Understanding the neurobiological basis of individual differences in second language acquisition (SLA) is important for research on bilingualism, learning, and neural plasticity. The current study used quantitative electroencephalography (qEEG) to predict SLA in college-aged individuals. Baseline, eyes-closed resting-state qEEG was used to predict language learning rate during eight weeks of French exposure using an immersive, virtual scenario software. Individual qEEG indices predicted up to 60% of the variability in SLA, whereas behavioral indices of fluid intelligence, executive functioning, and working-memory capacity were not correlated with learning rate. Specifically, power in beta and low-gamma frequency ranges over right temporoparietal regions were strongly positively correlated with SLA. These results highlight the utility of resting-state EEG for studying the neurobiological basis of SLA in a relatively construct-free, paradigm-independent manner.

Individuals who develop bilingually typically outperform monolinguals on tests of executive functions. This advantage likely reflects enhanced prefrontal function, but the mechanisms that underlie this improvement are still poorly understood. This article describes a theory on the nature of the neural underpinnings of improved executive function in bilinguals. Specifically, we propose that growing up in a bilingual environment trains a gating system in the striatum that flexibly routes information to the prefrontal cortex. This article is divided into three sections. Firstly, literature establishing a three-way connection between bilingualism, executive function, and fronto-striatal loops is summarized. Secondly, a computational model of information processing in the basal ganglia is described, illustrating how the striatal nuclei function to transfer information between cortical regions under prerequisite conditions. Finally, this model is extended to describe how bilingualism may "train the brain," enabling improved performance under conditions of competitive information selection during information transfer. Theoretical implications and predictions of this theory are discussed.It is well known that bilingual individuals outperform monolinguals in a number of tasks involving executive function (e.g., Bialystok, 1998(e.g., Bialystok, , 1999(e.g., Bialystok, , 2004(e.g., Bialystok, , 2009. The cognitive nature of this advantage, however, is still debated, and its neural mechanism unspecified. In this paper, we propose a brain-based computational model of information routing from the striatum to the frontal cortex that simultaneously explains how bilingualism "trains" the brain and clarifies the

The current study used quantitative electroencephalography (qEEG) to characterize individual differences in neural rhythms at rest and to relate them to fluid reasoning ability, to first language proficiency, and to subsequent second language (L2) learning ability, with the goal of obtaining a better understanding of the neurocognitive bases of L2 aptitude. Mean spectral power, laterality, and coherence metrics were extracted across theta, alpha, beta, and gamma frequency bands obtained from eyes-closed resting-state qEEG data from 41 adults aged 18–34 years. Participants then completed 8 weeks of French training using a virtual language and cultural immersion software. Results replicate and extend previous studies showing that faster learners have higher beta power recorded over right hemisphere (RH) electrode sites, greater laterality (RH − LH/RH + LH) of alpha and beta bands, and greater coherence between RH frontotemporal sites across all frequencies, although only coherence measures survived multiple comparisons. Increased coherence within and between RH networks was also associated with greater posttest declarative memory scores and with more accurate speech during learning. Total speech attempts, in contrast, correlated with bilaterally distributed small-world network configurations, as indexed by lower power and coherence over high-frequency (beta and gamma) bands recorded over frontotemporal networks in both hemispheres. Results from partial correlations and regression analyses suggest that the neural predictors of L2 learning rate, posttest proficiency, and total speech attempts varied in their degree of overlap with qEEG correlates of first language proficiency and fluid reasoning abilities, but that neural predictors alone explained 26–60% of the variance in L2 outcomes.

A previous functional magnetic resonance imaging (fMRI) study by Weiss et al.