanisms, genetic and environmental factors need to be probed together with their possible interactions. Here we review and discuss such interplay between environment and genetic predispositions in understanding language disorders, with a particular focus on a possible endophenotype, the ability for statistical sequential learning.

Under What Conditions Can Recursion Be Learned? Effects of Starting Small in Artificial Grammar Learning of Center-Embedded Structure

It has been suggested that external and/or internal limitations paradoxically may lead to superior learning, that is, the concepts of starting small and less is more (Elman, 1993; Newport, 1990). In this paper, we explore the type of incremental ordering during training that might help learning, and what mechanism explains this facilitation. We report four artificial grammar learning experiments with human participants. In Experiments 1a and 1b we found a beneficial effect of starting small using two types of simple recursive grammars: right‐branching and center‐embedding, with recursive embedded clauses in fixed positions and fixed length. This effect was replicated in Experiment 2 (N = 100). In Experiment 3 and 4, we used a more complex center‐embedded grammar with recursive loops in variable positions, producing strings of variable length. When participants were presented an incremental ordering of training stimuli, as in natural language, they were better able to generalize their knowledge of simple units to more complex units when the training input “grew” according to structural complexity, compared to when it “grew” according to string length. Overall, the results suggest that starting small confers an advantage for learning complex center‐embedded structures when the input is organized according to structural complexity.

Grounding the neurobiology of language in first principles: The necessity of non-language-centric explanations for language comprehension

Recent decades have ushered in tremendous progress in understanding the neural basis of language. Most of our current knowledge on language and the brain, however, is derived from lab-based experiments that are far removed from everyday language use, and that are inspired by questions originating in linguistic and psycholinguistic contexts. In this paper we argue that in order to make progress, the field needs to shift its focus to understanding the neurobiology of naturalistic language comprehension. We present here a new conceptual framework for understanding the neurobiological organization of language comprehension. This framework is non-language-centered in the computational/neurobiological constructs it identifies, and focuses strongly on context. Our core arguments address three general issues: (i) the difficulty in extending language-centric explanations to discourse; (ii) the necessity of taking context as a serious topic of study, modeling it formally and acknowledging the limitations on external validity when studying language comprehension outside context; and (iii) the tenuous status of the language network as an explanatory construct. We argue that adopting this framework means that neurobiological studies of language will be less focused on identifying correlations between brain activity patterns and mechanisms postulated by psycholinguistic theories. Instead, they will be less self-referential and increasingly more inclined towards integration of language with other cognitive systems, ultimately doing more justice to the neurobiological organization of language and how it supports language as it is used in everyday life.

Lack of Cross-Modal Effects in Dual-Modality Implicit Statistical Learning

A current controversy in the area of implicit statistical learning (ISL) is whether this process consists of a single, central mechanism or multiple modality-specific ones. To provide insight into this question, the current study involved three ISL experiments to explore whether multimodal input sources are processed separately in each modality or are integrated together across modalities. In Experiment 1, visual and auditory ISL were measured under unimodal conditions, with the results providing a baseline level of learning for subsequent experiments. Visual and auditory sequences were presented separately, and the underlying grammar used for both modalities was the same. In Experiment 2, visual and auditory sequences were presented simultaneously with each modality using the same artificial grammar to investigate whether redundant multisensory information would result in a facilitative effect (i.e., increased learning) compared to the baseline. In Experiment 3, visual and auditory sequences were again presented simultaneously but this time with each modality employing different artificial grammars to investigate whether an interference effect (i.e., decreased learning) would be observed compared to the baseline. Results showed that there was neither a facilitative learning effect in Experiment 2 nor an interference effect in Experiment 3. These findings suggest that participants were able to track simultaneously and independently two sets of sequential regularities under dual-modality conditions. These findings are consistent with the theories that posit the existence of multiple, modality-specific ISL mechanisms rather than a single central one.

