Whole-brain functional connectivity during acquisition of novel grammar: Distinct functional networks depend on language learning abilities

Study protocol: a comprehensive multi-method neuroimaging approach to disentangle developmental effects and individual differences in second language learning

Background

While it is well established that second language (L2) learning success changes with age and across individuals, the underlying neural mechanisms responsible for this developmental shift and these individual differences are largely unknown. We will study the behavioral and neural factors that subserve new grammar and word learning in a large cross-sectional developmental sample. This study falls under the NWO (Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Dutch Research Council]) Language in Interaction consortium (website: https://www.languageininteraction.nl/).

Methods

We will sample 360 healthy individuals across a broad age range between 8 and 25 years. In this paper, we describe the study design and protocol, which involves multiple study visits covering a comprehensive behavioral battery and extensive magnetic resonance imaging (MRI) protocols. On the basis of these measures, we will create behavioral and neural fingerprints that capture age-based and individual variability in new language learning. The behavioral fingerprint will be based on first and second language proficiency, memory systems, and executive functioning. We will map the neural fingerprint for each participant using the following MRI modalities: T1‐weighted, diffusion-weighted, resting-state functional MRI, and multiple functional-MRI paradigms. With respect to the functional MRI measures, half of the sample will learn grammatical features and half will learn words of a new language. Combining all individual fingerprints allows us to explore the neural maturation effects on grammar and word learning.

Discussion

This will be one of the largest neuroimaging studies to date that investigates the developmental shift in L2 learning covering preadolescence to adulthood. Our comprehensive approach of combining behavioral and neuroimaging data will contribute to the understanding of the mechanisms influencing this developmental shift and individual differences in new language learning. We aim to answer: (I) do these fingerprints differ according to age and can these explain the age-related differences observed in new language learning? And (II) which aspects of the behavioral and neural fingerprints explain individual differences (across and within ages) in grammar and word learning? The results of this study provide a unique opportunity to understand how the development of brain structure and function influence new language learning success.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40359-022-00873-x.

Neural Fingerprints Underlying Individual Language Learning Profiles

Human language learning differs significantly across individuals in the process and ultimate attainment. Although decades of research exploring the neural substrates of language learning have identified distinct and overlapping neural networks subserving learning of different components, the neural mechanisms that drive the large interindividual differences are still far from being understood. Here we examine to what extent the neural dynamics of multiple brain networks in men and women across sessions of training contribute to explaining individual differences in learning multiple linguistic components (i.e., vocabulary, morphology, and phrase and sentence structures) of an artificial language in a 7 d training and imaging paradigm with functional MRI. With machine-learning and predictive modeling, neural activation patterns across training sessions were highly predictive of individual learning success profiles derived from the four components. We identified four neural learning networks (i.e., the Perisylvian, frontoparietal, salience, and default-mode networks) and examined their dynamic contributions to the learning success prediction. Moreover, the robustness of the predictions systematically changes across networks depending on specific training phases and the learning components. We further demonstrate that a subset of network nodes in the inferior frontal, insular, and frontoparietal regions increasingly represent newly acquired language knowledge, while the multivariate connectivity between these representation regions is enhanced during learning for more successful learners. These findings allow us to understand why learners differ and are the first to attribute not only the degree of success but also patterns of language learning across components, to neural fingerprints summarized from multiple neural network dynamics.SIGNIFICANCE STATEMENT Individual differences in learning a language are widely observed not only within the same component of language but also across components. This study demonstrates that the dynamics of multiple brain networks across four imaging sessions of a 7 d artificial language training contribute to individual differences in learning-outcome profiles derived from four language components. With machine-learning predictive modeling, we identified four neural learning networks, including the Perisylvian, frontoparietal, salience, and default-mode networks, that contribute to predicting individual learning-outcome profiles and revealed language-component-general and component-specific prediction patterns across training sessions. These findings provide significant insights in understanding training-dependent neural dynamics underlying individual differences in learning success across language components.

Task-induced brain functional connectivity as a representation of schema for mediating unsupervised and supervised learning dynamics in language acquisition

INTRODUCTION

Based on the schema theory advanced by Rumelhart and Norman, we shed light on the individual variability in brain dynamics induced by hybridization of learning methodologies, particularly alternating unsupervised learning and supervised learning in language acquisition. The concept of "schema" implies a latent knowledge structure that a learner holds and updates as intrinsic to his or her cognitive space for guiding the processing of newly arriving information.

METHODS

We replicated the cognitive experiment of Onnis and Thiessen on implicit statistical learning ability in language acquisition but included additional factors of prosodic variables and explicit supervised learning. Functional magnetic resonance imaging was performed to identify the functional network connections for schema updating by alternately using unsupervised and supervised artificial grammar learning tasks to segment potential words.

RESULTS

Regardless of the quality of task performance, the default mode network represented the first stage of spontaneous unsupervised learning, and the wrap-up accomplishment for successful subjects of the whole hybrid learning in concurrence with the task-related auditory language networks. Furthermore, subjects who could easily "tune" the schema for recording a high task precision rate resorted even at an early stage to a self-supervised learning, or "superlearning," as a set of different learning mechanisms that act in synergy to trigger widespread neuro-transformation with a focus on the cerebellum.

CONCLUSIONS

Investigation of the brain dynamics revealed by functional connectivity imaging analysis was able to differentiate the synchronized neural responses with respect to learning methods and the order effect that affects hybrid learning.

