Resting-state qEEG predicts rate of second language learning in adults

Degree of multilingual engagement modulates resting state oscillatory activity across the lifespan

Multilingualism has been demonstrated to lead to a more favorable trajectory of neurocognitive aging, yet our understanding of its effect on neurocognition across the lifespan remains limited. We collected resting state EEG recordings from a sample of multilingual individuals across a wide age range. Additionally, we obtained data on participant multilingual language use patterns alongside other known lifestyle enrichment factors. Language experience was operationalized via a modified multilingual diversity (MLD) score. Generalized additive modeling was employed to examine the effects and interactions of age and MLD on resting state oscillatory power and coherence. The data suggest an independent modulatory effect of individualized multilingual engagement on age-related differences in whole brain resting state power across alpha and theta bands, and an interaction between age and MLD on resting state coherence in alpha, theta, and low beta. These results provide evidence of multilingual engagement as an independent correlational factor related to differences in resting state EEG power, consistent with the claim that multilingualism can serve as a protective factor in neurocognitive aging.

Decoding bilingualism from resting-state oscillatory network organization

Can lifelong bilingualism be robustly decoded from intrinsic brain connectivity? Can we determine, using a spectrally resolved approach, the oscillatory networks that better predict dual-language experience? We recorded resting-state magnetoencephalographic activity in highly proficient Spanish-Basque bilinguals and Spanish monolinguals, calculated functional connectivity at canonical frequency bands, and derived topological network properties using graph analysis. These features were fed into a machine learning classifier to establish how robustly they discriminated between the groups. The model showed excellent classification (AUC: 0.91 ± 0.12) between individuals in each group. The key drivers of classification were network strength in beta (15-30 Hz) and delta (2-4 Hz) rhythms. Further characterization of these networks revealed the involvement of temporal, cingulate, and fronto-parietal hubs likely underpinning the language and default-mode networks (DMNs). Complementary evidence from a correlation analysis showed that the top-ranked features that better discriminated individuals during rest also explained interindividual variability in second language (L2) proficiency within bilinguals, further supporting the robustness of the machine learning model in capturing trait-like markers of bilingualism. Overall, our results show that long-term experience with an L2 can be "brain-read" at a fine-grained level from resting-state oscillatory network organization, highlighting its pervasive impact, particularly within language and DMN networks.

Lexical tone perception and learning in older adults: A review and future directions

While the literature is well represented in accounting for how aging influences segmental properties of speech, less is known about its influences on suprasegmental properties such as lexical tones. In addition, foreign language learning is increasingly endorsed as being a potential intervention to boost cognitive reserve and overall well-being in older adults. Empirical studies on young learners learning lexical tones are aplenty in comparison with older learners. Challenges in this domain for older learners might be different due to aging and other learner-internal factors. This review consolidates behavioural and neuroscientific research related to lexical tone, speech perception, factors characterising learner groups, and other variables that would influence lexical tone perception and learning in older adults. Factors commonly identified to influence tone learning in younger adult populations, such as musical experience, language background, and motivation in learning a new language, are discussed in relation to older learner groups and recommendations to boost lexical tone learning in older age are provided based on existing studies.

Vigilant attention mediates the association between resting EEG alpha oscillations and word learning ability

Individuals exhibit considerable variability in their capacity to learn and retain new information, including novel vocabulary. Prior research has established the importance of vigilance and electroencephalogram (EEG) alpha rhythm in the learning process. However, the interplay between vigilant attention, EEG alpha oscillations, and an individual's word learning ability (WLA) remains elusive. To address this knowledge gap, here we conducted two experiments with a total of 140 young and middle-aged adults who underwent resting EEG recordings prior to completing a paired-associate word learning task and a psychomotor vigilance test (PVT). The results of both experiments consistently revealed significant positive correlations between WLA and resting EEG alpha oscillations in the occipital and frontal regions. Furthermore, the association between resting EEG alpha oscillations and WLA was mediated by vigilant attention, as measured by the PVT. These findings provide compelling evidence supporting the crucial role of vigilant attention in linking EEG alpha oscillations to an individual's learning ability.