Effect of pattern awareness on the behavioral and neurophysiological correlates of visual statistical learning

Statistical learning is the ability to extract predictive patterns from structured input. A common assumption is that statistical learning is a type of implicit learning that does not result in explicit awareness of learned patterns. However, there is also some evidence that statistical learning may involve explicit processing to some extent. The purpose of this study was to examine the effect of pattern awareness on behavioral and neurophysiological correlates of visual statistical learning. Participants completed a visual learning task while behavioral responses and event-related potentials were recorded. Following the completion of the task, awareness of statistical patterns was assessed through a questionnaire scored by three independent raters. Behavioral findings indicated learning only for participants exhibiting high pattern awareness levels. Neurophysiological data indicated that only the high-pattern awareness group showed expected P300 event-related potential learning effects, although there was also some indication that the low awareness groups showed a sustained mid- to late-latency negativity. Linear mixed-model analyses confirmed that only the high awareness group showed neurophysiological indications of learning. Finally, source estimation results revealed left hemispheric activation was associated with statistical learning extending from frontal to occipital and parietal regions. Further analyses suggested that left insula, left parahippocampal, and right precentral regions showed different levels of activation based on pattern awareness. To conclude, we found that pattern awareness, a dimension associated with explicit processing, strongly influences the behavioral and neurophysiological correlates of visual statistical learning.

Sequential learning in individuals with agrammatic aphasia: evidence from artificial grammar learning

We examined sequential learning in individuals with agrammatic aphasia (n = 12) and healthy age-matched participants (n = 12) using an artificial grammar. Artificial grammar acquisition, 24-hour retention, and the potential benefits of additional training were examined by administering an artificial grammar judgment test (1) immediately following auditory exposure-based training, (2) one day after training, and (3) after a second training session on the second day. An untrained control group (n = 12 healthy age-matched participants) completed the tests on the same time schedule. The trained healthy and aphasic groups showed greater sensitivity to the detection of grammatical items than the control group. No significant correlations between sequential learning and language abilities were observed among the aphasic participants. The results suggest that individuals with agrammatic aphasia show sequential learning, but the underlying processes involved in this learning may be different than for healthy adults.

Early positivity signals changes in an abstract linguistic pattern

The extraction of abstract structures from speech (or from gestures in the case of sign languages) has been claimed to be a fundamental mechanism for language acquisition. In the present study we registered the neural responses that are triggered when a violation of an abstract, token-independent rule is detected. We registered ERPs while presenting participants with trisyllabic CVCVCV nonsense words in an oddball paradigm. Standard stimuli followed an ABB rule (where A and B are different syllables). Importantly, to distinguish neural responses triggered by changes in surface information from responses triggered by changes in the underlying abstract structure, we used two types of deviant stimuli. Phoneme deviants differed from standards only in their phonemes. Rule deviants differed from standards in both their phonemes and their composing rule. We observed a significant positivity as early as 300 ms after the presentation of deviant stimuli that violated the abstract rule (Rule deviants). The amplitude of this neural response was correlated with participants’ performance in a behavioral rule learning test. Differences in electrophysiological responses observed between learners and non-learners suggest that individual differences in an abstract rule learning task might be related to how listeners select relevant sources of information.

What is your neural function, visual narrative conjunction? Grammar, meaning, and fluency in sequential image processing

Visual narratives sometimes depict successive images with different characters in the same physical space; corpus analysis has revealed that this occurs more often in Japanese manga than American comics. We used event-related brain potentials to determine whether comprehension of "visual narrative conjunctions" invokes not only incremental mental updating as traditionally assumed, but also, as we propose, "grammatical" combinatoric processing. We thus crossed (non)/conjunction sequences with character (in)/congruity. Conjunctions elicited a larger anterior negativity (300-500 ms) than nonconjunctions, regardless of congruity, implicating "grammatical" processes. Conjunction and incongruity both elicited larger P600s (500-700 ms), indexing updating. Both conjunction effects were modulated by participants' frequency of reading manga while growing up. Greater anterior negativity in frequent manga readers suggests more reliance on combinatoric processing; larger P600 effects in infrequent manga readers suggest more resources devoted to mental updating. As in language comprehension, it seems that processing conjunctions in visual narratives is not just mental updating but also partly grammatical, conditioned by comic readers' experience with specific visual narrative structures.

