The Role Of Individual Differences In Bilingual Language Processing

In this thesis, I investigated the neural correlates of bilingualism, and how individual differences in both brain and behaviour affect second language processing. To date, theories of bilingualism have tended to treat bilinguals as a uniform group, while in practice they vary greatly in both experience and ability. By examining how individual differences in proficiency and age of acquisition contribute to second language learning and processing, I sought to address this issue. In chapter two, I used event-related potentials to investigate how age of acquisition and proficiency modulate processing of a novel versus a grammatical rule that is similar across languages. I provided evidence that both age of acquisition and proficiency, in addition to bilingual status, modulate processing of a novel grammatical rule. In contrast, only proficiency predicted processing of a similar grammatical rule. Thus, while the similarities between languages affect second language processing, the degree of their influence is modulated by individual differences in second language experience. In chapter three, I used functional magnetic resonance imaging to investigate how bilinguals represent their shared, integrated lexicons in the brain. Several areas showed differing patterns of representation, while univariate analyses in these areas showed no differences in levels of activation. The separate representation of first and second languages in these regions provides a possible basis for the neurocognitive realization of a shared, integrated lexicon proposed by many theories of bilingualism. In chapter four, I used diffusion tensor imaging to investigate how AoA modulates white matter microstructure, examining white matter tracts in the left and right hemispheres that underlie language processing. Group statistics suggested that second language speakers as a whole may have lower fractional anisotropy, while the within-group analysis revealed that white matter integrity is sensitive to individual experience. Chapter five discusses the relevant findings of the previous chapters, and considers how individual differences arise. Next, I make recommendations for theories of bilingual language processing, and close with a discussion of future research directions

The influence of proficiency and age of acquisition on second language processing: An fMRI study of Mandarin-English bilinguals

Research investigating the neural correlates of second language (L2) processing has usually studied age of acquisition (AoA) and proficiency separately. Presently, we examined both in parallel, treated as continuous variables. We used fMRI to study neural activity for L2 processing in adult native Mandarin speakers who are L2 English speakers. Behavioral measures of language proficiency and AoA were obtained from subjects prior to performing a picture-word matching task during an fMRI scan. Brain activity during L2 English processing was shown to be independently affected by AoA and proficiency; activity in left superior temporal gyrus and right parahippocampal gyrus was modulated by AoA when L2 proficiency is accounted for, while activity in right insula, right middle temporal gyrus, and left parahippocampal gyrus was modulated by L2 proficiency regardless of AoA. These results suggest that brain organization of L2 lexico-semantic processing is susceptible to L2 ability levels as well as age-dependent learning

A Transdiagnostic Examination of Cognitive Heterogeneity in Children and Adolescents with Neurodevelopmental Disorders

Children and adolescents with neurodevelopmental disorders (NDDs) demonstrate extensive cognitive heterogeneity that is not adequately captured by traditional diagnostic systems. Using a transdiagnostic approach, a retrospective cohort study of cognitive functioning was conducted with a large heterogenous sample (n = 1529) of children and adolescents 7 to 18 years of age with NDDs. Measures of short-term memory, verbal ability, and reasoning were administered to participants with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), comorbid ADHD/ASD, and typically developing (TD) participants using a 12-item web-based neurocognitive testing battery. Unsupervised machine learning techniques were implemented to create a self-organizing map (SOM), an artificial neural network, in conjunction with k-means clustering algorithms to identify data-driven subgroups. Six clusters representing different cognitive profiles were identified, including participants with varying degrees of cognitive impairment. Diagnostic status did not correspond with cluster-membership, providing evidence for the application of transdiagnostic approaches to understanding cognitive heterogeneity in children and adolescents with NDDs. Additionally, the findings suggest that many TD participants may have undiagnosed learning difficulties, emphasizing the need for accessible cognitive assessment tools in school-based settings

Cognition across the lifespan: Investigating age, sex, and other sociodemographic influences

Maintaining cognitive health across the lifespan has been the focus of a multi-billion-dollar industry. In order to guide treatment and interventions, a clear understanding of the way that proficiency in different cognitive domains develops and declines in both sexes across the lifespan is necessary. Additionally, there are sex differences in a range of other factors, including psychiatric illnesses such as anxiety, depression, and substance use, that are also known to affect cognition, although the scale of this interaction is unknown. Our objective was to assess differences in cognitive function across the lifespan in men and women in a large, representative sample. Leveraging online cognitive testing, a sample of 9451 men and 9451 women ranging in age from 12 to 69 (M = 28.21) matched on socio-demographic factors were studied. Segmented regression was used to model three cognitive domains—working memory, verbal abilities, and reasoning. Sex differences in all three domains were minimal; however, after broadening the sample in terms of socio-demographic factors, sex differences appeared. These results suggest that cognition across the lifespan differs for men and women, but is greatly influenced by environmental factors. We discuss these findings within a framework that describes sex differences in cognition as likely guided by a complex interplay between biology and environment

Late positive complex in event-related potentials tracks memory signals when they are decision relevant.