Individual differences in information processing during sleep and wake predict sleep-based memory consolidation of complex rules

Memory is critical for many cognitive functions, from remembering facts, to learning complex environmental rules. While memory encoding occurs during wake, memory consolidation is associated with sleep-related neural activity. Further, research suggests that individual differences in alpha frequency during wake (∼7 - 13 Hz) modulate memory processes, with higher individual alpha frequency (IAF) associated with greater memory performance. However, the relationship between wake-related EEG individual differences, such as IAF, and sleep-related neural correlates of memory consolidation has been largely unexplored, particularly in a complex rule-based memory context. Here, we aimed to investigate whether wake-derived IAF and sleep neurophysiology interact to influence rule learning in a sample of 35 healthy adults (16 males; mean age = 25.4, range: 18 - 40). Participants learned rules of a modified miniature language prior to either 8hrs of sleep or wake, after which they were tested on their knowledge of the rules in a grammaticality judgement task. Results indicate that sleep neurophysiology and wake-derived IAF do not interact but modulate memory for complex linguistic rules separately. Phase-amplitude coupling between slow oscillations and spindles during non-rapid eye-movement (NREM) sleep also promoted memory for rules that were analogous to the canonical English word order. As an exploratory analysis, we found that rapid eye-movement (REM) sleep theta power at posterior regions interacts with IAF to predict rule learning and proportion of time in REM sleep predicts rule learning differentially depending on grammatical rule type. Taken together, the current study provides behavioural and electrophysiological evidence for a complex role of NREM and REM sleep neurophysiology and wake-derived IAF in the consolidation of rule-based information.

Getting language right: Relating individual differences in right hemisphere contributions to language learning and relearning

Language, or the diverse set of dynamic processes through which symbolic, perceptual codes are linked to meaning representations in memory, has long been assumed to be lateralized to the left hemisphere (LH). However, after over 150 years of investigation, we still lack a unifying account of when, and for whom, a particular linguistic process relies upon LH or right hemisphere (RH) computations, or both. With a focus on individual differences, this article integrates existing theories of hemispheric contributions to language and cognition into a novel proposed framework for understanding how, when, and for whom the RH contributes to linguistic processes. We use evidence from first and second language learning and language relearning following focal brain damage to highlight the critical contributions of the RH.

Foreign speech sound discrimination and associative word learning lead to a fast reconfiguration of resting-state networks

Learning new words in an unfamiliar language is a complex endeavor that requires the orchestration of multiple perceptual and cognitive functions. Although the neural mechanisms governing word learning are becoming better understood, little is known about the predictive value of resting-state (RS) metrics for foreign word discrimination and word learning attainment. In addition, it is still unknown which of the multistep processes involved in word learning have the potential to rapidly reconfigure RS networks. To address these research questions, we used electroencephalography (EEG), measured forty participants, and examined scalp-based power spectra, source-based spectral density maps and functional connectivity metrics before (RS1), in between (RS2) and after (RS3) a series of tasks which are known to facilitate the acquisition of new words in a foreign language, namely word discrimination, word-referent mapping and semantic generalization. Power spectra at the scalp level consistently revealed a reconfiguration of RS networks as a function of foreign word discrimination (RS1 vs. RS2) and word learning (RS1 vs. RS3) tasks in the delta, lower and upper alpha, and upper beta frequency ranges. Otherwise, functional reconfigurations at the source level were restricted to the theta (spectral density maps) and to the lower and upper alpha frequency bands (spectral density maps and functional connectivity). Notably, scalp RS changes related to the word discrimination tasks (difference between RS2 and RS1) correlated with word discrimination abilities (upper alpha band) and semantic generalization performance (theta and upper alpha bands), whereas functional changes related to the word learning tasks (difference between RS3 and RS1) correlated with word discrimination scores (lower alpha band). Taken together, these results highlight that foreign speech sound discrimination and word learning have the potential to rapidly reconfigure RS networks at multiple functional scales.

Bilingualism modulates neural efficiency at rest through alpha reactivity

The aim of the present study was to investigate how resting state EEG rhythms reflect attentional processes and bilingual experience. We compared alpha and beta rhythms for monolingual and bilingual young adults in eyes open and eyes closed conditions using EEG measures of frequency power, reactivity, and coherence. Power shows the amount of brain activity at a given frequency band; reactivity indexes the desynchronization of neuronal activity when individuals open their eyes at rest; and coherence indicates the brain regions that have correlated activity. The results showed that bilinguals had similar alpha power as monolinguals in both resting conditions but less alpha reactivity across the whole scalp. There was also more focused activation for bilinguals expressed as more coherence in posterior electrodes, particularly when eyes were opened to direct attention. For beta, there were no group differences in power or reactivity, but there was higher coherence for monolinguals than bilinguals, a pattern consistent with previous literature showing that beta frequency was related to language learning and native language proficiency. These results are in line with a neural efficiency theory and suggest that bilinguals have a more efficient brain for attentional mechanisms than monolinguals at rest.