Visual statistical learning is related to natural language ability in adults: An ERP study

Statistical learning (SL) is believed to enable language acquisition by allowing individuals to learn regularities within linguistic input. However, neural evidence supporting a direct relationship between SL and language ability is scarce. We investigated whether there are associations between event-related potential (ERP) correlates of SL and language abilities while controlling for the general level of selective attention. Seventeen adults completed tests of visual SL, receptive vocabulary, grammatical ability, and sentence completion. Response times and ERPs showed that SL is related to receptive vocabulary and grammatical ability. ERPs indicated that the relationship between SL and grammatical ability was independent of attention while the association between SL and receptive vocabulary depended on attention. The implications of these dissociative relationships in terms of underlying mechanisms of SL and language are discussed. These results further elucidate the cognitive nature of the links between SL mechanisms and language abilities.

Possible roles for fronto-striatal circuits in reading disorder

Several studies have reported hyperactivation in frontal and striatal regions in individuals with reading disorder (RD) during reading-related tasks. Hyperactivation in these regions is typically interpreted as a form of neural compensation related to articulatory processing. Fronto-striatal hyperactivation in RD could however, also arise from fundamental impairment in reading related processes, such as phonological processing and implicit sequence learning relevant to early language acquisition. We review current evidence for the compensation hypothesis in RD and apply large-scale reverse inference to investigate anatomical overlap between hyperactivation regions and neural systems for articulation, phonological processing, implicit sequence learning. We found anatomical convergence between hyperactivation regions and regions supporting articulation, consistent with the proposed compensatory role of these regions, and low convergence with phonological and implicit sequence learning regions. Although the application of large-scale reverse inference to decode function in a clinical population should be interpreted cautiously, our findings suggest future lines of research that may clarify the functional significance of hyperactivation in RD.

Possible roles for fronto-striatal circuits in reading disorder

Several studies have reported hyperactivation in frontal and striatal regions in individuals with reading disorder (RD) during reading-related tasks. Hyperactivation in these regions is typically interpreted as a form of neural compensation related to articulatory processing. Fronto-striatal hyperactivation in RD could however, also arise from fundamental impairment in reading related processes, such as phonological processing and implicit sequence learning relevant to early language acquisition. We review current evidence for the compensation hypothesis in RD and apply large-scale reverse inference to investigate anatomical overlap between hyperactivation regions and neural systems for articulation, phonological processing, implicit sequence learning. We found anatomical convergence between hyperactivation regions and regions supporting articulation, consistent with the proposed compensatory role of these regions, and low convergence with phonological and implicit sequence learning regions. Although the application of large-scale reverse inference to decode function in a clinical population should be interpreted cautiously, our findings suggest future lines of research that may clarify the functional significance of hyperactivation in RD.

Evolutionary origins of non-adjacent sequence processing in primate brain potentials

There is considerable interest in understanding the ontogeny and phylogeny of the human language system, yet, neurobiological work at the interface of both fields is absent. Syntactic processes in language build on sensory processing and sequencing capabilities on the side of the receiver. While we better understand language-related ontogenetic changes in the human brain, it remains a mystery how neurobiological processes at specific human development stages compare with those in phylogenetically closely related species. To address this knowledge gap, we measured EEG event-related potentials (ERPs) in two macaque monkeys using a paradigm developed to evaluate human infant and adult brain potentials associated with the processing of non-adjacent ordering relationships in sequences of syllable triplets. Frequent standard triplet sequences were interspersed with infrequent voice pitch or non-adjacent rule deviants. Monkey ERPs show early pitch and rule deviant mismatch responses that are strikingly similar to those previously reported in human infants. This stands in contrast to adults' later ERP responses for rule deviants. The results reveal how non-adjacent sequence ordering relationships are processed in the primate brain and provide evidence for evolutionarily conserved neurophysiological effects, some of which are remarkably like those seen at an early human developmental stage.

