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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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The impact of language proficiency on task-dependent neural activity and functional connectivity: Insights from deafness

Cerebral Cortex. 2026. Vol. 36. No. 1. Article bhaf332.
Vinogradova V., Manini B., Woll B., Eimer M., Cardin V.

Our study investigates how language proficiency impacts cognitive processing in the brain. We focused on congenitally and early deaf adults, where individual differences in language access during development significantly influence language proficiency and cognitive function. This variability in language backgrounds and skills, allows us to explore the influence of early language experience on the large-scale brain networks that support cognition. We used functional MRI in a group of deaf adults with diverse language backgrounds and a control group of hearing participants. We hypothesised that differences in language skills would modulate neural responses and functional connectivity in task-related networks during the execution of demanding working memory and planning tasks. Our study revealed that differences in language proficiency, independently of language modality (signed or spoken), are positively correlated with neural activity and functional connectivity within the task-positive network during working memory in deaf adults. Furthermore, compared to hearing participants, the deaf group showed distinct patterns of neural activity and connectivity in task-dependent regions in the working memory experiment. Our findings emphasise the profound impact of early environmental experiences on brain responses during cognitive processing. Specifically, they highlight the role of language proficiency in shaping and supporting higher-order cognition.

Research target: Philology and Linguistics
Language: English
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DOI
Text on another site
Keywords: planningfMRIfunctional connectivity working memorydeafness
Publication based on the results of:
Neural foundations of language and its impairments: From basic research to clinical practice (2025)
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