Search bioRxiv⌕ Search

bioRxiv · 10.1101/2022.10.06.510955

Functional neural architecture of cognitive control mediates the relationship between individual differences in bilingual experience and behaviour

Abstract

Bilinguals have often, but not always, been found to outperform monolinguals on domain-general attentional control. Inconsistent findings have been argued to stem, at least partly, from treating bilingualism as a uniform category and from not considering how neural adaptations to bilingual experiences modulate behavioural outcomes. The present study investigated how patterns of language experience, including language switching behaviour, duration and intensity/diversity of bilingual language use, influence the brain processes underlying cognitive control, and how these in turn translate to cognitive control performance. We examined reaction times and spectral dynamics of the electroencephalograms (EEG) of two-hundred-and-thirty-nine participants (about 70% bilinguals) with diverse language experiences during two cognitive control paradigms testing interference suppression (flanker and Simon task). Using structural equation modelling, we found that different bilingual experience factors were related with neurocognitive measures, which in turn were related with behavioural interference effects, for the flanker but not the Simon task. More specifically, increased frequency of language switching and intensity / diversity of bilingual language usage was negatively related to induced top-down control measures (especially midline-frontal theta), which in turn was beneficial for interference control. In contrast, duration of bilingual engagement correlated negatively with evoked bottom-up control measures (especially P3) and was therefore detrimental to interference control. We demonstrate here for the first time how the different factors of bilingual experience lead to different neural adaptations which impact behavioural outcomes. Significance statementLike other intensive experiences, bilingualism leads to brain adaptations. It results in structural changes in language areas, and, due to demands on language control, in brain areas associated with domain-general cognitive control. Related to this, bilinguals often outperform monolinguals on cognitive control tasks. But what is often ignored is that bilingualism is a multi-dimensional phenomenon, with variations such as diversity of language usage and duration of language use. The present large-scale study of neural functioning in bilingualism revealed for the first time how individual differences in bilingual experience lead to adaptations to brain functioning which in turn affect cognitive control behaviour. It exemplifies how the complexity of individual experiences plays a fundamental role in brain function.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Carter, F., DeLuca, V., Segaert, K., Mazaheri, A., Krott, A.. 2022-10-07. Functional neural architecture of cognitive control mediates the relationship between individual differences in bilingual experience and behaviour. https://doi.org/10.1101/2022.10.06.510955

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