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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.
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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.
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Сравнительный анализ методик изучения рабочей памяти в фМРТ- и МЭГ-исследованиях

Экспериментальная психология. 2025. Т. 18. № 1. С. 181–199.
Pechenkova E., Королькова О. А., Паникратова Я. Р., Пчелинцева М. Е., Синицын В. Е.

Context and relevance. To date, the study of brain correlates of working memory (WM) is associated with
a number of theoretical as well as methodological difficulties. Firstly, substantially variable tasks are used
to assess WM. Secondly, each neuroimaging method has its own characteristics and limitations. Objective.
The aim of this paper was to systematize the tasks used to study the brain correlates of WM, as well as to
analyze these paradigms in terms of the possibility and feasibility of their parallel use in fMRI and MEG
studies, taking into account the specific requirements of both methods. Methods and materials. A literature
search in the PubMed database identified 1,505 empirical studies published from 1995 to 2023 in which
brain correlates of WM were studied using fMRI and/or MEG. The vast majority of them (1,398) used
fMRI; 103 used MEG; 4 studies used both methods. Results. The analysis showed that the most frequently
used tasks are the n-back task and the delayed match-to-sample task, including the Sternberg task. The con-
sidered tasks can use both verbal (e.g., letters, numbers, words, etc.) and non-verbal stimuli; they can be pre-
sented in different modalities (visual, auditory, and even tactile or vibrotactile). Conclusions. The features
of these tasks and the possibility of their implementation in studies using fMRI and MEG are described.

Research target: Psychology
Language: Russian
Full text
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Text on another site
Keywords: working memoryрабочая памятьMEGМЭГфМРТfMRIn-back taskзадача СтернбергаSternberg taskзадача «N шагов назад» (N-back)
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