Electrophysiological correlates of dispositional mindfulness: A quantitative and complexity EEG study

While growing evidence supports that dispositional mindfulness relates to psychological health and cognitive enhancement, to date there have been only a few attempts to characterize its neural underpinnings. In the present study, we aimed at exploring the electrophysiological (EEG) signature of dispositional mindfulness using quantitative and complexity measures of EEG during resting state and while performing a learning task. Hundred twenty participants were assessed with the Five Facet Mindfulness Questionnaire and underwent 5 min eyes-closed resting state and 5 min at task EEG recording. We hypothesized that high mindfulness individuals would show patterns of brain activity related to (a) lower involvement of the default mode network (DMN) at rest (reduced frontal gamma power) and (b) a state of 'task readiness' reflected in a more similar pattern from rest to task (reduced overall q-EEG power at rest but not at task), as compared to their low mindfulness counterparts. Dispositional mindfulness was significantly linked to reduced frontal gamma power at rest and lower overall power during rest but not at task. In addition, we found a trend towards higher entropy during task performance in mindful individuals, which has recently been reported during mindfulness meditation. Altogether, our results add to those from expert meditators to show that high (dispositional) mindfulness seems to have a specific electrophysiological pattern characteristic of less involvement of the DMN and mind-wandering processes.

Short-term PM2.5 exposure and cognitive function: Association and neurophysiological mechanisms

BACKGROUND

Although converging evidence has demonstrated that exposure to fine particulate matter (PM_2.5) caused adverse effects on brain structure and cognitive function, the association between the short-term exposure to PM_2.5 and cognition dysfunction remained underexplored, especially possible neurophysiological mechanisms.

METHODS

We conducted a longitudinal observational study with four repeated measurement sessions among 90 young adults from September 2020 to June 2021. During each measurement session, we measured participants' personal-level air pollution exposure for one week with portable monitors, followed by executive function assessment and electrophysiological signal recording at an assessment center. Standard Stroop color-word test was used accompanied with electroencephalogram (EEG) recording to assess performance on executive function. We used linear mixed-effect model with lagged values of PM_2.5 levels to analyze the association between PM_2.5 exposure and changes in executive function, and mediation analysis to investigate mediation effect by EEG signal.

RESULTS

Adjusted mixed-effect models demonstrated that elevated PM_2.5 exposure three days prior to cognitive assessment (lag-3) was associated with (1) declined performance in both congruent and incongruent tasks in Stroop test, (2) reduced lower and upper alpha event-related desynchronization (ERD) during 500-1000 ms after stimuli, both indicating impaired executive control. Lower and upper alpha ERD also mediated observed associations between short-term PM_2.5 exposure and executive function. No significant associations were found between short-term PM_2.5 exposure or aperiodic exponents in tonic and phasic states, or periodic alpha oscillations in tonic state.

CONCLUSION

Our results provided evidence that short-term PM_2.5 exposure was associated with executive dysfunction. Reduced alpha ERD was likely to be the underlying pathway through which PM_2.5 induced adverse effects on neuron activities during cognitive tasks.

Type of bilingualism conditions individual differences in the oscillatory dynamics of inhibitory control

The present study uses EEG time-frequency representations (TFRs) with a Flanker task to investigate if and how individual differences in bilingual language experience modulate neurocognitive outcomes (oscillatory dynamics) in two bilingual group types: late bilinguals (L2 learners) and early bilinguals (heritage speakers-HSs). TFRs were computed for both incongruent and congruent trials. The difference between the two (Flanker effect vis-à-vis cognitive interference) was then (1) compared between the HSs and the L2 learners, (2) modeled as a function of individual differences with bilingual experience within each group separately and (3) probed for its potential (a)symmetry between brain and behavioral data. We found no differences at the behavioral and neural levels for the between-groups comparisons. However, oscillatory dynamics (mainly theta increase and alpha suppression) of inhibition and cognitive control were found to be modulated by individual differences in bilingual language experience, albeit distinctly within each bilingual group. While the results indicate adaptations toward differential brain recruitment in line with bilingual language experience variation overall, this does not manifest uniformly. Rather, earlier versus later onset to bilingualism-the bilingual type-seems to constitute an independent qualifier to how individual differences play out.

Oscillatory and Aperiodic Neural Activity Jointly Predict Language Learning

Memory formation involves the synchronous firing of neurons in task-relevant networks, with recent models postulating that a decrease in low-frequency oscillatory activity underlies successful memory encoding and retrieval. However, to date, this relationship has been investigated primarily with face and image stimuli; considerably less is known about the oscillatory correlates of complex rule learning, as in language. Furthermore, recent work has shown that nonoscillatory (1/ƒ) activity is functionally relevant to cognition, yet its interaction with oscillatory activity during complex rule learning remains unknown. Using spectral decomposition and power-law exponent estimation of human EEG data (17 females, 18 males), we show for the first time that 1/ƒ and oscillatory activity jointly influence the learning of word order rules of a miniature artificial language system. Flexible word-order rules were associated with a steeper 1/ƒ slope, whereas fixed word-order rules were associated with a shallower slope. We also show that increased theta and alpha power predicts fixed relative to flexible word-order rule learning and behavioral performance. Together, these results suggest that 1/ƒ activity plays an important role in higher-order cognition, including language processing, and that grammar learning is modulated by different word-order permutations, which manifest in distinct oscillatory profiles.