Language and thought are not the same thing: evidence from neuroimaging and neurological patients

Is thought possible without language? Individuals with global aphasia, who have almost no ability to understand or produce language, provide a powerful opportunity to find out. Surprisingly, despite their near-total loss of language, these individuals are nonetheless able to add and subtract, solve logic problems, think about another person's thoughts, appreciate music, and successfully navigate their environments. Further, neuroimaging studies show that healthy adults strongly engage the brain's language areas when they understand a sentence, but not when they perform other nonlinguistic tasks such as arithmetic, storing information in working memory, inhibiting prepotent responses, or listening to music. Together, these two complementary lines of evidence provide a clear answer: many aspects of thought engage distinct brain regions from, and do not depend on, language.

Examining Procedural Learning and Corticostriatal Pathways for Individual Differences in Language: Testing Endophenotypes of DRD2/ANKK1

The aim of the study was to explore whether genetic variation in the dopaminergic system is associated with procedural learning and the corticostriatal pathways in individuals with developmental language impairment (DLI). We viewed these two systems as endophenotypes and hypothesized that they would be more sensitive indicators of genetic effects than the language phenotype itself. Thus, we genotyped two SNPs in the DRD2/ANKK1 gene complex, and tested for their associations to the phenotype of DLI and the two endophenotypes. Results showed that individuals with DLI revealed poor procedural learning abilities and abnormal structures of the basal ganglia. Genetic variation in DRD2/ANKK1 was associated with procedural learning abilities and with microstructural differences of the caudate nucleus. The association of the language phenotype with these DRD2/ANKK1 polymorphisms was not significant, but the phenotype was significantly associated with the two endophenotypes. We suggest that procedural learning and the corticostriatal pathways could be used as effective endophenotypes to aid molecular genetic studies searching for genes predisposing to DLI.

Individual Differences in Statistical Learning Predict Children's Comprehension of Syntax

Variability in children's language acquisition is likely due to a number of cognitive and social variables. The current study investigated whether individual differences in statistical learning (SL), which has been implicated in language acquisition, independently predicted 6- to 8-year-old's comprehension of syntax. Sixty-eight (N = 68) English-speaking children completed a test of comprehension of four syntactic structures, a test of SL utilizing nonlinguistic visual stimuli, and several additional control measures. The results revealed that SL independently predicted comprehension of two syntactic structures that show considerable variability in this age range: passives and object relative clauses. These data suggest that individual differences in children's capacity for SL are associated with the acquisition of the syntax of natural languages.

The language faculty that wasn't: a usage-based account of natural language recursion

In the generative tradition, the language faculty has been shrinking—perhaps to include only the mechanism of recursion. This paper argues that even this view of the language faculty is too expansive. We first argue that a language faculty is difficult to reconcile with evolutionary considerations. We then focus on recursion as a detailed case study, arguing that our ability to process recursive structure does not rely on recursion as a property of the grammar, but instead emerges gradually by piggybacking on domain-general sequence learning abilities. Evidence from genetics, comparative work on non-human primates, and cognitive neuroscience suggests that humans have evolved complex sequence learning skills, which were subsequently pressed into service to accommodate language. Constraints on sequence learning therefore have played an important role in shaping the cultural evolution of linguistic structure, including our limited abilities for processing recursive structure. Finally, we re-evaluate some of the key considerations that have often been taken to require the postulation of a language faculty.

The language faculty that wasn't: a usage-based account of natural language recursion

In the generative tradition, the language faculty has been shrinking-perhaps to include only the mechanism of recursion. This paper argues that even this view of the language faculty is too expansive. We first argue that a language faculty is difficult to reconcile with evolutionary considerations. We then focus on recursion as a detailed case study, arguing that our ability to process recursive structure does not rely on recursion as a property of the grammar, but instead emerges gradually by piggybacking on domain-general sequence learning abilities. Evidence from genetics, comparative work on non-human primates, and cognitive neuroscience suggests that humans have evolved complex sequence learning skills, which were subsequently pressed into service to accommodate language. Constraints on sequence learning therefore have played an important role in shaping the cultural evolution of linguistic structure, including our limited abilities for processing recursive structure. Finally, we re-evaluate some of the key considerations that have often been taken to require the postulation of a language faculty.

