Developmental differences in EEG oscillations supporting the identification of novel word meaning from context

Abstract

Implicit learning about new words by picking up on associative information in the contexts they appear in is an important aspect of vocabulary growth. The current study investigated the neural correlates that underlie how school-aged children and adolescents identify the meaning of novel words embedded within sentence contexts. Importantly, we examine how differences in the brain response to novel words and their context differ as a function of 1) explicit learning success, i.e., whether novel word meanings can be correctly estimated in isolation after a learning opportunity, and 2) individual differences in offline language aptitude as well as age across our cohort (N = 82; 8-16 years). Using a regression-based analysis, we identified the unique influence of these individuals difference metrics by using both measures within the same series of models. The most notable finding from our analysis was a frequency-specific dissociation between the way age and language abilities held relationships with task-relevant oscillatory activity during the novel word meaning task: language abilities associated with task-relevant changes in beta band activity during sentence processing, while age associated with task-relevant changes in theta band activity during pseudoword processing. These effects reflect the how the neural correlates of mapping semantic meaning from sentence contexts-an important skill for word learning-is uniquely influenced by the maturity of language abilities as well as age.

Keywords: EEG; Language Processing; Semantic processing; Time frequency analysis; Word learning.

Fig. 1

Depiction of a single trial with an example sentence triplet used in the meaning identification task. Note that the target real word “bed” fits as a plausible ending for each sentence in the trial.

Fig. 2

EEG data collected from 52 scalp electrodes were aggregated within 9 cluster regions for the regression-based ERSP analysis.

Fig. 3

A) Simple linear regression between Age and performance on the meaning identification task. B) Simple linear regression between Language Abilities, as indexed by raw scores on the Formulating Sentences and Recalling Sentences subtests of the CELF-5 battery, and performance on the meaning identification task. Reported test statistics used a model with z-transformed proportion of total correct trials on the meaning identification task, but raw proportions are represented in the scatterplots for clarity. Both Age and Language Abilities held a significant positive relationship with Task Accuracy.

Fig. 4

Summary figure depicting the distribution of the task relevant theta and beta band activity identified by the GLMER analysis. Age modulated the effect of theta band activity on task performance while language abilities held a modulatory effect on the relationship between beta band activity and task performance.

Fig. 5

A) Time series of regression model weights corresponding to the main effects of beta (blue) and theta (orange) band activity on task accuracy identified during Sentence 1. B) Time series of regression model weights corresponding to the interaction effects between theta band activity and age on task accuracy during Sentence 2. C) Time series of regression model weights corresponding to interaction effects between beta band activity and language abilities on task accuracy during Sentences 1 (left), 2 (middle), and 3 (right). Shaded areas surrounding the plotted lines represent the standard error for the corresponding model estimate at each time point. Significant model estimates are marked by the shaded boxes. Pseudoword onset occurred at 0 ms.

Fig. 6

Main effects of theta and beta power on Task Accuracy. Graphs depict predicted power plotted across time as a function of Task Accuracy to visualize the relationship between ERSP activity and task performance. All main effects were identified during initial sentence in each trial (Sentence 1). A) Main effects of beta band activity on task performance were identified in middle parietal, left frontal, and left central pre-pseudoword activity during sentence 1. The GLMER analysis revealed that greater beta band suppression was associated with better task performance. B) A main effect of theta activity on Task Accuracy was identified over right parietal electrodes during sentence 1. The GLMER analysis revealed that greater theta band enhancement was associated with better task performance. Shaded regions denote the time windows that significant main effects of theta and beta activity on Task Accuracy were identified. Pseudoword onset occurred at 0 ms.

Fig. 7

A series of graphs showing predicted theta band power across correct and incorrect trials as a function of child age during the second sentence. Predicted fits were obtained in a series of LMER models that modeled theta band activity as a function of Task Accuracy. Interactions between Task Accuracy and age were included to visualize the theta band by Age interactions identified in the GLMER analysis using Task Accuracy as a binomial outcome variable. Shaded regions represent the significant time points identified in the GLMER analysis. Pseudoword onset occurred at 0 ms.

Fig. 8

A series of graphs showing predicted beta band power across correct and incorrect trials as a function of language abilities during the first (left) and third (right) sentences. Predicted fits were obtained in a series of LMER models that modeled beta band activity as a function of Task Accuracy. Interactions between Task Accuracy and language abilities were included to visualize the beta band by Language Ability interactions identified in the GLMER analysis using Task Accuracy as a binomial outcome variable. Shaded regions represent the significant time points identified in the GLMER analysis. Pseudoword onset occurred at 0 ms.