Determinants of bilingualism predict dynamic changes in resting state EEG oscillations

This study uses resting state EEG data from 103 bilinguals to understand how determinants of bilingualism may reshape the mind/brain. Participants completed the LSBQ, which quantifies language use and crucially the division of labor of dual-language use in diverse activities and settings over the lifespan. We hypothesized correlations between the degree of active bilingualism with power of neural oscillations in specific frequency bands. Moreover, we anticipated levels of mean coherence (connectivity between brain regions) to vary by degree of bilingual language experience. Results demonstrated effects of Age of L2/2L1 onset on high beta and gamma powers. Higher usage of the non-societal language at home and society modulated indices of functional connectivity in theta, alpha and gamma frequencies. Results add to the emerging literature on the neuromodulatory effects of bilingualism for rs-EEG, and are in line with claims that bilingualism effects are modulated by degree of engagement with dual-language experiential factors.

Longitudinal qEEG changes correlate with clinical outcomes in patients with somatic symptom disorder

OBJECTIVE

The quantitative electroencephalography (qEEG) of patients with somatic symptom disorder (SSD) was not yet thoroughly studied. This study aimed to investigate qEEG of SSD patients compared with those of normal controls (NCs), and changes therein after treatment.

METHODS

SSD patients currently without treatment and age- and sex-matched NCs were recruited. Spectral analysis of 64-channel EEG recording was performed and somatization, anxiety, and depression were evaluated via self-rating scales at baseline. After six months of treatment as usual, SSD patients were longitudinally followed up for assessments.

RESULTS

At baseline, the SSD group (n = 44) had higher alpha (p = 0.047) and lower beta 2 (p = 0.027) and gamma power (p = 0.001) compared with NCs (n = 29). After 6-month treatment, SSD patients showed improvement in symptoms, as well as increased beta 1 (p = 0.032), beta 2 (p = 0.012), and gamma power (p = 0.009) compared with baseline. A significant correlation was observed between the change in somatization score and temporal gamma power (r = -0.424, p = 0.031), and between the change in anxiety score and beta 2 power in the frontal (r = -0.420, p = 0.033) and central (r = -0.484, p = 0.012) regions.

CONCLUSIONS

EEG findings in this study may provide neurophysiological features of SSD. The alpha enhancement and reduced fast wave activity may reflect attentional dysfunction in patients with SSD. Decreased fast wave activity is reversible and may serve as a state marker of SSD.

EEG Resting-State and Event-Related Potentials as Markers of Learning Success in Older Adults Following Second Language Training: A Pilot Study

OBJECTIVES

In this pilot study, we evaluated the use of electrophysiological measures at rest as paradigm-independent predictors of second language (L2) development for the first time in older adult learners. We then assessed EEG correlates of the learning outcome in a language-switching paradigm after the training, which to date has only been done in younger adults and at intermediate to advanced L2 proficiency.

METHODS

Ten (Swiss) German-speaking adults between 65-74 years of age participated in an intensive 3-week English training for beginners. A resting-state EEG was recorded before the training to predict the ensuing L2 development (Experiment 1). A language-switching ERP experiment was conducted after the training to assess the learning outcome (Experiment 2).

RESULTS

All participants improved their L2 skills but differed noticeably in their individual development. Experiment 1 showed that beta1 oscillations at rest (13-14.5 Hz) predicted these individual differences. We interpret resting-state beta1 oscillations as correlates of attentional capacities and semantic working memory that facilitate the extraction and processing of novel forms and meanings from the L2 input.In Experiment 2, we found that language switching from the L2 into the native language (L1) elicited an N400 component, which was reduced in the more advanced learners. Thus, for learners beginning the acquisition of an L2 in third age, language switching appears to become less effortful with increasing proficiency, suggesting that the lexicons of the L1 and L2 become more closely linked.

CONCLUSIONS

In sum, our findings extend the available evidence of neurological processes in L2 learning from younger to older adults, suggesting that electrophysiological mechanisms are similar across the lifespan.

