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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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When Do You Grasp The Idea? MEG Evidence For Instantaneous Idiom Understanding

Neuroimage. 2012. Vol. 59. P. 3502–3513.
Boulenger V., Shtyrov Y., Pulvermuller F.

We investigated the time-course of cortical activation during comprehension of literal and idiomatic sentences using MEG and anatomically guided distributed source analysis. Previous fMRI work had shown that the comprehension of sentences including action-related words elicits somatotopic semantic activation along the motor strip, reflecting meaning aspects of constituent words. Furthermore, idioms more strongly activated temporal pole and prefrontal cortex than literal sentences. Here we show that, compared to literal sentences, processing of idioms in a silent reading task modulates anterior fronto-temporal activity very early-on, already 150-250 ms after the sentences' critical disambiguating words ("kick the habit"). In parallel, the meaning of action words embedded in sentences is reflected by somatotopic activation of precentral motor systems. As neural reflections of constituent parts of idiomatic sentences are manifest at the same early latencies as brain indexes of idiomatic vs. literal meaning processing, we suggest that within ¼ of a second, compositional and abstract context-driven semantic processes in parallel contribute to the understanding of idiom meaning.

Research target: Philology and Linguistics Psychology Earth Sciences Biology
Priority areas: humanitarian
Language: English
Text on another site
Keywords: language comprehensionMEGmotor cortex
Publication based on the results of:
Neurocognitive mechanisms of decision making and social influence (2014)
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