The Small and Efficient Language Network of Polyglots and Hyper-polyglots

Acquiring a foreign language is challenging for many adults. Yet certain individuals choose to acquire sometimes dozens of languages and often just for fun. Is there something special about the minds and brains of such polyglots? Using robust individual-level markers of language activity, measured with fMRI, we compared native language processing in polyglots versus matched controls. Polyglots (n = 17, including nine "hyper-polyglots" with proficiency in 10-55 languages) used fewer neural resources to process language: Their activations were smaller in both magnitude and extent. This difference was spatially and functionally selective: The groups were similar in their activation of two other brain networks-the multiple demand network and the default mode network. We hypothesize that the activation reduction in the language network is experientially driven, such that the acquisition and use of multiple languages makes language processing generally more efficient. However, genetic and longitudinal studies will be critical to distinguish this hypothesis from the one whereby polyglots' brains already differ at birth or early in development. This initial characterization of polyglots' language network opens the door to future investigations of the cognitive and neural architecture of individuals who gain mastery of multiple languages, including changes in this architecture with linguistic experiences.

Mini Pinyin: A modified miniature language for studying language learning and incremental sentence processing

Artificial grammar learning (AGL) paradigms are used extensively to characterise (neuro)cognitive bases of language learning. However, despite their effectiveness in characterising the capacity to learn complex structured sequences, AGL paradigms lack ecological validity and typically do not account for cross-linguistic differences in sentence comprehension. Here, we describe a new modified miniature language paradigm - Mini Pinyin - that mimics natural language as it is based on an existing language (Mandarin Chinese) and includes both structure and meaning. Mini Pinyin contains a number of cross-linguistic elements, including varying word orders and classifier-noun rules. To evaluate the effectiveness of Mini Pinyin, 76 (mean age = 24.9; 26 female) monolingual native English speakers completed a learning phase followed by a sentence acceptability judgement task. Generalised mixed effects modelling revealed that participants attained a moderate degree of accuracy on the judgement task, with performance scores ranging from 25% to 100% accuracy depending on the word order of the sentence. Further, sentences compatible with the canonical English word order were learned more efficiently than non-canonical word orders. We controlled for inter-individual differences in statistical learning ability, which accounted for ~20% of the variance in performance on the sentence judgement task. We provide stimuli and statistical analysis scripts as open-source resources and discuss how future research can utilise this paradigm to study the neurobiological basis of language learning. Mini Pinyin affords a convenient tool for improving the future of language learning research by building on the parameters of traditional AGL or existing miniature language paradigms.

Auditory Cortex Morphology Predicts Language Learning Potential in Children and Teenagers

In two recent studies, we identified neuroanatomical and neurofunctional markers of musical aptitude, attention deficit (hyperactivity) disorder and dyslexia in the auditory cortex (AC) of children. In a subsequent study with adults, we found evidence for neuroanatomical correlates of speech imitation ability in right Heschl's gyrus (HG), a structure comprising primary and parts of secondary AC. In the present study, we aimed to verify this previously suggested link between structural variation of right HG and language aptitude in a younger population of children and teenagers (N = 42; age range: 10-16 years), while behaviorally exploring the relationship between language aptitude, working memory, arithmetic skills and musicality. Behaviorally, scores on the language aptitude battery strongly correlated with working memory and speech imitation ability. Furthermore, we found that self- and parent-reported language aptitude and school grades were closely associated with language aptitude scores. Neuroanatomical analyses revealed a significant relationship between the occurrence of multiple HGs and high gray matter (GM) volumes in right AC and high language aptitude regardless of age, gender or musical ability. Additionally, low language aptitude was associated with the occurrence of single gyri in right AC. In accordance with previous research, we suggest that right HG might be associated with language aptitude, with a stronger gyrification and higher GM volumes being beneficial for successful auditory processing and the integration of speech-related cues.

"When Music Speaks": Auditory Cortex Morphology as a Neuroanatomical Marker of Language Aptitude and Musicality

Recent research has shown that the morphology of certain brain regions may indeed correlate with a number of cognitive skills such as musicality or language ability. The main aim of the present study was to explore the extent to which foreign language aptitude, in particular phonetic coding ability, is influenced by the morphology of Heschl’s gyrus (HG; auditory cortex), working memory capacity, and musical ability. In this study, the auditory cortices of German-speaking individuals (N = 30; 13 males/17 females; aged 20–40 years) with high and low scores in a number of language aptitude tests were compared. The subjects’ language aptitude was measured by three different tests, namely a Hindi speech imitation task (phonetic coding ability), an English pronunciation assessment, and the Modern Language Aptitude Test (MLAT). Furthermore, working memory capacity and musical ability were assessed to reveal their relationship with foreign language aptitude. On the behavioral level, significant correlations were found between phonetic coding ability, English pronunciation skills, musical experience, and language aptitude as measured by the MLAT. Parts of all three tests measuring language aptitude correlated positively and significantly with each other, supporting their validity for measuring components of language aptitude. Remarkably, the number of instruments played by subjects showed significant correlations with all language aptitude measures and musicality, whereas, the number of foreign languages did not show any correlations. With regard to the neuroanatomy of auditory cortex, adults with very high scores in the Hindi testing and the musicality test (AMMA) demonstrated a clear predominance of complete posterior HG duplications in the right hemisphere. This may reignite the discussion of the importance of the right hemisphere for language processing, especially when linked or common resources are involved, such as the inter-dependency between phonetic and musical aptitude.