Electrophysiological Prints of Grit

While scientific interest in understanding the grit trait has grown exponentially in recent years, one important gap in the grit literature relates to its biological and neural substrate. In the present study, we adopted a hypotheses-driven approach in a large sample of young adults (N = 120) with diverse educational backgrounds and work experiences in order to investigate the electrophysiological correlates of grit both during rest and while performing a learning task. Additionally, we selected a measure of impulsiveness to better understand the neural similarities and differences between grit and related self-control constructs. Based on previous work that implicated the prefrontal cortex in grit, we hypothesized that high grit participants would have lower frontal theta/beta ratio (a broadly used index that reflects prefrontally-mediated top-down processes, which might indicate better control over subcortical information). Furthermore, we expected the perseverance of effort facet of grit to be linked to higher complexity during task engagement because previous research has shown complexity indexes (entropy and fractal dimension) to be linked to effort while performing cognitive tasks. Our results revealed that although there were no differences at rest as a function of grit, the participants with high grit and high consistency of interest scores exhibited lower frontal theta/beta ratios during the learning task. This pattern suggests that individual differences in grit might be more evident when top-down control processes are at work. Furthermore, there was a positive association between perseverance of effort and entropy at task, which might indicate more effort and engagement in the task. Finally, no association was found between the neural indexes (frontal theta/beta ratio, entropy, or fractal dimension) and impulsiveness, neither impulsiveness mediated between grit and brain measures. Finally, when controlling for impulsiveness and demographic variables (gender, age, education, and work experience) the effects at the facet level remained statistically significant. While there is still a long way to fully understand the neural mechanisms of grit, the present work constitutes a step toward unveiling the electrophysiological prints of grit.

Multivariate patterns and long-range temporal correlations of alpha oscillations are associated with flexible manipulation of visual working memory representations

The ability to flexibly manipulate memory representations is embedded in visual working memory (VWM) and can be tested using paradigms with retrospective cues. Although valid retrospective cues often facilitate memory recall, invalid ones may or may not result in performance costs. We investigated individual differences in utilising retrospective cues and evaluated how these individual differences are associated with brain oscillatory activity at rest. At the behavioural level, we operationalised flexibility as the ability to make effective use of retrospective cues or disregard them if required. At the neural level, we tested whether individual differences in such flexibility were associated with properties of resting-state alpha oscillatory activity (8-12 Hz). To capture distinct aspects of these brain oscillations, we evaluated their power spectral density and temporal dynamics using long-range temporal correlations (LRTCs). In addition, we performed multivariate patterns analysis (MVPA) to classify individuals' level of behavioural flexibility based on these neural measures. We observed that alpha power alone (magnitude) at rest was not associated with flexibility. However, we found that the participants' ability to manipulate VWM representations was correlated with alpha LRTC and could be decoded using MVPA on patterns of alpha power. Our findings suggest that alpha LRTC and multivariate patterns of alpha power at rest may underlie some of the individual differences in using retrospective cues in working memory tasks.

The development of brain rhythms at rest and its impact on vocabulary acquisition

A long-standing question in developmental science is how the neurodevelopment of the brain influences cognitive functions. Here, we examined the developmental change of resting EEG power and its links to vocabulary acquisition in school-age children. We further explored what mechanisms may mediate the relation between brain rhythm maturation and vocabulary knowledge. Eyes-opened resting-state EEG data were recorded from 53 typically-developing Chinese children every 2 years between the ages of 7 and 11. Our results showed first that delta, theta, and gamma power decreased over time, whereas alpha and beta power increased over time. Second, after controlling for general cognitive abilities, age, home literacy environment, and phonological skills, theta decreases explained 6.9% and 14.4% of unique variance in expressive vocabulary at ages 9 and 11, respectively. We also found that beta increase from age 7 to 9 significantly predicted receptive vocabulary at age 11. Finally, theta decrease predicted expressive vocabulary through the effects of phoneme deletion at age 9 and tone discrimination at age 11. These results substantiate the important role of brain oscillations at rest, especially theta rhythm, in language development. The developmental change of brain rhythms could serve as sensitive biomarkers for vocabulary development in school-age children, which would be of great value in identifying children at risk of language impairment.

Resting-state brain oscillations predict cognitive function in psychiatric disorders: A transdiagnostic machine learning approach

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Resting EEG activity associated with cognitive function in psychiatric disorders.

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Using EEG, random forest modeling predicts cognitive performance but not diagnosis.

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High alpha oscillations associated with better episodic memory and processing speed.

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Beta oscillations associated with worse performance in several cognitive domains.

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EEG power changes in psychiatric disorders may be related to cognitive dysfunction.

Background

Cognitive dysfunction is widespread in psychiatric disorders and can significantly impact quality of life. Deficits cut across traditional diagnostic boundaries, necessitating new approaches to understand how cognitive function relates to large-scale brain activity and psychiatric symptoms across the diagnostic spectrum.

Objective

Using random forest regression, we aimed to identify transdiagnostic patterns linking cognitive function to resting-state EEG oscillations.