The Late Positive Complex (LPC) is an Event-Related Potential (ERP) consistently observed in recognition-memory paradigms. In the present study, we investigated whether the LPC tracks the strength of multiple types of memory signals, and whether it does so in a decision dependent manner. For this purpose, we employed judgements of cumulative lifetime exposure to object concepts, and judgements of cumulative recent exposure (i.e., frequency judgements) in a study-test paradigm. A comparison of ERP signatures in relation to degree of prior exposure across the two memory tasks and the study phase revealed that the LPC tracks both types of memory signals, but only when they are relevant to the decision at hand. Another ERP component previously implicated in recognition memory, the FN400, showed a distinct pattern of activity across conditions that differed from the LPC; it tracked only recent exposure in a decision-dependent manner. Another similar ERP component typically linked to conceptual processing in past work, the N400, was sensitive to degree of recent and lifetime exposure, but it did not track them in a decision dependent manner. Finally, source localization analyses pointed to a potential source of the LPC in left ventral lateral parietal cortex, which also showed the decision-dependent effect. The current findings highlight the role of decision making in ERP markers of prior exposure in tasks other than those typically used in studies of recognition memory, and provides an initial link between the LPC and the previously suggested role of ventral lateral parietal cortex in memory judgements

Bilingualism Affords No General Cognitive Advantages: A Population Study of Executive Function in 11,000 People

Whether acquiring a second language affords any general advantages to executive function has been a matter of fierce scientific debate for decades. If being bilingual does have benefits over and above the broader social, employment, and lifestyle gains that are available to speakers of a second language, then it should manifest as a cognitive advantage in the general population of bilinguals. We assessed 11,041 participants on a broad battery of 12 executive tasks whose functional and neural properties have been well described. Bilinguals showed an advantage over monolinguals on only one test (whereas monolinguals performed better on four tests), and these effects all disappeared when the groups were matched to remove potentially confounding factors. In any case, the size of the positive bilingual effect in the unmatched groups was so small that it would likely have a negligible impact on the cognitive performance of any individual

Prenatal and postpartum maternal mental health and neonatal motor outcomes during the COVID-19 pandemic

Background: Rates of prenatal and postpartum stress and depression in pregnant individuals have increased during the COVID-19 pandemic. Perinatal maternal mental health has been linked to worse motor development in offspring, with motor deficits appearing in infancy and early childhood. We aimed to evaluate the relationship between prenatal and postpartum stress and depression and motor outcome in infants born during the COVID-19 pandemic. Methods: One hundred and seventeen participants completed an online prospective survey study at two timepoints: during pregnancy and within 2 months postpartum. Depression was self-reported using the Edinburgh Perinatal/Postpartum Depression Scale (EPDS), and stress via the Perceived Stress Scale (PSS). Mothers reported total infant motor ability (fine and gross) using the interRAI 0–3 Developmental Domains questionnaire. Results: Prenatal (EPDS median=10.0, interquartile range[IQR]=6.0 – 14.0, B=-0.035, 95%CI=-0.062 to -0.007, p = 0.014) and postpartum maternal depression outcomes (median=7, IQR=4–12, B=-0.037, 95%CI= -0.066 to -0.008, p = 0.012) were significantlynegatively associated with total infant motor ability. Neither pregnancy nor postpartum perceived stress was associated with infant motor function. A cluster analysis revealed that preterm and low-birth weight infants whose mothers reported elevated depressive symptoms during pregnancy and in the postpartum period had the poorest motor outcomes. Conclusions: Prenatal and postpartum depression, but not stress, was associated with early infant motor abilities. Preterm and low-birth weight infants whose mothers reported elevated depressive symptoms maybe at-risk of experiencing poor motor outcomes. These results highlight the importance of identifying pre- and postnatal maternal mental health issues, especially during the ongoing COVID-19 pandemic

Machine learning-based predictive modeling of resilience to stressors in pregnant women during COVID-19: A prospective cohort study

During the COVID-19 pandemic, pregnant women have been at high risk for psychological distress. Lifestyle factors may be modifiable elements to help reduce and promote resilience to prenatal stress. We used Machine-Learning (ML) algorithms applied to questionnaire data obtained from an international cohort of 804 pregnant women to determine whether physical activity and diet were resilience factors against prenatal stress, and whether stress levels were in turn predictive of sleep classes. A support vector machine accurately classified perceived stress levels in pregnant women based on physical activity behaviours and dietary behaviours. In turn, we classified hours of sleep based on perceived stress levels. This research adds to a developing consensus concerning physical activity and diet, and the association with prenatal stress and sleep in pregnant women. Predictive modeling using ML approaches may be used as a screening tool and to promote positive health behaviours for pregnant women