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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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Use of magnetoencephalography (MEG) for the functional motor cortex localization: extraction and localization of the motor component in movement preparation processes by Independent Component Analysis

P. 41–42.
Pronko P. K., Chayanov N. V., Prokofyev A. O., Chernyshev V. Boris, Stroganova T. A.

The problem of non-invasive preoperative localization of motor areas in human cortex has not been solved yet. In clinical practice, localization of the hand representation in the primary motor cortex often becomes one of the main goals of the pre-surgical evaluation. In healthy subjects the area of the motor hand representation usually corresponds to certain standard anatomical landmarks (hand knob in the precentral gyrus), which can be easily found in sMRI images. Unfortunately, in patients with various brain lesions these landmarks may be absent or not corresponding to the area of the motor cortex. In such cases, location of irreplacable areas must be determined according to their functional and/or temporal dynamical characteristics.

It might become a promising method of localizing primary motor area by way of taking into account the characteristic properties of the primary motor cortex temporal dynamics during movement preparation.

Language: English
Keywords: MEGnon-invasive preoperative localizationmotor areashuman cortexIndependent Component Analysismotor component
Publication based on the results of:
The Psychophysiology of Sustained Attention and Perception in Conditions of Impeded Decision Making in Relation to Individual Differences (2012)

In book

International Symposium on Functional Neuroimaging: Basic Research and Clinical Applications. Abstracts
MSUPE, 2012.
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