Methods

216 participants recruited through an outpatient psychiatric clinic completed the Cambridge Neuropsychological Test Automated Battery and underwent a 5-minute eyes-closed resting state EEG recording. We built random forest regression models to predict performance on each cognitive test using the resting-state EEG power spectrum as input, and we compared model performance to a sampling distribution constructed with random permutations. For models that performed significantly better than chance, we used feature importance estimates to identify features of the EEG power spectrum that are predictive of cognitive functioning.

Results

Random forest models successfully predicted performance on measures of episodic memory and associative learning (Paired Associates Learning, PAL), information processing speed (Choice Reaction Time, CRT), and attentional set-shifting and executive function (Intra-Extra Dimensional Set Shift, IED). Oscillatory power in the upper alpha range was associated with better performance on PAL and CRT, while low alpha power was associated with worse CRT performance. Beta power predicted poor performance on all three tests. Theta power was associated with good performance on PAL, and delta and theta oscillations were identified as predictors of good performance on IED. No differences in cognitive performance were found between diagnostic categories.

Conclusion

Resting oscillations are predictive of certain dimensions of cognitive function across various psychiatric disorders. These findings may inform treatment development to improve cognition.

Bilingualism and domain-general cognitive functions from a neural perspective: A systematic review

A large body of research has indicated that bilingualism - through continual practice in language control - may impact cognitive functions, as well as relevant aspects of brain function and structure. The present review aimed to bring together findings on the relationship between bilingualism and domain-general cognitive functions from a neural perspective. The final sample included 210 studies, covering findings regarding neural responses to bilingual language control and/or domain-general cognitive tasks, as well as findings regarding effects of bilingualism on non-task-related brain function and brain structure. The evidence indicates that a) bilingual language control likely entails neural mechanisms responsible for domain-general cognitive functions; b) bilingual experiences impact neural responses to domain-general cognitive functions; and c) bilingual experiences impact non-task-related brain function (both resting-state and metabolic function) as well as aspects of brain structure (both macrostructure and microstructure), each of which may in turn impact mental processes, including domain-general cognitive functions. Such functional and structural neuroplasticity associated with bilingualism may contribute to both cognitive and neural reserves, producing benefits across the lifespan.

Gauging Working Memory Capacity From Differential Resting Brain Oscillations in Older Individuals With A Wearable Device

Working memory is a core cognitive function and its deficits is one of the most common cognitive impairments. Reduced working memory capacity manifests as reduced accuracy in memory recall and prolonged speed of memory retrieval in older adults. Currently, the relationship between healthy older individuals’ age-related changes in resting brain oscillations and their working memory capacity is not clear. Eyes-closed resting electroencephalogram (rEEG) is gaining momentum as a potential neuromarker of mild cognitive impairments. Wearable and wireless EEG headset measuring key electrophysiological brain signals during rest and a working memory task was utilized. This research’s central hypothesis is that rEEG (e.g., eyes closed for 90 s) frequency and network features are surrogate markers for working memory capacity in healthy older adults. Forty-three older adults’ memory performance (accuracy and reaction times), brain oscillations during rest, and inter-channel magnitude-squared coherence during rest were analyzed. We report that individuals with a lower memory retrieval accuracy showed significantly increased alpha and beta oscillations over the right parietal site. Yet, faster working memory retrieval was significantly correlated with increased delta and theta band powers over the left parietal sites. In addition, significantly increased coherence between the left parietal site and the right frontal area is correlated with the faster speed in memory retrieval. The frontal and parietal dynamics of resting EEG is associated with the “accuracy and speed trade-off” during working memory in healthy older adults. Our results suggest that rEEG brain oscillations at local and distant neural circuits are surrogates of working memory retrieval’s accuracy and processing speed. Our current findings further indicate that rEEG frequency and coherence features recorded by wearable headsets and a brief resting and task protocol are potential biomarkers for working memory capacity. Additionally, wearable headsets are useful for fast screening of cognitive impairment risk.

Bilingual Language Experience Shapes Resting-State Brain Rhythms

An increasing body of research has investigated how bilingual language experience changes brain structure and function, including changes to task-free, or "resting-state" brain connectivity. Such findings provide important evidence about how the brain continues to be shaped by different language experiences throughout the lifespan. The neural effects of bilingual language experience can provide evidence about the additional processing demands placed on the linguistic and/or executive systems by dual-language use. While considerable research has used MRI to examine where these changes occur, such methods cannot reveal the temporal dynamics of functioning brain networks at rest. The current study used data from task-free EEGS to disentangle how the linguistic and cognitive demands of bilingual language use impact brain functioning. Data analyzed from 106 bilinguals and 91 monolinguals revealed that bilinguals had greater alpha power, and significantly greater and broader coherence in the alpha and beta frequency ranges than monolinguals. Follow-up analyses showed that higher alpha was related to language control: more second-language use, higher native-language proficiency, and earlier age of second-language acquisition. Bilateral beta power was related to native-language proficiency, whereas theta was related to native-language proficiency only in left-hemisphere electrodes. The results contribute to our understanding of how the linguistic and cognitive requirements of dual-language use shape intrinsic brain activity, and what the broader implications for information processing may be.

