bioRxiv Science⌕ Search

bioRxiv · 10.1101/2021.07.20.452909

A neural signature of automatic lexical access in bilinguals

Abstract

Bilingualism is often associated with beneficial effects on cognitive control and top-down processes. The present study aimed at bypassing these processes to assess automatic visual word recognition in bilinguals. Using fast periodic visual stimulation, we recorded frequency-tagged word-selective EEG responses in French monolinguals and late bilinguals (German native, French as second language). Words were presented centrally within rapid (10 Hz) sequences of letter strings varying in word-likeness, i.e., consonant strings, non-words, pseudo-words, while participants performed an orthogonal task. Automatic word-selective brain responses in the occipito-temporal cortex arose almost exclusively for the languages mastered by participants: two in bilinguals vs. one in monolinguals. Importantly, the amplitude of bilinguals responses to words within consonant strings were unaffected by the native vs. late-learnt status of the language. Furthermore, for all and only known languages, word-selective responses were reduced by embedding them in pseudo-words relative to non-words, both derived from the same language as the words. This word-likeness effect highlights the lexical nature of the recorded brain visual responses. A cross-language word-likeness effect was observed only in bilinguals and only with pseudo-words derived from the native language, indicating an experience-based tuning to language. Taken together these findings indicate that the amount of exposure to a language determines the engagement of neural resources devoted to word processing in the occipito-temporal visual cortex. We conclude that automatic lexical coding occurs at early visual processing in bilinguals and monolinguals alike, and that language exposure determines the competition strength of a language. Significance StatementBilingualism and its possible impact on automatic processes have rarely attracted interest, contrary to bilingualism and its mutual relation with the executive functions. We assessed automatic visual word recognition in bi- and monolingual individuals while purposively bypassing executive functions. Visual brain potentials frequency tagged to words, that were flashed in rapid trains of strings with varying word-likeness degrees, exposed the automatic encoding of word-form as well as language identity at early stages of visual word processing within the occipito-temporal visual cortex. The mechanisms involved in both encoding processes reflect experience-based activity as the one characterizing tight-tuned neurons in the VWFA. Our findings provide a novel framework to understand the mechanisms behind the incredible efficiency of bilinguals in handling multiple languages.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Aristei, S., Lochy, A., Rossion, B., Schiltz, C.. 2021-07-21. A neural signature of automatic lexical access in bilinguals. https://doi.org/10.1101/2021.07.20.452909

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↗