Can we improve structured sequence processing? Exploring the direct and indirect effects of computerized training using a mediational model

Recent research suggests that language acquisition may rely on domain-general learning abilities, such as structured sequence processing, which is the ability to extract, encode, and represent structured patterns in a temporal sequence. If structured sequence processing supports language, then it may be possible to improve language function by enhancing this foundational learning ability. The goal of the present study was to use a novel computerized training task as a means to better understand the relationship between structured sequence processing and language function. Participants first were assessed on pre-training tasks to provide baseline behavioral measures of structured sequence processing and language abilities. Participants were then quasi-randomly assigned to either a treatment group involving adaptive structured visuospatial sequence training, a treatment group involving adaptive non-structured visuospatial sequence training, or a control group. Following four days of sequence training, all participants were assessed with the same pre-training measures. Overall comparison of the post-training means revealed no group differences. However, in order to examine the potential relations between sequence training, structured sequence processing, and language ability, we used a mediation analysis that showed two competing effects. In the indirect effect, adaptive sequence training with structural regularities had a positive impact on structured sequence processing performance, which in turn had a positive impact on language processing. This finding not only identifies a potential novel intervention to treat language impairments but also may be the first demonstration that structured sequence processing can be improved and that this, in turn, has an impact on language processing. However, in the direct effect, adaptive sequence training with structural regularities had a direct negative impact on language processing. This unexpected finding suggests that adaptive training with structural regularities might potentially interfere with language processing. Taken together, these findings underscore the importance of pursuing designs that promote a better understanding of the mechanisms underlying training-related changes, so that regimens can be developed that help reduce these types of negative effects while simultaneously maximizing the benefits to outcome measures of interest.

Statistical learning as an individual ability: Theoretical perspectives and empirical evidence

Although the power of statistical learning (SL) in explaining a wide range of linguistic functions is gaining increasing support, relatively little research has focused on this theoretical construct from the perspective of individual differences. However, to be able to reliably link individual differences in a given ability such as language learning to individual differences in SL, three critical theoretical questions should be posed: Is SL a componential or unified ability? Is it nested within other general cognitive abilities? Is it a stable capacity of an individual? Following an initial mapping sentence outlining the possible dimensions of SL, we employed a battery of SL tasks in the visual and auditory modalities, using verbal and non-verbal stimuli, with adjacent and non-adjacent contingencies. SL tasks were administered along with general cognitive tasks in a within-subject design at two time points to explore our theoretical questions. We found that SL, as measured by some tasks, is a stable and reliable capacity of an individual. Moreover, we found SL to be independent of general cognitive abilities such as intelligence or working memory. However, SL is not a unified capacity, so that individual sensitivity to conditional probabilities is not uniform across modalities and stimuli.

The notion of the motion: the neurocognition of motion lines in visual narratives

Motion lines appear ubiquitously in graphic representation to depict the path of a moving object, most popularly in comics. Some researchers have argued that these graphic signs directly tie to the "streaks" appearing in the visual system when a viewer tracks an object (Burr, 2000), despite the fact that previous studies have been limited to offline measurements. Here, we directly examine the cognition of motion lines by comparing images in comic strips that depicted normal motion lines with those that either had no lines or anomalous, reversed lines. In Experiment 1, shorter viewing times appeared to images with normal lines than those with no lines, which were shorter than those with anomalous lines. In Experiment 2, measurements of event-related potentials (ERPs) showed that, compared to normal lines, panels with no lines elicited a posterior positivity that was distinct from the frontal positivity evoked by anomalous lines. These results suggested that motion lines aid in the comprehension of depicted events. LORETA source localization implicated greater activation of visual and language areas when understanding was made more difficult by anomalous lines. Furthermore, in both experiments, participants' experience reading comics modulated these effects, suggesting motion lines are not tied to aspects of the visual system, but rather are conventionalized parts of the "vocabulary" of the visual language of comics.