Relating Natural Language Aptitude to Individual Differences in Learning Programming Languages

This experiment employed an individual differences approach to test the hypothesis that learning modern programming languages resembles second "natural" language learning in adulthood. Behavioral and neural (resting-state EEG) indices of language aptitude were used along with numeracy and fluid cognitive measures (e.g., fluid reasoning, working memory, inhibitory control) as predictors. Rate of learning, programming accuracy, and post-test declarative knowledge were used as outcome measures in 36 individuals who participated in ten 45-minute Python training sessions. The resulting models explained 50-72% of the variance in learning outcomes, with language aptitude measures explaining significant variance in each outcome even when the other factors competed for variance. Across outcome variables, fluid reasoning and working-memory capacity explained 34% of the variance, followed by language aptitude (17%), resting-state EEG power in beta and low-gamma bands (10%), and numeracy (2%). These results provide a novel framework for understanding programming aptitude, suggesting that the importance of numeracy may be overestimated in modern programming education environments.

Monitoring of attentional oscillations through Spectral Similarity Analysis predicts reading comprehension

Deviations of attention from the task at hand are often associated with worse reading performance (Schooler, Reichle, & Halpern, 2004). Ironically, current methods for detecting these shifts of attention typically generate task interruptions and further disrupt performance. In the current study, we developed a method to (1) track shifts of attention away from the reading task by examining the similarity between 5 min of eyes-closed-resting-state EEG and 5 min reading EEG; and (2) investigate, during reading, how the ratio between attention shifts and focused reading relates to readers' comprehension. We performed a Spectral Similarity Analysis (SSA) that examined the spectral similarity between EEG recorded during reading and at rest on a moment-by-moment basis. We then recursively applied the algorithm to the resting-state data itself to obtain an individual baseline of the stability of brain activation recorded during rest. We defined any moment in which SSA during reading was greater than the mean correlation between resting-state EEG and itself as an "attentional shift." The results showed that the proportion of such attentional shifts recorded over the left visual region (O1) significantly predicted reading comprehension, with higher ratios (indicative of more frequent attentional shifts) relating to worse comprehension scores on the reading test. As a proof of its validity, the same measure collected during the reading comprehension test also predicted participants' Simon effect (incongruent - congruent response times) which is a common index of selective attention. This novel method allows researchers to detect attention shifts moments during reading without interrupting natural reading process.

Mechanisms for Auditory Perception: A Neurocognitive Study of Second Language Learning of Mandarin Chinese

Speech perception is an important early skill for language learning. This study uses functional magnetic resonance imaging (fMRI) to examine the relationship between auditory perception abilities and second language (L2) vocabulary learning in an effort to explore behavior-brain correlations. Twenty-one English monolinguals learned 48 auditory Chinese pseudowords over six weeks. Their pre-training abilities in non-linguistic pitch and linguistic tone perception significantly and positively predicted their novel word-learning performance, which correlated with their brain response patterns in the left Heschl’s gyrus. Analyses of regions of interest (ROIs) showed coactivation of the frontal and temporal regions during novel lexical retrieval, and the non-linguistic pitch perception ability modulated brain activations in these regions. Effective connectivity analyses further indicated a collaboration of a ventral stream for speech perception and a dorsal stream for sensory-motor mapping in the L2 network. The ventral stream, compared with the dorsal stream, played a more dominant role in auditory word learning as the L2 proficiency increased. Better pitch and tone perception abilities strengthened the ventral pathways and decreased the reliance on frontal regions. These findings are discussed in light of current models of speech processing and L2 learning.

Individual Differences in Resting-state Brain Rhythms Uniquely Predict Second Language Learning Rate and Willingness to Communicate in Adults

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.

Exploiting Language Variation to Better Understand the Cognitive Consequences of Bilingualism

Within the past decade, there has been an explosion of research investigating the cognitive consequences of bilingualism. However, a controversy has arisen specifically involving research claiming a "bilingual advantage" in executive function. In this brief review, we re-examine the nature of the "bilingual advantage" and suggest three themes for future research. First, there must be a theoretical account of how specific variation in language experience impacts aspects of executive function and domain general cognition. Second, efforts toward adequately characterizing the participants tested will be critical to interpreting results. Finally, designing studies that employ converging analytical approaches and sensitive methodologies will be important to advance our knowledge of the dynamics between bilingual language experience and cognition.

Neural oscillatory mechanisms during novel grammar learning underlying language analytical abilities

The goal of the present study was to investigate the initial phases of novel grammar learning on a neural level, concentrating on mechanisms responsible for individual variability between learners. Two groups of participants, one with high and one with average language analytical abilities, performed an Artificial Grammar Learning (AGL) task consisting of learning and test phases. During the task, EEG signals from 32 cap-mounted electrodes were recorded and epochs corresponding to the learning phases were analysed. We investigated spectral power modulations over time, and functional connectivity patterns by means of a bivariate, frequency-specific index of phase synchronization termed Phase Locking Value (PLV). Behavioural data showed learning effects in both groups, with a steeper learning curve and higher ultimate attainment for the highly skilled learners. Moreover, we established that cortical connectivity patterns and profiles of spectral power modulations over time differentiated L2 learners with various levels of language analytical abilities. Over the course of the task, the learning process seemed to be driven by whole-brain functional connectivity between neuronal assemblies achieved by means of communication in the beta band frequency. On a shorter time-scale, increasing proficiency on the AGL task appeared to be supported by stronger local synchronisation within the right hemisphere regions. Finally, we observed that the highly skilled learners might have exerted less mental effort, or reduced attention for the task at hand once the learning was achieved, as evidenced by the higher alpha band power.

"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.

The perisylvian language network and language analytical abilities

Aiming at exploring the brain's structural organisation underlying successful second language learning, we investigate the anatomy of the perisylvian language network in a group of healthy adults, consisting of participants with high and average language analytical abilities. Utilising deterministic tractography, six tracts per participant (left and right long direct segment, left and right indirect anterior segment and left and right indirect posterior segment) were virtually dissected and measurements pertaining to their microstructural organisation were collected. Our results obtained by means of linear discriminant analysis pointed to mean diffusivity (MD) values of three tracts (right anterior, left long and left anterior segments) as best discriminating between the two groups. By far the highest coefficient was obtained for the MD values of the right anterior segment, pointing to the role of the right white matter fronto-parietal connectivity for superior language learning abilities. The results imply the importance of attentional processes and reasoning abilities for successful L2 acquisition, and support previous findings concerning right-hemispheric involvement in language learning.

Native-language N400 and P600 predict dissociable language-learning abilities in adults

Language learning aptitude during adulthood varies markedly across individuals. An individual's native-language ability has been associated with success in learning a new language as an adult. However, little is known about how native-language processing affects learning success and what neural markers of native-language processing, if any, are related to success in learning. We therefore related variation in electrophysiology during native-language processing to success in learning a novel artificial language. Event-related potentials (ERPs) were recorded while native English speakers judged the acceptability of English sentences prior to learning an artificial language. There was a trend towards a double dissociation between native-language ERPs and their relationships to novel syntax and vocabulary learning. Individuals who exhibited a greater N400 effect when processing English semantics showed better future learning of the artificial language overall. The N400 effect was related to syntax learning via its specific relationship to vocabulary learning. In contrast, the P600 effect size when processing English syntax predicted future syntax learning but not vocabulary learning. These findings show that distinct neural signatures of native-language processing relate to dissociable abilities for learning novel semantic and syntactic information.

Fronto-Parietal Contributions to Phonological Processes in Successful Artificial Grammar Learning

Sensitivity to regularities plays a crucial role in the acquisition of various linguistic features from spoken language input. Artificial grammar learning paradigms explore pattern recognition abilities in a set of structured sequences (i.e., of syllables or letters). In the present study, we investigated the functional underpinnings of learning phonological regularities in auditorily presented syllable sequences. While previous neuroimaging studies either focused on functional differences between the processing of correct vs. incorrect sequences or between different levels of sequence complexity, here the focus is on the neural foundation of the actual learning success. During functional magnetic resonance imaging (fMRI), participants were exposed to a set of syllable sequences with an underlying phonological rule system, known to ensure performance differences between participants. We expected that successful learning and rule application would require phonological segmentation and phoneme comparison. As an outcome of four alternating learning and test fMRI sessions, participants split into successful learners and non-learners. Relative to non-learners, successful learners showed increased task-related activity in a fronto-parietal network of brain areas encompassing the left lateral premotor cortex as well as bilateral superior and inferior parietal cortices during both learning and rule application. These areas were previously associated with phonological segmentation, phoneme comparison, and verbal working memory. Based on these activity patterns and the phonological strategies for rule acquisition and application, we argue that successful learning and processing of complex phonological rules in our paradigm is mediated via a fronto-parietal network for phonological processes.