Exploring the neurodevelopment of visual statistical learning using event-related brain potentials

Implicit statistical learning (ISL) allows for the learning of environmental patterns and is thought to be important for many aspects of perception, cognition, and language development. However, very little is known about the development of the underlying neural mechanisms that support ISL. To explore the neurodevelopment of ISL, we investigated the event-related potential (ERP) correlates of learning in adults, older children (aged 9-12), and younger children (aged 6-9) using a novel predictor-target paradigm. In this task, which was a modification of the standard oddball paradigm, participants were instructed to view a serial input stream of visual stimuli and to respond with a button press when a particular target appeared. Unbeknownst to the participants, covert statistical probabilities were embedded in the task such that the target was predicted to varying degrees by different predictor stimuli. The results were similar across all three age groups: a P300 component that was elicited by the high predictor stimulus after sufficient exposure to the statistical probabilities. These neurophysiological findings provide evidence for developmental invariance in ISL, with adult-like competence reached by at least age 6.

Domain generality versus modality specificity: the paradox of statistical learning

Statistical learning (SL) is typically considered to be a domain-general mechanism by which cognitive systems discover the underlying distributional properties of the input. However, recent studies examining whether there are commonalities in the learning of distributional information across different domains or modalities consistently reveal modality and stimulus specificity. Therefore, important questions are how and why a hypothesized domain-general learning mechanism systematically produces such effects. Here, we offer a theoretical framework according to which SL is not a unitary mechanism, but a set of domain-general computational principles that operate in different modalities and, therefore, are subject to the specific constraints characteristic of their respective brain regions. This framework offers testable predictions and we discuss its computational and neurobiological plausibility.

The grammar of visual narrative: Neural evidence for constituent structure in sequential image comprehension

Constituent structure has long been established as a central feature of human language. Analogous to how syntax organizes words in sentences, a narrative grammar organizes sequential images into hierarchic constituents. Here we show that the brain draws upon this constituent structure to comprehend wordless visual narratives. We recorded neural responses as participants viewed sequences of visual images (comics strips) in which blank images either disrupted individual narrative constituents or fell at natural constituent boundaries. A disruption of either the first or the second narrative constituent produced a left-lateralized anterior negativity effect between 500 and 700ms. Disruption of the second constituent also elicited a posteriorly-distributed positivity (P600) effect. These neural responses are similar to those associated with structural violations in language and music. These findings provide evidence that comprehenders use a narrative structure to comprehend visual sequences and that the brain engages similar neurocognitive mechanisms to build structure across multiple domains.

Neurocognitive mechanisms of statistical-sequential learning: what do event-related potentials tell us?

Statistical-sequential learning (SL) is the ability to process patterns of environmental stimuli, such as spoken language, music, or one's motor actions, that unfold in time. The underlying neurocognitive mechanisms of SL and the associated cognitive representations are still not well understood as reflected by the heterogeneity of the reviewed cognitive models. The purpose of this review is: (1) to provide a general overview of the primary models and theories of SL, (2) to describe the empirical research - with a focus on the event-related potential (ERP) literature - in support of these models while also highlighting the current limitations of this research, and (3) to present a set of new lines of ERP research to overcome these limitations. The review is articulated around three descriptive dimensions in relation to SL: the level of abstractness of the representations learned through SL, the effect of the level of attention and consciousness on SL, and the developmental trajectory of SL across the life-span. We conclude with a new tentative model that takes into account these three dimensions and also point to several promising new lines of SL research.

An ERP study of structural anomalies in native and semantic free artificial grammar: evidence for shared processing mechanisms

Artificial grammars have been widely applied to the study of sequential learning in language, but few studies have directly compared the neural correlates of artificial and native grammar processing. In this study, we examined Event Related Potentials (ERPs) elicited by structural anomalies in semantic-free artificial grammar sequences and sentences in the subjects' native language (Spanish). Although ERPs differed during early stages, we observed similar posterior negativities (N400) and P600 effects in a late stage. We interpret these results as evidence of at least partially shared neural mechanisms for processing of language and artificial grammars. We suggest that in both the natural and artificial grammars, the N400 and P600 components we observed can be explained as the result of unfulfilled predictions about incoming stimuli.